diff --git a/.history/README_20250512195144.md b/.history/README_20250512195144.md
deleted file mode 100644
index 38fdb2fa03b514d2a45782dcba7953e79ed70a22..0000000000000000000000000000000000000000
--- a/.history/README_20250512195144.md
+++ /dev/null
@@ -1,110 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).  
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-  
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS {table_name}_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
-
diff --git a/.history/README_20250513101814.md b/.history/README_20250513101814.md
deleted file mode 100644
index 620aaab5c4ae9c9f0db5f5d08be8284a08c94d82..0000000000000000000000000000000000000000
--- a/.history/README_20250513101814.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS {table_name}_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101818.md b/.history/README_20250513101818.md
deleted file mode 100644
index 620aaab5c4ae9c9f0db5f5d08be8284a08c94d82..0000000000000000000000000000000000000000
--- a/.history/README_20250513101818.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS {table_name}_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101823.md b/.history/README_20250513101823.md
deleted file mode 100644
index 620aaab5c4ae9c9f0db5f5d08be8284a08c94d82..0000000000000000000000000000000000000000
--- a/.history/README_20250513101823.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS {table_name}_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101828.md b/.history/README_20250513101828.md
deleted file mode 100644
index b31f2b017b5fb0e9e57a3c62cb5680a4b3ac4e04..0000000000000000000000000000000000000000
--- a/.history/README_20250513101828.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101829.md b/.history/README_20250513101829.md
deleted file mode 100644
index b31f2b017b5fb0e9e57a3c62cb5680a4b3ac4e04..0000000000000000000000000000000000000000
--- a/.history/README_20250513101829.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101830.md b/.history/README_20250513101830.md
deleted file mode 100644
index b31f2b017b5fb0e9e57a3c62cb5680a4b3ac4e04..0000000000000000000000000000000000000000
--- a/.history/README_20250513101830.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-f"CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-f'CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101834.md b/.history/README_20250513101834.md
deleted file mode 100644
index 735c14b652bd034c38e759746d99a1bb15e54967..0000000000000000000000000000000000000000
--- a/.history/README_20250513101834.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101836.md b/.history/README_20250513101836.md
deleted file mode 100644
index 735c14b652bd034c38e759746d99a1bb15e54967..0000000000000000000000000000000000000000
--- a/.history/README_20250513101836.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101846.md b/.history/README_20250513101846.md
deleted file mode 100644
index 735c14b652bd034c38e759746d99a1bb15e54967..0000000000000000000000000000000000000000
--- a/.history/README_20250513101846.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513101854.md b/.history/README_20250513101854.md
deleted file mode 100644
index 735c14b652bd034c38e759746d99a1bb15e54967..0000000000000000000000000000000000000000
--- a/.history/README_20250513101854.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513102004.md b/.history/README_20250513102004.md
deleted file mode 100644
index a367e268cc7a2326aec483dc170e9e7ff81465c3..0000000000000000000000000000000000000000
--- a/.history/README_20250513102004.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{EMPTY_OBJECT}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513102007.md b/.history/README_20250513102007.md
deleted file mode 100644
index c3d365acc023694904ba937327d16a887ea95bd4..0000000000000000000000000000000000000000
--- a/.history/README_20250513102007.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513102008.md b/.history/README_20250513102008.md
deleted file mode 100644
index c3d365acc023694904ba937327d16a887ea95bd4..0000000000000000000000000000000000000000
--- a/.history/README_20250513102008.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP2. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513103952.md b/.history/README_20250513103952.md
deleted file mode 100644
index ade2a91d10cb30b9dd44311f8e8baee5e4760506..0000000000000000000000000000000000000000
--- a/.history/README_20250513103952.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP 2】. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513103953.md b/.history/README_20250513103953.md
deleted file mode 100644
index bbbb69d09f7e7c035cd6ce3721c65da414120c87..0000000000000000000000000000000000000000
--- a/.history/README_20250513103953.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using SigLIP 2]. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513103954.md b/.history/README_20250513103954.md
deleted file mode 100644
index 5c324a23106bb9aece84f94c8789c4a7ee558bec..0000000000000000000000000000000000000000
--- a/.history/README_20250513103954.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2]. All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513103957.md b/.history/README_20250513103957.md
deleted file mode 100644
index aac87ccf5b8e151182ff7fbb959e219caa6ec917..0000000000000000000000000000000000000000
--- a/.history/README_20250513103957.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104028.md b/.history/README_20250513104028.md
deleted file mode 100644
index bcb9b1c858c23b68af40b754d10e1cd18bd09079..0000000000000000000000000000000000000000
--- a/.history/README_20250513104028.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104030.md b/.history/README_20250513104030.md
deleted file mode 100644
index aca39335f18a4ed535be2305d2f1ec242343eb5c..0000000000000000000000000000000000000000
--- a/.history/README_20250513104030.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M] image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104031.md b/.history/README_20250513104031.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104031.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104042.md b/.history/README_20250513104042.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104042.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104044.md b/.history/README_20250513104044.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104044.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104103.md b/.history/README_20250513104103.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104103.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104104.md b/.history/README_20250513104104.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104104.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104204.md b/.history/README_20250513104204.md
deleted file mode 100644
index 1937f5c3d6a693b2100278394cc0cc9702a73df6..0000000000000000000000000000000000000000
--- a/.history/README_20250513104204.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104207.md b/.history/README_20250513104207.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104207.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104211.md b/.history/README_20250513104211.md
deleted file mode 100644
index 45886a330218f8a2f165b63fe6ab7c2717ce653f..0000000000000000000000000000000000000000
--- a/.history/README_20250513104211.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated Public Domain 12M[PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104214.md b/.history/README_20250513104214.md
deleted file mode 100644
index 4b3ea61fa033dd2f43d86acd710a6adf0dd1aade..0000000000000000000000000000000000000000
--- a/.history/README_20250513104214.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [PD12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104216.md b/.history/README_20250513104216.md
deleted file mode 100644
index 1937f5c3d6a693b2100278394cc0cc9702a73df6..0000000000000000000000000000000000000000
--- a/.history/README_20250513104216.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104217.md b/.history/README_20250513104217.md
deleted file mode 100644
index 1937f5c3d6a693b2100278394cc0cc9702a73df6..0000000000000000000000000000000000000000
--- a/.history/README_20250513104217.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://huggingface.co/datasets/Spawning/PD12M) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513104240.md b/.history/README_20250513104240.md
deleted file mode 100644
index 7aeb93850069ee82fdf445f94996362862689ff4..0000000000000000000000000000000000000000
--- a/.history/README_20250513104240.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111012.md b/.history/README_20250513111012.md
deleted file mode 100644
index cc0acefc85388798f6ee448899f9fc98caa9e23f..0000000000000000000000000000000000000000
--- a/.history/README_20250513111012.md
+++ /dev/null
@@ -1,108 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111014.md b/.history/README_20250513111014.md
deleted file mode 100644
index 6454809aac06bcb7f7c038a5b5afe1ec0978193c..0000000000000000000000000000000000000000
--- a/.history/README_20250513111014.md
+++ /dev/null
@@ -1,108 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-    2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111019.md b/.history/README_20250513111019.md
deleted file mode 100644
index 05d7941f92c5c66ff9ff720058854b9790d3cc3c..0000000000000000000000000000000000000000
--- a/.history/README_20250513111019.md
+++ /dev/null
@@ -1,108 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-    1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111025.md b/.history/README_20250513111025.md
deleted file mode 100644
index 7aeb93850069ee82fdf445f94996362862689ff4..0000000000000000000000000000000000000000
--- a/.history/README_20250513111025.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111029.md b/.history/README_20250513111029.md
deleted file mode 100644
index 4353a3b77af61d4c4129877a18797737094bc114..0000000000000000000000000000000000000000
--- a/.history/README_20250513111029.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111030.md b/.history/README_20250513111030.md
deleted file mode 100644
index 4353a3b77af61d4c4129877a18797737094bc114..0000000000000000000000000000000000000000
--- a/.history/README_20250513111030.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111034.md b/.history/README_20250513111034.md
deleted file mode 100644
index b79bb9b238fa80e713e4306bb29da934e039f71b..0000000000000000000000000000000000000000
--- a/.history/README_20250513111034.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111035.md b/.history/README_20250513111035.md
deleted file mode 100644
index b79bb9b238fa80e713e4306bb29da934e039f71b..0000000000000000000000000000000000000000
--- a/.history/README_20250513111035.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111036.md b/.history/README_20250513111036.md
deleted file mode 100644
index b79bb9b238fa80e713e4306bb29da934e039f71b..0000000000000000000000000000000000000000
--- a/.history/README_20250513111036.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111037.md b/.history/README_20250513111037.md
deleted file mode 100644
index b79bb9b238fa80e713e4306bb29da934e039f71b..0000000000000000000000000000000000000000
--- a/.history/README_20250513111037.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111043.md b/.history/README_20250513111043.md
deleted file mode 100644
index 7aeb93850069ee82fdf445f94996362862689ff4..0000000000000000000000000000000000000000
--- a/.history/README_20250513111043.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111045.md b/.history/README_20250513111045.md
deleted file mode 100644
index 7aeb93850069ee82fdf445f94996362862689ff4..0000000000000000000000000000000000000000
--- a/.history/README_20250513111045.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-## Dataset Structure
diff --git a/.history/README_20250513111058.md b/.history/README_20250513111058.md
deleted file mode 100644
index d372e33ecebee9578980449cbfd4632d3003a714..0000000000000000000000000000000000000000
--- a/.history/README_20250513111058.md
+++ /dev/null
@@ -1,107 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513111111.md b/.history/README_20250513111111.md
deleted file mode 100644
index 18a4fdd88d62b470f814ab29aee7551b74443cab..0000000000000000000000000000000000000000
--- a/.history/README_20250513111111.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513111112.md b/.history/README_20250513111112.md
deleted file mode 100644
index 722238e20f21d55e79ef27ae1f3278b601907740..0000000000000000000000000000000000000000
--- a/.history/README_20250513111112.md
+++ /dev/null
@@ -1,111 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513111216.md b/.history/README_20250513111216.md
deleted file mode 100644
index 7c1fdccf5d35a39ddca753d74d8c9a8e465581a9..0000000000000000000000000000000000000000
--- a/.history/README_20250513111216.md
+++ /dev/null
@@ -1,158 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513111230.md b/.history/README_20250513111230.md
deleted file mode 100644
index 0b86debe32dde9cf7be4eef0bab8149e4f8b36d8..0000000000000000000000000000000000000000
--- a/.history/README_20250513111230.md
+++ /dev/null
@@ -1,160 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112320.md b/.history/README_20250513112320.md
deleted file mode 100644
index 793d201f5d126c4c23b0a8f39d4a7b7665cc68dd..0000000000000000000000000000000000000000
--- a/.history/README_20250513112320.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112324.md b/.history/README_20250513112324.md
deleted file mode 100644
index 793d201f5d126c4c23b0a8f39d4a7b7665cc68dd..0000000000000000000000000000000000000000
--- a/.history/README_20250513112324.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112325.md b/.history/README_20250513112325.md
deleted file mode 100644
index a669131059b7b393d5e111e7878fe66fef94e564..0000000000000000000000000000000000000000
--- a/.history/README_20250513112325.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112329.md b/.history/README_20250513112329.md
deleted file mode 100644
index 793d201f5d126c4c23b0a8f39d4a7b7665cc68dd..0000000000000000000000000000000000000000
--- a/.history/README_20250513112329.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112332.md b/.history/README_20250513112332.md
deleted file mode 100644
index a4db0df30f87d2f8af86331e2e71ed728d3e9b79..0000000000000000000000000000000000000000
--- a/.history/README_20250513112332.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112334.md b/.history/README_20250513112334.md
deleted file mode 100644
index 2994bafe4c4068da405a1b22746b22b520336fda..0000000000000000000000000000000000000000
--- a/.history/README_20250513112334.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes:
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112337.md b/.history/README_20250513112337.md
deleted file mode 100644
index ff38d277dc914602330478ec93c0f8b1b6a11df5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112337.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112341.md b/.history/README_20250513112341.md
deleted file mode 100644
index 74745f21d3d318f84822716e5bf1ff392d833366..0000000000000000000000000000000000000000
--- a/.history/README_20250513112341.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance:
-
-
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112344.md b/.history/README_20250513112344.md
deleted file mode 100644
index 8dbc9447f3d9a48f103f8a06a7a2a8b2b61e8200..0000000000000000000000000000000000000000
--- a/.history/README_20250513112344.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112345.md b/.history/README_20250513112345.md
deleted file mode 100644
index 06595391340212b35784baeae5f959a7b16eb6d1..0000000000000000000000000000000000000000
--- a/.history/README_20250513112345.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112353.md b/.history/README_20250513112353.md
deleted file mode 100644
index 590e9cbf8f6c045df999178a781b2358cd7c4919..0000000000000000000000000000000000000000
--- a/.history/README_20250513112353.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112357.md b/.history/README_20250513112357.md
deleted file mode 100644
index e8edf158d109ccd6d1c0a1589910c3dc85c4ab76..0000000000000000000000000000000000000000
--- a/.history/README_20250513112357.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112401.md b/.history/README_20250513112401.md
deleted file mode 100644
index e76251c126e57952ca0186fd5679b6d58decdfa5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112401.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112411.md b/.history/README_20250513112411.md
deleted file mode 100644
index f3c25ccd75f0c5054a5f28046a21240a55c4b85b..0000000000000000000000000000000000000000
--- a/.history/README_20250513112411.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112416.md b/.history/README_20250513112416.md
deleted file mode 100644
index a0bea453b31feb67066a05c3e195c182bda5b510..0000000000000000000000000000000000000000
--- a/.history/README_20250513112416.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112420.md b/.history/README_20250513112420.md
deleted file mode 100644
index a0bea453b31feb67066a05c3e195c182bda5b510..0000000000000000000000000000000000000000
--- a/.history/README_20250513112420.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from 
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112423.md b/.history/README_20250513112423.md
deleted file mode 100644
index d4d0c6ebdb447d568aa984fdf08652c8ed51eba0..0000000000000000000000000000000000000000
--- a/.history/README_20250513112423.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the vec
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112427.md b/.history/README_20250513112427.md
deleted file mode 100644
index c06bb6ad82b7e1d58ce8affde628bb557033135a..0000000000000000000000000000000000000000
--- a/.history/README_20250513112427.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the ve
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112429.md b/.history/README_20250513112429.md
deleted file mode 100644
index bb61b6fed3ff609181f20c8d41ee97638adf9980..0000000000000000000000000000000000000000
--- a/.history/README_20250513112429.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the vector
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112431.md b/.history/README_20250513112431.md
deleted file mode 100644
index f509e55bec6c8566e28b1bd548999cc58714594a..0000000000000000000000000000000000000000
--- a/.history/README_20250513112431.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://github.com/tensorchord/vectorchord) repository.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112436.md b/.history/README_20250513112436.md
deleted file mode 100644
index 53ed7b3cf5fe1b2bf842e3deec24977a298a6939..0000000000000000000000000000000000000000
--- a/.history/README_20250513112436.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://github.com/tensorchord/vectorchord) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112439.md b/.history/README_20250513112439.md
deleted file mode 100644
index d1162461bd22e0da35a4834602c79d10d4a84a42..0000000000000000000000000000000000000000
--- a/.history/README_20250513112439.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112440.md b/.history/README_20250513112440.md
deleted file mode 100644
index d1162461bd22e0da35a4834602c79d10d4a84a42..0000000000000000000000000000000000000000
--- a/.history/README_20250513112440.md
+++ /dev/null
@@ -1,164 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112452.md b/.history/README_20250513112452.md
deleted file mode 100644
index 54b1a5b6b0e7725cb9e10f77c810c4468d94f668..0000000000000000000000000000000000000000
--- a/.history/README_20250513112452.md
+++ /dev/null
@@ -1,172 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-id: A unique identifier for the image.
-url: The URL of the image.
-caption: A caption for the image.
-width: The width of the image in pixels.
-height: The height of the image in pixels.
-mime_type: The MIME type of the image file.
-hash: The MD5 hash of the image file.
-license: The URL of the image license.
-source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112502.md b/.history/README_20250513112502.md
deleted file mode 100644
index 85b0495da54a49dafe4063ed0b39a2746b11e84e..0000000000000000000000000000000000000000
--- a/.history/README_20250513112502.md
+++ /dev/null
@@ -1,172 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- id                   | bigint                      |           | not null |
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112512.md b/.history/README_20250513112512.md
deleted file mode 100644
index d51eedcb886edebaa0413f46885a3b54960f0db4..0000000000000000000000000000000000000000
--- a/.history/README_20250513112512.md
+++ /dev/null
@@ -1,171 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- url                  | character varying           |           | not null |
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112514.md b/.history/README_20250513112514.md
deleted file mode 100644
index 689e5a8693a09abe897bda8a7710a4409b474f98..0000000000000000000000000000000000000000
--- a/.history/README_20250513112514.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- caption              | character varying           |           | not null |
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112515.md b/.history/README_20250513112515.md
deleted file mode 100644
index 8ea6b0d5aa384255d73ead1c2db1677ee550e9ee..0000000000000000000000000000000000000000
--- a/.history/README_20250513112515.md
+++ /dev/null
@@ -1,169 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112522.md b/.history/README_20250513112522.md
deleted file mode 100644
index feb9081adcfc991d5830ba317e6db44e60373bad..0000000000000000000000000000000000000000
--- a/.history/README_20250513112522.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112523.md b/.history/README_20250513112523.md
deleted file mode 100644
index 680e6807b34e0bb70ddfdfb9207002482db94d64..0000000000000000000000000000000000000000
--- a/.history/README_20250513112523.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image .
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112527.md b/.history/README_20250513112527.md
deleted file mode 100644
index feb9081adcfc991d5830ba317e6db44e60373bad..0000000000000000000000000000000000000000
--- a/.history/README_20250513112527.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112531.md b/.history/README_20250513112531.md
deleted file mode 100644
index 69c81d88b858ff6f256f04cf42072f98474ce9e5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112531.md
+++ /dev/null
@@ -1,168 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112603.md b/.history/README_20250513112603.md
deleted file mode 100644
index 2b8128f9748c37cf89b996e4612ddf5e5d1dc59a..0000000000000000000000000000000000000000
--- a/.history/README_20250513112603.md
+++ /dev/null
@@ -1,165 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112617.md b/.history/README_20250513112617.md
deleted file mode 100644
index 69c81d88b858ff6f256f04cf42072f98474ce9e5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112617.md
+++ /dev/null
@@ -1,168 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112619.md b/.history/README_20250513112619.md
deleted file mode 100644
index feb9081adcfc991d5830ba317e6db44e60373bad..0000000000000000000000000000000000000000
--- a/.history/README_20250513112619.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
-----------------------+-----------------------------+-----------+----------+---------------
- caption_long         | character varying           |           | not null |
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112620.md b/.history/README_20250513112620.md
deleted file mode 100644
index 69c81d88b858ff6f256f04cf42072f98474ce9e5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112620.md
+++ /dev/null
@@ -1,168 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- width: The width of the image in pixels.
-- height: The height of the image in pixels.
-- mime_type: The MIME type of the image file.
-- hash: The MD5 hash of the image file.
-- license: The URL of the image license.
-- source : The source organization of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112719.md b/.history/README_20250513112719.md
deleted file mode 100644
index 2b8128f9748c37cf89b996e4612ddf5e5d1dc59a..0000000000000000000000000000000000000000
--- a/.history/README_20250513112719.md
+++ /dev/null
@@ -1,165 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112723.md b/.history/README_20250513112723.md
deleted file mode 100644
index df090ec78f59d0cb80602544d633ac73b44ce217..0000000000000000000000000000000000000000
--- a/.history/README_20250513112723.md
+++ /dev/null
@@ -1,165 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112725.md b/.history/README_20250513112725.md
deleted file mode 100644
index 26d96fab6adbbf7f54499b3ae4c4f955cb812c96..0000000000000000000000000000000000000000
--- a/.history/README_20250513112725.md
+++ /dev/null
@@ -1,171 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112727.md b/.history/README_20250513112727.md
deleted file mode 100644
index 9ce60a3b5edb8e80a4c513408af564ac9fc02b70..0000000000000000000000000000000000000000
--- a/.history/README_20250513112727.md
+++ /dev/null
@@ -1,170 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112728.md b/.history/README_20250513112728.md
deleted file mode 100644
index 36c780bfcb98428a04a7fe976bf47c6e4c04e1bd..0000000000000000000000000000000000000000
--- a/.history/README_20250513112728.md
+++ /dev/null
@@ -1,176 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112731.md b/.history/README_20250513112731.md
deleted file mode 100644
index ca5e5d0f01fe68cf7f44a45ebec30493458400c5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112731.md
+++ /dev/null
@@ -1,175 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112733.md b/.history/README_20250513112733.md
deleted file mode 100644
index 36c780bfcb98428a04a7fe976bf47c6e4c04e1bd..0000000000000000000000000000000000000000
--- a/.history/README_20250513112733.md
+++ /dev/null
@@ -1,176 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112734.md b/.history/README_20250513112734.md
deleted file mode 100644
index ca5e5d0f01fe68cf7f44a45ebec30493458400c5..0000000000000000000000000000000000000000
--- a/.history/README_20250513112734.md
+++ /dev/null
@@ -1,175 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-```
-\d is_pd12m;
-                                  Table "public.is_pd12m"
-        Column        |            Type             | Collation | Nullable |    Default
- origin_width         | bigint                      |           | not null |
- origin_height        | bigint                      |           | not null |
- origin_storage_id    | character varying(1024)     |           | not null |
- processed_storage_id | character varying(1024)     |           | not null |
- processed_width      | bigint                      |           | not null |
- processed_height     | bigint                      |           | not null |
- aspect_ratio         | double precision            |           | not null |
- exif                 | jsonb                       |           | not null |
- meta                 | jsonb                       |           | not null |
- created_at           | timestamp without time zone |           | not null |
- updated_at           | timestamp without time zone |           | not null |
- source               | jsonb                       |           | not null |
- vector               | halfvec(1152)               |           |          | NULL::halfvec
-Indexes:
-    "id_pd12m_pkey" PRIMARY KEY, btree (id)
-    "is_pd12m_aspect_ratio_index" btree (aspect_ratio)
-    "is_pd12m_caption_index" btree (caption) WHERE caption::text = ''::text
-    "is_pd12m_caption_long_index" btree (caption_long) WHERE caption_long::text = ''::text
-    "is_pd12m_created_at_index" btree (created_at)
-    "is_pd12m_exif_index" gin (exif)
-    "is_pd12m_meta_index" gin (meta)
-    "is_pd12m_origin_height_index" btree (origin_height)
-    "is_pd12m_origin_storage_id_index" btree (origin_storage_id)
-    "is_pd12m_origin_width_index" btree (origin_width)
-    "is_pd12m_processed_height_index" btree (processed_height)
-    "is_pd12m_processed_storage_id_index" btree (processed_storage_id)
-    "is_pd12m_processed_width_index" btree (processed_width)
-    "is_pd12m_source_index" gin (source)
-    "is_pd12m_updated_at_index" btree (updated_at)
-    "is_pd12m_url_index" UNIQUE, btree (url)
-    "is_pd12m_vector_index" vchordrq (vector halfvec_l2_ops) WITH (options='
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-')
-    "is_pd12m_vector_null_index" btree (vector) WHERE vector IS NULL
-```
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112743.md b/.history/README_20250513112743.md
deleted file mode 100644
index e52ae1dc9c97b59d6df82ba0564cdc99aca3bf63..0000000000000000000000000000000000000000
--- a/.history/README_20250513112743.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513112758.md b/.history/README_20250513112758.md
deleted file mode 100644
index e52ae1dc9c97b59d6df82ba0564cdc99aca3bf63..0000000000000000000000000000000000000000
--- a/.history/README_20250513112758.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513122556.md b/.history/README_20250513122556.md
deleted file mode 100644
index 369b641a23441288b13a149c37e9ad639adb2c61..0000000000000000000000000000000000000000
--- a/.history/README_20250513122556.md
+++ /dev/null
@@ -1,129 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513122557.md b/.history/README_20250513122557.md
deleted file mode 100644
index 327ac7f79165f54842eca67373fffcff0f79ace2..0000000000000000000000000000000000000000
--- a/.history/README_20250513122557.md
+++ /dev/null
@@ -1,128 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513122636.md b/.history/README_20250513122636.md
deleted file mode 100644
index e52ae1dc9c97b59d6df82ba0564cdc99aca3bf63..0000000000000000000000000000000000000000
--- a/.history/README_20250513122636.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513122638.md b/.history/README_20250513122638.md
deleted file mode 100644
index 369b641a23441288b13a149c37e9ad639adb2c61..0000000000000000000000000000000000000000
--- a/.history/README_20250513122638.md
+++ /dev/null
@@ -1,129 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
diff --git a/.history/README_20250513122642.md b/.history/README_20250513122642.md
deleted file mode 100644
index cad7faa432883bdcda73bc59d0d9dd9c3c10a64f..0000000000000000000000000000000000000000
--- a/.history/README_20250513122642.md
+++ /dev/null
@@ -1,134 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122646.md b/.history/README_20250513122646.md
deleted file mode 100644
index cf678ca37f20bfe12bc6bfd920e7cce1fd41e419..0000000000000000000000000000000000000000
--- a/.history/README_20250513122646.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122653.md b/.history/README_20250513122653.md
deleted file mode 100644
index 2d6babbfbdd60d712dfd820192d93c79fae3b5d6..0000000000000000000000000000000000000000
--- a/.history/README_20250513122653.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications. H
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122657.md b/.history/README_20250513122657.md
deleted file mode 100644
index 298fef5d1f30a978aa0f741d7aa4ab67a0545197..0000000000000000000000000000000000000000
--- a/.history/README_20250513122657.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications. Here i
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122700.md b/.history/README_20250513122700.md
deleted file mode 100644
index faeef90a8e2bd6fc26c6c184326af4de5f6cea94..0000000000000000000000000000000000000000
--- a/.history/README_20250513122700.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122702.md b/.history/README_20250513122702.md
deleted file mode 100644
index 1ebc7ae876f2e45fbe53aff93c6b33e75cc784c3..0000000000000000000000000000000000000000
--- a/.history/README_20250513122702.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122705.md b/.history/README_20250513122705.md
deleted file mode 100644
index 6939c5b827a03666ae875969eca948a485031b7a..0000000000000000000000000000000000000000
--- a/.history/README_20250513122705.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a 
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122707.md b/.history/README_20250513122707.md
deleted file mode 100644
index f840b59845d15c2dc5ac65ff7d74af5d2e2df25c..0000000000000000000000000000000000000000
--- a/.history/README_20250513122707.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo 
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122708.md b/.history/README_20250513122708.md
deleted file mode 100644
index 3f502bf9439e6d5d7fadfdf92716979a85b243c4..0000000000000000000000000000000000000000
--- a/.history/README_20250513122708.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset in PostgreSQL.
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122711.md b/.history/README_20250513122711.md
deleted file mode 100644
index d4b48dd07c652f00e69cb5a8fc94555e9874ed5b..0000000000000000000000000000000000000000
--- a/.history/README_20250513122711.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with 
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122713.md b/.history/README_20250513122713.md
deleted file mode 100644
index 8051429165d16798f9707bed2bb8ecb0a02edce7..0000000000000000000000000000000000000000
--- a/.history/README_20250513122713.md
+++ /dev/null
@@ -1,137 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with Chipmunk.
-
-
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122715.md b/.history/README_20250513122715.md
deleted file mode 100644
index 373ef13bbda04f0724f36050111fbd421188a6e3..0000000000000000000000000000000000000000
--- a/.history/README_20250513122715.md
+++ /dev/null
@@ -1,140 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with Chipmunk.
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122724.md b/.history/README_20250513122724.md
deleted file mode 100644
index 983d4c24204c5c6e20e1dda309980b01ae94a911..0000000000000000000000000000000000000000
--- a/.history/README_20250513122724.md
+++ /dev/null
@@ -1,140 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with Chipmunk.
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122726.md b/.history/README_20250513122726.md
deleted file mode 100644
index 007c9e22803419ddc1d516c048bfc10313775fbd..0000000000000000000000000000000000000000
--- a/.history/README_20250513122726.md
+++ /dev/null
@@ -1,140 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk)..
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122727.md b/.history/README_20250513122727.md
deleted file mode 100644
index 5e543a4ca963436b2a861202ca1180ceaabba28a..0000000000000000000000000000000000000000
--- a/.history/README_20250513122727.md
+++ /dev/null
@@ -1,140 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122732.md b/.history/README_20250513122732.md
deleted file mode 100644
index e99c515e0db3611c32c203748e62b31e3ac92566..0000000000000000000000000000000000000000
--- a/.history/README_20250513122732.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1. Create Table
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122747.md b/.history/README_20250513122747.md
deleted file mode 100644
index dfa7f8ea49fe77056f64aec1327163556a24dcee..0000000000000000000000000000000000000000
--- a/.history/README_20250513122747.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Use directly in PostgreSQL
-
-1.
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122749.md b/.history/README_20250513122749.md
deleted file mode 100644
index cbf9b9aa4480d0fcb4d472f7019a10c5e9b20d9e..0000000000000000000000000000000000000000
--- a/.history/README_20250513122749.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create Table Use directly in PostgreSQL
-
-1.
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122751.md b/.history/README_20250513122751.md
deleted file mode 100644
index 9f2c209b140d0e2329841ac5e34e60001d681414..0000000000000000000000000000000000000000
--- a/.history/README_20250513122751.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table Use directly in PostgreSQL
-
-1.
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122752.md b/.history/README_20250513122752.md
deleted file mode 100644
index 0fe7370de5af77b3124e1789ab893c3254133b17..0000000000000000000000000000000000000000
--- a/.history/README_20250513122752.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a  Use directly in PostgreSQL
-
-1.
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122753.md b/.history/README_20250513122753.md
deleted file mode 100644
index c92188a8b5bf60bb65564c97d829524fe087b0fa..0000000000000000000000000000000000000000
--- a/.history/README_20250513122753.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a PostgreSQL
-
-1.
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122756.md b/.history/README_20250513122756.md
deleted file mode 100644
index ac7937356373e7525d11f29b2f46dcf19c68e64a..0000000000000000000000000000000000000000
--- a/.history/README_20250513122756.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table inPostgreSQL
-
-1.
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122801.md b/.history/README_20250513122801.md
deleted file mode 100644
index 89b5b6e78b0c1a4b1b9a15c8bd651d41d902df3c..0000000000000000000000000000000000000000
--- a/.history/README_20250513122801.md
+++ /dev/null
@@ -1,135 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-1. Create a table in PostgreSQL:
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122803.md b/.history/README_20250513122803.md
deleted file mode 100644
index 8b34e067f05e31370456c0d27c9271373213af87..0000000000000000000000000000000000000000
--- a/.history/README_20250513122803.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-2. Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122811.md b/.history/README_20250513122811.md
deleted file mode 100644
index 55175c0384be7c2e4878d5fc42efae4d12d0d56d..0000000000000000000000000000000000000000
--- a/.history/README_20250513122811.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-##Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122813.md b/.history/README_20250513122813.md
deleted file mode 100644
index dfcba6def1b8cc8d77b9521af5b8c149204e1f44..0000000000000000000000000000000000000000
--- a/.history/README_20250513122813.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-2.1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122814.md b/.history/README_20250513122814.md
deleted file mode 100644
index 4d4d2f92c055a3c081e336e940ad99ef785146b1..0000000000000000000000000000000000000000
--- a/.history/README_20250513122814.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2.2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122815.md b/.history/README_20250513122815.md
deleted file mode 100644
index 3f50f1e8ea6c9d32ae761627734a93fa713cca34..0000000000000000000000000000000000000000
--- a/.history/README_20250513122815.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-3. Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122821.md b/.history/README_20250513122821.md
deleted file mode 100644
index c3dea13ce2d581a1accc6599ee3f8ea038ece35c..0000000000000000000000000000000000000000
--- a/.history/README_20250513122821.md
+++ /dev/null
@@ -1,133 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122825.md b/.history/README_20250513122825.md
deleted file mode 100644
index 932ec48ff48eb0fbb02e09b046c134f4ec2fca80..0000000000000000000000000000000000000000
--- a/.history/README_20250513122825.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Use with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122831.md b/.history/README_20250513122831.md
deleted file mode 100644
index 23a7aa32d7a5808babd43f1f59f491d1ff8c0886..0000000000000000000000000000000000000000
--- a/.history/README_20250513122831.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to load the dataset to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122845.md b/.history/README_20250513122845.md
deleted file mode 100644
index ec3db3c864e41427a52e6e111641dd9f3cbb6452..0000000000000000000000000000000000000000
--- a/.history/README_20250513122845.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the  to [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122847.md b/.history/README_20250513122847.md
deleted file mode 100644
index d721b3f160836338a71fa74da284dec6aa737f0e..0000000000000000000000000000000000000000
--- a/.history/README_20250513122847.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122848.md b/.history/README_20250513122848.md
deleted file mode 100644
index d721b3f160836338a71fa74da284dec6aa737f0e..0000000000000000000000000000000000000000
--- a/.history/README_20250513122848.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513122851.md b/.history/README_20250513122851.md
deleted file mode 100644
index d721b3f160836338a71fa74da284dec6aa737f0e..0000000000000000000000000000000000000000
--- a/.history/README_20250513122851.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# Dataset Card for `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513133625.md b/.history/README_20250513133625.md
deleted file mode 100644
index 50674c3a078b887387cc32b6249f542d90169efb..0000000000000000000000000000000000000000
--- a/.history/README_20250513133625.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513133627.md b/.history/README_20250513133627.md
deleted file mode 100644
index 50674c3a078b887387cc32b6249f542d90169efb..0000000000000000000000000000000000000000
--- a/.history/README_20250513133627.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513133633.md b/.history/README_20250513133633.md
deleted file mode 100644
index 50674c3a078b887387cc32b6249f542d90169efb..0000000000000000000000000000000000000000
--- a/.history/README_20250513133633.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513134037.md b/.history/README_20250513134037.md
deleted file mode 100644
index c4371dfaa05de6e8e30742cef72c4ce011443c8f..0000000000000000000000000000000000000000
--- a/.history/README_20250513134037.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for `L2` indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513134038.md b/.history/README_20250513134038.md
deleted file mode 100644
index c4371dfaa05de6e8e30742cef72c4ce011443c8f..0000000000000000000000000000000000000000
--- a/.history/README_20250513134038.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv file to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for `L2` indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513134717.md b/.history/README_20250513134717.md
deleted file mode 100644
index ae3f694730d26707566f08a823c085d44bbb88b1..0000000000000000000000000000000000000000
--- a/.history/README_20250513134717.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv files to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for `L2` indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513134718.md b/.history/README_20250513134718.md
deleted file mode 100644
index ae3f694730d26707566f08a823c085d44bbb88b1..0000000000000000000000000000000000000000
--- a/.history/README_20250513134718.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv files to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for `L2` indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
diff --git a/.history/README_20250513134719.md b/.history/README_20250513134719.md
deleted file mode 100644
index ae3f694730d26707566f08a823c085d44bbb88b1..0000000000000000000000000000000000000000
--- a/.history/README_20250513134719.md
+++ /dev/null
@@ -1,132 +0,0 @@
----
-license: apache-2.0
-task_categories:
-- feature-extraction
-language:
-- en
-size_categories:
-- 1M<n<10M
----
-
-# `PD12M`
-
-This is a curated PD12M dataset for use with the [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk) project.
-
-## Dataset Details
-
-### Dataset Description
-
-This dataset comprises a curated [Public Domain 12M](https://source.plus/pd12m) image collection, refined by filtering for active image links. EXIF data was extracted, and images underwent preprocessing and feature extraction using [SigLIP 2](https://huggingface.co/papers/2502.14786). All vector embeddings are normalized 16-bit half-precision vectors optimized for L2 indexing with [vectorchord](https://github.com/tensorchord/vectorchord).
-
-### Dataset Sources
-
-This dataset is derived and organized from [Spawning/PD12M](http://huggingface.co/datasets/Spawning/PD12M). The original license information for the image can be found in the corresponding entry of the original database.
-
-## Dataset Structure
-
-- id: A unique identifier for the image.
-- url: The URL of the image.
-- caption: A caption for the image.
-- caption_long: A long caption for the image.
-- origin_hash: The MD5 hash of the original image file.
-- origin_width: The width of the original image in pixels.
-- origin_height: The height of the original image in pixels.
-- origin_storage_id: The storage ID of the original image file.
-- processed_storage_id: The storage ID of the processed image file.
-- processed_width: The width of the processed image in pixels.
-- processed_height: The height of the processed image in pixels.
-- aspect_ratio: The aspect ratio of the image.
-- exif: The EXIF data of the image.
-- meta: The metadata of the image.
-- source: The source organization of the image.
-- vector: The vector embedding of the image.
-- created_at: The creation time of the image.
-- updated_at: The update time of the image.
-
-## Uses
-
-This dataset is available for a wide range of applications.
-
-Here is a demo of how to use the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).
-
-### Create a Table in PostgreSQL
-
-```sql
-CREATE TABLE IF NOT EXISTS is_pd12m (
-    id BIGSERIAL PRIMARY KEY,
-    url VARCHAR NOT NULL,
-    hash VARCHAR NOT NULL DEFAULT '',
-    caption VARCHAR NOT NULL DEFAULT '',
-    caption_long VARCHAR NOT NULL DEFAULT '',
-    origin_hash VARCHAR NOT NULL DEFAULT '',
-    origin_width BIGINT NOT NULL DEFAULT 0,
-    origin_height BIGINT NOT NULL DEFAULT 0,
-    origin_storage_id VARCHAR(1024) DEFAULT NULL,
-    processed_storage_id VARCHAR(1024) NOT NULL DEFAULT '',
-    processed_width BIGINT NOT NULL DEFAULT 0,
-    processed_height BIGINT NOT NULL DEFAULT 0,
-    aspect_ratio DOUBLE PRECISION NOT NULL DEFAULT 0,
-    exif JSONB NOT NULL DEFAULT '{}',
-    meta JSONB NOT NULL DEFAULT '{}',
-    source JSONB NOT NULL DEFAULT '[]',
-    vector halfvec(1152) DEFAULT NULL,
-    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-);
-```
-
-### Load csv files to database
-
-1. Load the dataset from local file system to a remote PostgreSQL server:
-
-```sql
-\copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-\copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-2. Load the dataset from the PostgreSQL server's file system:
-
-```sql
-copy is_pd12m FROM 'data/0000000.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000001.csv' CSV HEADER;
-copy is_pd12m FROM 'data/0000002.csv' CSV HEADER;
-...
-```
-
-### Create Indexes
-
-You need to create the following indexes for the best performance.
-
-The `vector` column is a halfvec(1152) column, which is a 16-bit half-precision vector optimized for `L2` indexing with [vectorchord](https://github.com/tensorchord/vectorchord). You can get more information about the vector index from the [vectorchord](https://docs.vectorchord.ai/vectorchord/usage/indexing.html) documentation.
-
-```sql
-CREATE UNIQUE INDEX IF NOT EXISTS is_pd12m_url_index ON is_pd12m (url);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_width_index ON is_pd12m (origin_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_height_index ON is_pd12m (origin_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_origin_storage_id_index ON is_pd12m (origin_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_storage_id_index ON is_pd12m (processed_storage_id);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_width_index ON is_pd12m (processed_width);
-CREATE INDEX IF NOT EXISTS is_pd12m_processed_height_index ON is_pd12m (processed_height);
-CREATE INDEX IF NOT EXISTS is_pd12m_aspect_ratio_index ON is_pd12m (aspect_ratio);
-CREATE INDEX IF NOT EXISTS is_pd12m_exif_index ON is_pd12m USING gin(exif);
-CREATE INDEX IF NOT EXISTS is_pd12m_meta_index ON is_pd12m USING gin(meta);
-CREATE INDEX IF NOT EXISTS is_pd12m_source_index ON is_pd12m USING gin(source);
-CREATE INDEX IF NOT EXISTS is_pd12m_created_at_index ON is_pd12m (created_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_updated_at_index ON is_pd12m (updated_at);
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_index ON is_pd12m USING vchordrq (vector halfvec_l2_ops)  WITH (options = $$
-    residual_quantization = true
-    [build.internal]
-    lists = [20000]
-    build_threads = 6
-    spherical_centroids = false
-$$);
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_index ON is_pd12m (caption) WHERE caption = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_caption_long_index ON is_pd12m (caption_long) WHERE caption_long = '';
-CREATE INDEX IF NOT EXISTS is_pd12m_vector_null_index ON is_pd12m (vector) WHERE vector IS NULL;
-```
-
-### Query with Chipmunk
-
-Click this link to learn how to query the dataset with [Chipmunk](https://github.com/Intelligent-Internet/Chipmunk).