| --- |
| license: mit |
| task_categories: |
| - feature-extraction |
| tags: |
| - vector-database |
| - semantic-search |
| - ivf-index |
| - embeddings |
| - information-retrieval |
| size_categories: |
| - 10M<n<100M |
| --- |
| |
| # Semantic Search Engine with Vectorized DB — Artifacts |
|
|
| This repository hosts the pre-computed on-disk index artifacts for the **20,000,000 vector database** (`OpenSubtitles_en_20M_emb_64.dat`), built for the **Advanced Database Systems** project (Cairo University, Faculty of Engineering). |
|
|
| --- |
|
|
| ## 📁 Repository Structure |
|
|
| ```text |
| semantic-search-artifacts/ |
| │ |
| ├── README.md # Repository documentation & usage guide |
| │ |
| ├── production/ |
| │ ├── m1_ivf_k4096/ # Module 1: IVF coarse index & cluster-sorted vectors |
| │ │ ├── centroids.f32 # (4096, 64) float32 L2-normalized coarse centroids |
| │ │ ├── offsets.i64 # (4097,) int64 inverted list boundary offsets |
| │ │ ├── ids.i32 # (20,000,000,) int32 original row IDs (cluster-sorted) |
| │ │ ├── vectors.f32 # (20,000,000, 64) float32 normalized vectors (cluster-sorted) |
| │ │ ├── labels.i16 # (20,000,000,) int16 cluster labels for original rows |
| │ │ ├── meta.json # Complete build parameters, stage timestamps & invariants |
| │ │ └── SHA256SUMS.txt # Cryptographic SHA-256 checksums |
| │ │ |
| │ └── m2_pq/ # Module 2: Product Quantization (in progress) |
| │ ├── pq_codes.* |
| │ ├── pq_codebooks.* |
| │ ├── pq_meta.json |
| │ └── SHA256SUMS.txt |
| │ |
| └── reports/ |
| ├── full_index_report.json # Complete validation & recall metrics for 20M index |
| └── dev_index_report.json # Validation report for 1M dev index |
| ``` |
|
|
| --- |
|
|
| ## 📊 Module 1 Production Index Details (`m1_ivf_k4096`) |
|
|
| - **Total Vectors ($N$):** 20,000,000 |
| - **Vector Dimension ($D$):** 64 (`float32`) |
| - **Clusters ($K$):** 4096 |
| - **Clustering Method:** `MiniBatchKMeans` on 2M L2-normalized vector sample, final centroids L2-normalized. |
| - **Empty Clusters:** **0** (min size = 680, max size = 22,911, mean = 4,882.8) |
| - **Coverage@64 (Upper Bound Recall):** **99.30%** (exceeds team target of $\ge 99.0\%$) |
| - **Build Time:** 304 seconds (~5 minutes) |
|
|
| --- |
|
|
| ## 🔒 Verification & Checksums |
|
|
| | File | Shape / Dtype | Size | SHA-256 Checksum | |
| | :--- | :--- | :--- | :--- | |
| | `centroids.f32` | `(4096, 64)` `float32` | 1,048,576 B (1.0 MB) | `deb0e2e88c764503ddbcf5eaf68d3807497228d300560477abd3fe642c635fff` | |
| | `offsets.i64` | `(4097,)` `int64` | 32,776 B (32 KB) | `7894cf57c10e8a4fa25aab62ccb6c4c4a8a08d4bc744091c5904fdefb1d237b4` | |
| | `ids.i32` | `(20000000,)` `int32` | 80,000,000 B (80 MB) | `6675a2ac22afbec3f65b467d5f3663d4618e541293ddba4ee10d3940c6035cab` | |
| | `labels.i16` | `(20000000,)` `int16` | 40,000,000 B (40 MB) | `d3294a967e330ad2ce757ff15abe4938274315b9fd6a9b43c08d9480f7c1d1b5` | |
| | `meta.json` | JSON metadata | 3,407 B (~3.4 KB) | `b86fe06ba30cf377994f271908958de6fd618ea6b818caa24102ecf648515991` | |
| | `vectors.f32` | `(20000000, 64)` `float32` | 5,120,000,000 B (5.12 GB) | `caaadbd8454542fbd7c329314134730ef79fd7b228130027b60f20b2a7476054` | |
|
|
| --- |
|
|
| ## 💻 Download & Integration Instructions |
|
|
| ### In Python using `huggingface_hub` |
| ```python |
| from huggingface_hub import hf_hub_download |
|
|
| # Example: Download centroids and offsets for Module 3 (Retrieval) |
| centroids_file = hf_hub_download( |
| repo_id="Abdelrahman610/Semantic-Search-Engine-with-Vectorized-DB", |
| filename="production/m1_ivf_k4096/centroids.f32", |
| repo_type="dataset", |
| ) |
| |
| offsets_file = hf_hub_download( |
| repo_id="Abdelrahman610/Semantic-Search-Engine-with-Vectorized-DB", |
| filename="production/m1_ivf_k4096/offsets.i64", |
| repo_type="dataset", |
| ) |
| ``` |
| |
| ### Download the entire index folder via CLI |
| ```bash |
| huggingface-cli download Abdelrahman610/Semantic-Search-Engine-with-Vectorized-DB --repo-type dataset --local-dir ./downloaded_artifacts |
| ``` |
|
|
