README.md

metadata

license: mit
task_categories:
  - text-retrieval
language:
  - en
size_categories:
  - 10K<n<100K

CAG-Lab AWS Docs Vectors

89,221 document chunk embeddings from AWS public documentation.

• Embedding model: OpenAI text-embedding-3-small (512 dimensions)
• Distance metric: Cosine
• Source: AWS public documentation chunks

Schema

Column	Type	Description
id	string	Deterministic UUID
embedding	list[float32]	512-dim vector
content	string	Document chunk text
filePath	string	Original file path
chunkIndex	string	Chunk position
_pinecone_id	string	Original Pinecone vector ID

Usage

from datasets import load_dataset

ds = load_dataset("mouadja/aws-docs")

Or use with CAG-Lab:

python scripts/setup_vectordb.py