Datasetpublic

mouadja/aws-docs

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… See the full description on the dataset page: https://huggingface.co/datasets/mouadja/aws-docs.

sourceHugging Facemitupdated 4mo agoView on Hugging Face

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Dataset Card

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
pineconeid	string	Original Pinecone vector ID

Usage

python

from datasets import load_dataset

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

Or use with CAG-Lab:

bash

python scripts/setup_vectordb.py