Datasets:

mouadja
/

aws-docs

Parquet error: Scan size limit exceeded: attempted to read 400043965 bytes, limit is 300000000 bytes Make sure that 1. the Parquet files contain a page index to enable random access without loading entire row groups2. otherwise use smaller row-group sizes when serializing the Parquet files

Error code:   TooBigContentError

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

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

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