Datasets:

PaczkiLives
/

daemon-wiki-faiss

license: mit
task_categories:
  - feature-extraction
  - text-retrieval
language:
  - en
pretty_name: Daemon Wiki FAISS Index
size_categories:
  - 10M<n<100M
tags:
  - faiss
  - wikipedia
  - embeddings
  - retrieval

Daemon Wiki FAISS Index

Pre-built FAISS IVFPQ index and metadata for the Daemon conversational RAG system.

File	Size	Description
`vector_index_ivf.faiss`	~2.2 GB	FAISS IVFPQ index (48 subquantizers x 8 bits, ~32x compression)
`metadata.parquet`	~12 GB	Row-group metadata (titles, text, timestamps) for zero-copy lookup

Coverage: ~41 million vectors from 6.5M+ English Wikipedia articles, embedded with sentence-transformers/all-MiniLM-L6-v2 (384-dim).

Usage

Download

pip install huggingface_hub

# Download both files into a local directory
huggingface-cli download PaczkiLives/daemon-wiki-faiss \
    --repo-type dataset \
    --local-dir ~/daemon-wiki-data/wiki_data

Point Daemon at the data

Set WIKI_DATA_ROOT to the parent directory of wiki_data/:

# If you downloaded to ~/daemon-wiki-data/wiki_data/
export WIKI_DATA_ROOT=~/daemon-wiki-data

# Then launch Daemon
python main.py

Or set individual paths directly:

export FAISS_INDEX_PATH=/path/to/wiki_data/vector_index_ivf.faiss
export FAISS_META_PATH=/path/to/wiki_data/metadata.parquet

Runtime requirements

RAM: ~2.6 GB (2.2 GB FAISS index + 0.4 GB embedding model). Metadata is read on-demand via zero-copy parquet row-group access — no DataFrame loaded into memory.
Disk: ~14.5 GB for both files.
CPU: Works on CPU. No GPU required.

How it was built

# From the Daemon repo:
python scripts/build_faiss_index.py

The build pipeline:

Downloads the latest English Wikipedia dump (~22 GB compressed)
Parses XML, extracts article text
Chunks articles at ~512 tokens with header-aware splitting
Embeds chunks with all-MiniLM-L6-v2 (384 dimensions)
Trains an IVF4096,PQ48 index on a sample, then adds all vectors
Writes metadata to a partitioned parquet file for zero-copy reads

License

MIT — same as the Daemon project.