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Yiorgis Gozadinos 9ed66e3a06
Search one database the ordinary way, however it was selected 
`sources=["alpha"]` on a client covering a set went through fusion, which
scores position: a result the database ranked at 0.6549 was reported as
1/(60+rank). Embedding also moved ahead of the repository, so a filter matching
no document embedded the query anyway.

A selection of one now runs the single-database search. Fusion reconciles
rankings from separate indexes, and one ranking has nothing to reconcile.

A reranker that returns chunks it built rather than the ones it was given loses
which database each came from, since ownership is by identity. That is named
now instead of surfacing as a KeyError, and stated on `RerankerBase._rerank`.
2026-08-27 14:41:10 +03:00
..
haiku/rag Search one database the ordinary way, however it was selected 2026-08-27 14:41:10 +03:00
LICENSE
pyproject.toml vb 2026-08-24 16:06:03 +03:00
README.md Give the docs an architecture page and one extras list 2026-08-20 15:07:06 +03:00

README.md

haiku.rag-slim

Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling - Core package with minimal dependencies.

haiku.rag-slim is the core package for users who want to install only the dependencies they need. Document processing (docling), and reranker support are all optional extras.

For most users, we recommend installing haiku.rag instead, which includes all features out of the box.

Installation

Python 3.12 or newer required

Minimal Installation

uv pip install haiku.rag-slim

Core functionality with OpenAI/Ollama support, MCP server, and Logfire observability. Document processing (docling) is optional.

With Document Processing

uv pip install haiku.rag-slim[docling]

Adds support for 40+ file formats including PDF, DOCX, HTML, and more.

Available Extras

docling, tui, voyageai, cohere, zeroentropy, cross-encoder, jina, s3, ingester, and one per model provider: anthropic, google, groq, mistral, bedrock, vertexai. Ollama and any OpenAI-compatible endpoint need no extra.

What each provides, and which ones the full haiku.rag package already includes: Installation.

# Common combinations
uv pip install 'haiku.rag-slim[docling,anthropic,cross-encoder]'
uv pip install 'haiku.rag-slim[docling,groq]'

Usage

See the main haiku.rag repository for:

  • Quick start guide
  • CLI examples
  • Python API usage
  • MCP server setup

Documentation

Full documentation: https://ggozad.github.io/haiku.rag/