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Yiorgis Gozadinos 2000098e16
Say which commands cover a set, and what a shared id does 
Three groups, not two: `search`, `ask`, `analyze` and `chat` cover the set,
`settings`, `init-config` and `download-models` open no database, and every
other command works on one — or on a configured set of one, which is
unambiguous and keeps its name. A database named in `lancedb.databases` keeps
that name whether or not it is the only one covered; only `lancedb.uri` places
one without naming it.

Document ids repeat between copies of a database, where the sandbox refuses a
duplicate but the chat filter's `id IN (...)` matches the document in every
copy. `build_document_id_filter` claimed ids never widen a selection.

Document the facade: `covers_multiple`, `source_names`, `source`,
`reader_for`, `clients_for`, the lifetime of a borrowed client, and
`sources=None` against `sources=[]`.

Drop the vision callout from the README, which the features list already
covers.
2026-08-26 13:03:58 +03:00
..
haiku/rag Say which commands cover a set, and what a shared id does 2026-08-26 13:03:58 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
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/