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Yiorgis Gozadinos 71e4e4a40a
Resolve a capability's databases once, into a scope 
`resolve_db_path` manufactured the default path whenever `lancedb.databases`
was empty, and `covers_several_databases` read coverage back out of the
configuration, so a capability built without a client opened
`storage.data_dir/haiku.rag.lancedb` instead of what `lancedb.uri` placed.
The entry point resolves a `DatabaseScope` instead: instructions ask it what
it covers and `_ensure_rag` opens it through `HaikuRAG._covering`, so
coverage is decided once rather than encoded in a path and re-derived.
`Sandbox._covering` takes the scope the capability already resolved, beside
the public constructor that takes a path. The factory signatures are
unchanged.
2026-08-26 12:20:21 +03:00
..
haiku/rag Resolve a capability's databases once, into a scope 2026-08-26 12:20:21 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml vb 2026-08-21 13:15:50 +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/