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Yiorgis Gozadinos 34180a0fd1
One reference and one placement for a database 
DatabaseRef is a name and a location. The configuration places databases
through lancedb.databases alone; with none configured the default is the
entry haiku.rag under storage.data_dir, selectable like any other.
lancedb.uri is removed, and a config carrying it fails to load with the
replacement spelled out. A path passed from Python is valid where the
configuration places nothing and raises AmbiguousDatabaseError beside
lancedb.databases; haiku-rag --db and haiku-ingester --db construct the
scope directly, so a human's override keeps working. Every database
answers to a name, and a database given as a path keeps its own errors.
2026-09-03 15:12:08 +03:00
..
haiku/rag One reference and one placement for a database 2026-09-03 15:12:08 +03:00
LICENSE
pyproject.toml vb 2026-09-01 16:07:03 +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/