haiku.rag/haiku_rag_slim
Yiorgis Gozadinos 59e05d2c22
Merge remote-tracking branch 'origin/main' into feat/multi-db
0.78.0 released `api_key` and two authorization fixes out of the section
this branch was still adding to, so the automatic merge filed every
multi-database entry under it and dropped the `0.77.0` heading, which both
sides had de-duplicated. Everything from `0.78.0` down is main's record
verbatim; the multi-database entries stay under Unreleased.
2026-08-26 12:48:58 +03:00
..
haiku/rag Resolve a capability's databases once, into a scope 2026-08-26 12:20:21 +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

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/