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Yiorgis Gozadinos 494294046f
Move to fastmcp 4 and MCP SDK 2 
fastmcp>=4.0.2,<5.0.0. Protocol types are snake_case (read_only_hint,
mime_type, input_schema, server_info); the camelCase names warn and go
in fastmcp 5, so the next major is an explicit upgrade. The client
defaults to the sessionless protocol, where initialize_result is None,
so the tests read client.instructions and client.server_info, which both
protocol modes populate. The server answers either mode.
2026-09-04 13:11:06 +03:00
..
haiku/rag Move to fastmcp 4 and MCP SDK 2 2026-09-04 13:11:06 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml Move to fastmcp 4 and MCP SDK 2 2026-09-04 13:11:06 +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/