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Yiorgis Gozadinos bae359e3bf
Align the MCP guidance with the analysis instructions and move to Monty 0.0.23 
The execute_code description gains the toc.json node shape, the patterns
the evals put into the analysis instructions (one list_documents call to
map a title to an id, files carry no source, toc before search for a known
document, doc_item_refs are items self_refs, chunk ids join files and are
not citations) and the sandbox's read-only, no-network, time-limit and
output facts, which the analysis instructions now state too. The skill
gains pictures as images, image search when offered, and citing chunk
metadata locators. docs/mcp.md lists the interpreter's limits under Code.

pydantic-monty>=0.0.23 brings collections, itertools, functools,
dataclasses, function decorators and str.format into the sandbox; every
layer names the same modules, and a test imports them. Monty now caps host
callbacks per checkout at 1000 by default; the sandbox raises it out of
reach, since the time budgets govern.
2026-09-07 12:02:33 +03:00
..
haiku/rag Align the MCP guidance with the analysis instructions and move to Monty 0.0.23 2026-09-07 12:02:33 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml Align the MCP guidance with the analysis instructions and move to Monty 0.0.23 2026-09-07 12:02:33 +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/