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Yiorgis Gozadinos b374d5eb83
Replace ask_question and analyze with execute_code 
In Claude Code the client is the model, so the server no longer runs one.
execute_code runs a Python program per call in the analysis sandbox over
the selected documents and returns what it printed; the sandbox is created
and closed per call so Monty's cumulative budget and a frozen mount never
outlive a program. --no-agents goes with the two tools, and format_citations
in haiku.rag.utils goes with its only caller.

The sandbox exposes chunk metadata to code: chunk_meta on search results,
metadata on list_documents rows and in metadata.json, and chunks.jsonl per
document. A host-side failure inside a program, a document read or an
in-code search raising, reaches the program by exception type only and is
logged with its traceback. recovery_hint moves to haiku.rag.sandbox.

Closes #604.
2026-09-07 10:02:42 +03:00
..
haiku/rag Replace ask_question and analyze with execute_code 2026-09-07 10:02:42 +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/