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Yiorgis Gozadinos 2a6d72171d
Make MCP failures errors on the wire 
FastMCP masks unexpected exceptions and logs the traceback server-side,
so paths and provider URLs never cross the transport. Expected failures
raise ToolError with a message: unknown document, unknown collection,
invalid filter, invalid base64, and agent failures naming only the
exception type. No tool returns an empty value or an error string on
failure any more.

A filter is validated on its own before the read that would use it, with
a filtered count on one of the selected databases: that is the query
engine rejecting the filter and nothing else, so its message (columns and
the statement) can be forwarded, while a ValueError raised later in the
read stays masked and no database outside the selection is opened.

Refs #599
2026-09-04 13:00:15 +03:00
..
haiku/rag Make MCP failures errors on the wire 2026-09-04 13:00:15 +03:00
LICENSE
pyproject.toml vb 2026-09-03 18:00:43 +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/