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Yiorgis Gozadinos bfd09f6880
Leave no database reading when a federated fan-out fails 
`asyncio.gather` propagates the first failure while its siblings run on, and the
caller unwinding from that closes the set through `async with` — so a sibling
still reading reads through a closed session. Seven fan-outs were affected:
lookup, search, image enrichment, multimodal picture loading, context expansion,
document listing and counting, and the sandbox's document load.

`gather_all` cancels and drains the rest, then re-raises the original exception.
A `TaskGroup` would drain them too but raise an `ExceptionGroup`, which every
caller and both CLIs' exception handlers would have to unwrap. The two
`return_exceptions=True` gathers in session opening and teardown already drain
their children and are left alone.
2026-08-28 12:02:07 +03:00
..
haiku/rag Leave no database reading when a federated fan-out fails 2026-08-28 12:02:07 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
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

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/