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Yiorgis Gozadinos d9e4d1e57c
Bound a call that never reads and restore the iteration test 
The read deadline only gets control at a read, so code that computes without
reading escaped it. Give the pool a request_timeout above code_timeout. The
watchdog kills the worker, and execute() already replaces a dead session, so a
runaway call fails and the next call recovers. A read refusal keeps the
variables, so it has to win the race whenever code does read.

Restore test_open_file_objects_are_not_iterable. Replacing the neighbouring
write test by text range deleted it, which left the instructions carrying a
prohibition with nothing to signal when monty lifts it.

Reuse the VFS and the pool when a session is replaced, so recovery skips the
document scan. Mount metadata.json with a lambda rather than a factory. Cover
open() in write mode. Fold the crash entry into the pydantic-monty bullet,
because no release shipped the worker without it.
2026-07-28 19:11:19 +03:00
..
haiku/rag Bound a call that never reads and restore the iteration test 2026-07-28 19:11:19 +03:00
LICENSE
pyproject.toml Bump pydantic-monty to 0.0.19 2026-07-28 19:10:53 +03:00
README.md Remove the mxbai reranking provider 2026-07-14 11:09:55 +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

Document Processing:

  • docling - PDF, DOCX, HTML, and 40+ file formats

Embedding Providers:

  • voyageai - VoyageAI embeddings

Rerankers:

  • cross-encoder - Local reranking via sentence-transformers
  • cohere - Cohere
  • zeroentropy - Zero Entropy

Model Providers:

  • OpenAI/Ollama - included in core (OpenAI-compatible APIs)
  • anthropic - Anthropic Claude
  • groq - Groq
  • google - Google Gemini
  • mistral - Mistral AI
  • bedrock - AWS Bedrock
  • vertexai - Google Vertex AI
# 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/