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haiku.rag/haiku_rag_slim
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Chris McDonough 07c5a97929 Reuse httpx.AsyncClient across requests in HTTP and WebDAV sources 
HTTPSource and WebDAVSource previously created a new AsyncClient for
every head(), fetch(), and discover() call — no connection reuse, TLS
renegotiation on every request, and connection pool churn at scale.

Create the client once in __init__ and reuse it for the lifetime of
the source. Add aclose() to both sources, called by PollerManager on
shutdown to cleanly close the connection pool.
2026-06-01 07:00:15 -04:00
..
haiku/rag Reuse httpx.AsyncClient across requests in HTTP and WebDAV sources 2026-06-01 07:00:15 -04:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml vb 2026-05-29 11:47:12 +03:00
README.md Update project description 2025-11-29 11:18:53 +02:00

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:

  • mxbai - MixedBread AI
  • 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,mxbai]
uv pip install haiku.rag-slim[docling,groq,logfire]

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/