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Yiorgis Gozadinos 65f6d72cd5
Remove the single-document item accessors the batching replaced 
`resolve_refs`, `get_items_in_range`, `get_caption_picture_refs` and
`get_all_items_grouped` have no callers left: the grouped equivalents serve every
path that used them. `get_all_items_grouped` had none even before this branch.

Tests whose subject was a removed method go with it. Tests that only used one to
fetch a fixture now use the grouped call, so what they assert is unchanged.
2026-08-18 17:12:10 +03:00
..
haiku/rag Remove the single-document item accessors the batching replaced 2026-08-18 17:12:10 +03:00
LICENSE
pyproject.toml Fix the MCP registry entry and fill in package and docs metadata 2026-08-18 14:37:05 +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/