haiku.rag/haiku_rag_slim
Yiorgis Gozadinos ab19f78507
Move source adapters out of the ingester package
haiku.rag.ingester.sources was never ingester-only: one-shot client
ingestion resolves adapters through it (create_document_from_source), and
convert() now fetches through HTTPSource, so the core client imported into
the ingester package to reach them.

Move the package to haiku.rag.sources and update every import. No shims:
haiku.rag.ingester.sources is gone.

The haiku.rag.sources plugin entry-point group is unchanged, so third-party
source packages need no edit — the group name now matches the module path it
always implied.

Source unit tests move to tests/sources/. test_source_plugins.py stays in
tests/ingester/: it drives a PeriodicPoller against the job repo, so it is
plugin wiring through ingester machinery rather than a source test.
2026-08-20 11:46:55 +03:00
..
haiku/rag Move source adapters out of the ingester package 2026-08-20 11:46:55 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
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

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/