haiku.rag/haiku_rag_slim
Yiorgis Gozadinos feaca386d3
Document that file objects cannot be iterated
Monty 0.0.19 supports open() and with blocks, but a file object is still not
iterable. See pydantic/monty#490, which is still open. The instructions now
state the limitation in three places and give the alternative next to each
one: readlines() or read().split("\n").

Replace chr(10) with "\n" in the prose and in the example. Both work on
0.0.19, and chr(10) implies that the escape is broken.

Add a test that pins the limitation. The test fails when Monty gains
iteration support, which is the signal to relax the instructions.
2026-07-28 19:10:53 +03:00
..
haiku/rag Document that file objects cannot be iterated 2026-07-28 19:10:53 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
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

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/