danvics/haiku.rag
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions
haiku.rag/haiku_rag_slim
History
Yiorgis Gozadinos b94e13083f
Hard-cap context expansion at max_context_chars 
A single oversized document_items row (e.g. a spreadsheet converted to one
table) expanded far past search.max_context_chars and could overflow the
model context window. _expand_outward only used the budget as a soft
accumulation threshold and expand_with_items never capped the joined result.

Add _clip_to_budget to clip each expanded result to max_context_chars,
returning a window centered on the matched chunk (via _evidence_anchors) so
the retrieved evidence survives the cut.
2026-06-27 09:46:36 +03:00
..
haiku/rag Hard-cap context expansion at max_context_chars 2026-06-27 09:46:36 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml vb 2026-06-26 17:13:03 +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/