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Yiorgis Gozadinos f4bfc12293
ARM ONLY, NEVER MERGE: z-scored branch fusion 
Hybrid without a reranker keeps each database's vector and FTS branches
apart and compares every candidate by per-branch z-score, summing both
branches for a chunk found in each. Databases are then compared by how
exceptional a hit is for them rather than by raw score, which is not
comparable across indexes.

Targets the measured ceiling on rank-and-score fusion: 73% of candidates at
n=4 and 84% at n=8 tie on both score and rank, so no key built from those
two can separate them and they fall to declaration order under every other
arm. Continuous keys should barely collide.

Implementation from the multi-fusion session; branch depth via
HAIKU_RAG_BRANCH_DEPTH, default 20.

Claude-Session: https://claude.ai/code/session_01WhudUtZm6qqiuv8Y1sbwSc
2026-08-31 19:10:22 +03:00
..
haiku/rag ARM ONLY, NEVER MERGE: z-scored branch fusion 2026-08-31 19:10:22 +03:00
LICENSE
pyproject.toml Update lancedb to 0.37.1 2026-08-31 18:54:48 +03:00
README.md Give the docs an architecture page and one extras list 2026-08-20 15:07:06 +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

docling, tui, voyageai, cohere, zeroentropy, cross-encoder, jina, s3, ingester, and one per model provider: anthropic, google, groq, mistral, bedrock, vertexai. Ollama and any OpenAI-compatible endpoint need no extra.

What each provides, and which ones the full haiku.rag package already includes: Installation.

# 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/