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Yiorgis Gozadinos a19f2c96b1
ARM ONLY, NEVER MERGE: sort the fused union by retrieval score 
Replaces the rank-interleaved fusion with a straight merge of the union
sorted by each candidate's raw retrieval score, ties still falling to
declaration order, cut at limit. This is the depth-quota candidate: within
one database rank order and raw-score order coincide, so the whole
difference from the tie-break fix is the cross-database interleaving.

This branch exists to be measured and discarded. The rank-dominance tests
in tests/multi_db/test_search.py pin the behaviour this deliberately
inverts, so the root suite FAILS here by design. If the arm wins, the
shipping implementation belongs to the session that owns client/search.py,
with its own tests.

Claude-Session: https://claude.ai/code/session_01WhudUtZm6qqiuv8Y1sbwSc
2026-08-31 19:10:16 +03:00
..
haiku/rag ARM ONLY, NEVER MERGE: sort the fused union by retrieval score 2026-08-31 19:10:16 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
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/