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Yiorgis Gozadinos 1d09b4e31b
Find a document in whichever database holds it 
`get_document_by_id`, `get_document_by_uri` and `get_chunk_by_id` read
through repositories a client covering a set does not have, so a lookup by
identifier raised AttributeError and `resolve_document` with it. An
identifier says nothing about which database holds it, so every database is
asked at once and the first that has it, in configured order, answers.

On the evaluation side, `--db` overrides the configured set as the CLI
documents, and population refuses a set rather than ingesting into a
database the run would not read. A case filter matching nothing raises
instead of reporting 0.0000 as though it were a score.
2026-08-24 10:03:47 +03:00
..
haiku/rag Find a document in whichever database holds it 2026-08-24 10:03:47 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml vb 2026-08-21 13:15:50 +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/