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Yiorgis Gozadinos bb92ccf67e
Cover the configured set in the chat TUI 
Chat answers with the same capabilities `ask` does, so it federates as
naturally as `ask` and `analyze` — but it went through the one-database
guard and refused a configured set outright, which left no way to chat
across several databases.

The guard was the visible half. `run_chat` also defaulted `db_path` to the
single default path whenever it was None, so lifting the refusal alone
would still have opened one database. It now leaves the path unresolved
when `lancedb.databases` names the set, and the client resolves it.

Listing and counting documents fan out over the set, which is what the
document filter reads, and visual grounding resolves the database holding
the cited chunk through the citation's source: chunks, pages and bounding
boxes all come from that one database. A limit on a listing means that
many documents in total, not that many per database.

The info modal reports every database it covers, each under its
configured name and without its location, since names are the only
identity that leaves the configuration. `database_lines` is what one
database reports about itself, shared by both paths, and it reports a
failure as a line so one unreachable database does not cost the report on
the others.

`inspect` stays a one-database command. It browses one database's
documents and chunks, so a set has nothing to show it.
2026-08-24 10:03:46 +03:00
..
haiku/rag Cover the configured set in the chat TUI 2026-08-24 10:03:46 +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/