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Yiorgis Gozadinos eb9934a6e5
Notice the endings a structured answer arrives in 
An output tool call is a `ToolCallPart` like any other, and treating every tool call as
intermediate meant a model could search, skip citing, emit its structured answer and
finish with neither a redirect nor a record. A response ends the question when it
carries no tool calls, or when one of its calls names an output tool.

Some endings are not visible from a single response — a host running
`end_strategy="early"` can finish on text beside a function call — so `after_run` is
the backstop: it cannot ask the model for anything by then, but it records a question
that reached the end of its run undeclared. That also covers a question that was asked
once, ignored, and finished anyway, which previously returned early on the redirect
marker and went unrecorded.

The capability documentation and the changelog said a question that gathered no
evidence is left alone. That describes neither the code nor the intent: enforcement
applies wherever there is something to declare, which includes a follow-up that reuses
evidence cited earlier without searching again.
2026-08-13 13:39:43 +03:00
..
haiku/rag Notice the endings a structured answer arrives in 2026-08-13 13:39:43 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml vb 2026-08-06 13:55:57 +03:00
README.md Remove the mxbai reranking provider 2026-07-14 11:09:55 +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

Document Processing:

  • docling - PDF, DOCX, HTML, and 40+ file formats

Embedding Providers:

  • voyageai - VoyageAI embeddings

Rerankers:

  • cross-encoder - Local reranking via sentence-transformers
  • 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,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/