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Yiorgis Gozadinos ae2755e88f
Enforce a declaration wherever there is something to declare 
Requiring an evidence outcome from the current question exempted the case enforcement
exists for: a follow-up about evidence already cited needs no new search, since that
evidence is still on the wire — in a capsule when a compactor is registered, in full
when not. The condition is now that the conversation has something to declare, either
an outcome in this question or evidence it has already cited, which is independent of
whether anything compacts. A conversation that has neither is still left alone.

Citing again cannot narrow a question at any epoch. Declarations merged only within one
epoch, so an empty second thought a request later replaced the refs with nothing and
reported a grounded question ungrounded. They merge while no evidence outcome has
followed the standing declaration, and only genuinely newer evidence starts one afresh.

Whether a question has already been asked to declare is read from the message history
rather than remembered on the run instance, which a resumption's `for_run` discarded —
the same question was asked twice. Reading the history also makes the right call when a
redirect was enqueued but the run ended before it reached the model: nothing is in the
history, so it is asked again. Violations are recorded once per question for the same
reason.
2026-08-13 13:39:42 +03:00
..
haiku/rag Enforce a declaration wherever there is something to declare 2026-08-13 13:39:42 +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/