A request can carry several of this capability's returns — a model can call search twice in one response — and the carrier was identified by message alone, so each of them received the whole capsule. It is selected by message and part now, so exactly one carries it however many share the request. The chat TUI passed its persisted state into the run, so tool synchronisation mutated it in place while the message history was promoted only on success. A cancelled or failed run therefore kept the evidence the tools had recorded and discarded the messages that justified it, and the next question derived its identity from the shorter history: behind the recorded epoch, refused as non-append-only, the conversation unusable until cleared. The run gets a copy, promoted with the messages or not at all. Five decorators had been left attached to a helper by an earlier extraction, which pytest does not collect, so the resume case they carried was silently untested. The wire test covers both resume shapes again, no prompt and deferred results. |
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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-transformerscohere- Coherezeroentropy- Zero Entropy
Model Providers:
- OpenAI/Ollama - included in core (OpenAI-compatible APIs)
anthropic- Anthropic Claudegroq- Groqgoogle- Google Geminimistral- Mistral AIbedrock- AWS Bedrockvertexai- 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/
- Installation - Provider setup
- Configuration - YAML configuration
- CLI - Command reference
- Python API - Complete API docs