Resumption was inferred from the transcript, and no shape says it. A missing prompt is how UI adapters ask their first question as much as how pydantic-ai resumes one, so every AG-UI host failed on its first message. Reading the tail instead moved the error rather than fixing it: a settled structured answer ends with an output tool's return, indistinguishable from results delivered to a question still in progress, so following questions inherited the first one's identity. `CapabilityEvidenceRecord.in_progress` is now the authority. `begin_question` sets it, `after_run` clears it unless the run is only pausing for deferred work, and a run that raised never reaches `after_run`, which is what leaves an interrupted question claimable. The history is consulted only to catch a host that dropped the state of a question the model is unmistakably still owed. |
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| haiku/rag | ||
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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