check_source_accessible narrowed its handler to ValueError, but Path.exists re-raises errno values outside its ignored set (EACCES, ENAMETOOLONG). Those were swallowed before and now escaped into the rebuild sweep the guard exists to protect. Catch OSError too. Restore the arity guard in _common_path_prefix: without it an empty list raises from min() and a single label yields a prefix covering the whole path. Two tests would have hung rather than failed on regression (the vacuum skip and the protected-wait cancellation); both are now bounded. The import vacuum test raced against the done-callback that discards the task, and now spies on the call instead, with a negative control. Replace assertions that could not fail: blank-query search against an empty corpus, a batch flush counted against an empty table, a picture description asserting its own input state, and an FS scheme check with nothing on disk to resolve. The get_model matrix asserted only the returned type across 26 cases and now pins the per-provider settings. The three batching tests now count flushes, which revealed embed-only writes through chunks_table.add rather than _flush_rebuild_batch. |
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| haiku/rag | ||
| LICENSE | ||
| pyproject.toml | ||
| 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-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