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:

  • mxbai - MixedBread AI
  • 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,mxbai]
uv pip install haiku.rag-slim[docling,groq,logfire]

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/

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.97.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for ggozad from gravatar.com ggozad

Credits

Author: Yiorgis Gozadinos

License

MIT

Requires

Python >=3.12

Provides Extra

anthropic bedrock cohere docling google groq mistral mxbai tui vertexai voyageai zeroentropy

Tags

RAG lancedb mcp ml vector-database

Classifiers

Report project as malware

Metadata

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.97.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for ggozad from gravatar.com ggozad

Credits

Author: Yiorgis Gozadinos

License

MIT

Requires

Python >=3.12

Provides Extra

anthropic bedrock cohere docling google groq mistral mxbai tui vertexai voyageai zeroentropy

Tags

RAG lancedb mcp ml vector-database

Classifiers

Report project as malware

Release files for haiku.rag-slim 0.26.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for haiku.rag-slim 0.26.1
File Size Uploaded
haiku_rag_slim-0.26.1.tar.gz 94.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for haiku.rag-slim 0.26.1
File Interpreter ABI Platform
haiku_rag_slim-0.26.1-py3-none-any.whl 130.7 kB Python 3 none any Details

Total release size: 225.0 kB

Release files / haiku_rag_slim-0.26.1.tar.gz

Download URL haiku_rag_slim-0.26.1.tar.gz
Size 94.3 kB
Tags Source
SHA-256 checksum
How to use checksums 		f8725f0330f3327e11cc83d0722d2807f7850ffc2c0c69288874f17ce2c07007
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Release files / haiku_rag_slim-0.26.1-py3-none-any.whl

Download URL haiku_rag_slim-0.26.1-py3-none-any.whl
Size 130.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums 		743e1bc206a5e651bd0000cee558f087e223e6591690e1e447d8770ea08583ac
BLAKE2b-256 checksum
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What is trusted publishing? 		No
Uploaded via twine/6.2.0 CPython/3.13.11

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