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 (0.96.1)

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 inspector mistral mxbai 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 (0.96.1)

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 inspector mistral mxbai vertexai voyageai zeroentropy

Tags

RAG lancedb mcp ml vector-database

Classifiers

Report project as malware

Release files for haiku.rag-slim 0.23.1

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 0.23.1
File Size Uploaded
haiku_rag_slim-0.23.1.tar.gz 93.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for haiku.rag-slim 0.23.1
File Interpreter ABI Platform
haiku_rag_slim-0.23.1-py3-none-any.whl 129.0 kB Python 3 none any Details

Total release size: 222.9 kB

Release files / haiku_rag_slim-0.23.1.tar.gz

Download URL haiku_rag_slim-0.23.1.tar.gz
Size 93.9 kB
Tags Source
SHA-256 checksum
How to use checksums 		d134d0496f8134f1ae10fdd2e4a766a06a645eb1696fe47f15d06a589f88e051
BLAKE2b-256 checksum
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Release files / haiku_rag_slim-0.23.1-py3-none-any.whl

Download URL haiku_rag_slim-0.23.1-py3-none-any.whl
Size 129.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums 		0f91c0cbeaad8ba5d218c683f758f9a158849fa77a6ccf4ce31e1051422953ad
BLAKE2b-256 checksum
How to use checksums 		5a44e303ce4309fe4859f512560959a806b073c31d37f9fe3a03ff698c0c2256
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What is trusted publishing? 		No
Uploaded via twine/6.2.0 CPython/3.13.11

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