Skip to main content

Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling - Minimal dependencies

Project description

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/

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

haiku_rag_slim-0.39.0.tar.gz (113.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

haiku_rag_slim-0.39.0-py3-none-any.whl (160.2 kB view details)

Uploaded Python 3

File details

Details for the file haiku_rag_slim-0.39.0.tar.gz.

File metadata

  • Download URL: haiku_rag_slim-0.39.0.tar.gz
  • Upload date:
  • Size: 113.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for haiku_rag_slim-0.39.0.tar.gz
Algorithm Hash digest
SHA256 b807afbee32d7ea8cf5cacbe430bcebf2b4431280a2338df508c12ea3b3a3f54
MD5 6e0962fa24457b2bc87cfd09cc96ae59
BLAKE2b-256 69618332d907d4bc3d3733b0e9ce854cd9da0377bad485cf045ef56716614584

See more details on using hashes here.

File details

Details for the file haiku_rag_slim-0.39.0-py3-none-any.whl.

File metadata

File hashes

Hashes for haiku_rag_slim-0.39.0-py3-none-any.whl
Algorithm Hash digest
SHA256 3c3bb84143aaeafa2ff8b05cc958c47aabd652c84701f852dea66228e3f24228
MD5 916bf7916e1d18a4d0f0261d20abb999
BLAKE2b-256 dc437e1ce849446d54196d9d880d16be3cc237a660baef64740d76fc251941a1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page