ragit Documentation

ragit is a RAG (Retrieval-Augmented Generation) toolkit for Python. Build and optimize RAG pipelines with any embedding or LLM provider.

Getting Started

User Guide

API Reference

Community

Key Features

  • Provider Agnostic: Use any embedding API (OpenAI, Cohere, HuggingFace) or Ollama with nomic-embed-text

  • RAG Hyperparameter Optimization: Find optimal chunk size, overlap, and retrieval parameters

  • High-Level API: Simple RAGAssistant for document Q&A

  • Document Loading: Built-in utilities for loading and chunking documents

Quick Example

from ragit import RAGAssistant

def my_embed(text: str) -> list[float]:
    # Use any embedding API
    return your_embedding_api(text)

assistant = RAGAssistant("docs/", embed_fn=my_embed)
results = assistant.retrieve("How do I create a new user?")

Or with Ollama (nomic-embed-text):

from ragit import RAGAssistant
from ragit.providers import OllamaProvider

assistant = RAGAssistant("docs/", provider=OllamaProvider())
results = assistant.retrieve("How do I create a new user?")

Indices and tables