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RagUI

RagUI is a Python framework that transforms your RAG (Retrieval Augmented Generation) pipelines into production-ready web applications. It's framework-agnostic and works seamlessly with popular LLM frameworks like LangChain and LlamaIndex.

Features

  • Instant Web Interface: Get a polished chat UI for your RAG pipeline with zero frontend code
  • Production Ready: Built on FastAPI and async Python for high performance
  • Developer Focused: Focus on your RAG logic while we handle the infrastructure
  • Framework Agnostic: Works with LangChain, LlamaIndex, or your custom LLM implementation
  • Flexible Integration: Adapt any existing RAG pipeline with minimal changes

Coming Soon:

  • 🔒 Authentication & User Management
  • 📊 Admin Dashboard
  • 💾 Conversation History & Analytics
  • 💰 Subscription Management
  • 🔄 Feedback Collection & Fine-tuning
  • 📈 Usage Metrics & Monitoring

Quick Start

pip install ragui

Create a pipeline (main.py):

from ragui import RagUI
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate

ragui = RagUI()

# Define your LangChain components
prompt = ChatPromptTemplate.from_messages([
    ("user", "Context: {context}\nQuestion: {user_message}")
])
chain = prompt | ChatOpenAI() | StrOutputParser()

@ragui.pipeline("RAG Pipeline")
async def rag_pipeline(query, message_history, user_context):
    async for chunk in chain.astream({
        "context": "Your retrieved context here",
        "user_message": query
    }):
        yield chunk

Launch your application:

ragui main.py

Visit http://localhost:8000 to interact with your pipeline.

Why RagUI?

  • Save Development Time: Focus on your RAG logic instead of building UI/infrastructure
  • Production Ready: Built with production use-cases in mind
  • Future Proof: As we add features, your application automatically gets upgrades
  • Full Control: Customize and extend any aspect of the framework

Roadmap

  • Simple UI for text input/output
  • Feedback collection
  • Support files input
  • Support for multiple pipelines
  • Support for audio input
  • Messages persistence (database)
  • Conversation history
  • User authentication
  • Admin dashboard
  • Add to website support (little chat bubble on the corner)
  • Usage metrics
  • Subscription management

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