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