| Tool | License | Stars | Description |
|---|---|---|---|
| Gradio | Apache-2.0 | 25k+ | ML demo interface builder |
| Streamlit | Apache-2.0 | 25k+ | Data app framework |
| LangServe | MIT | Part of LangChain | LangChain deployment |
| FastAPI + React | Custom | N/A | Custom solution |
| NiceGUI | MIT | 5k+ | Python UI framework |
| Panel | BSD | 4k+ | Data app framework |
| Feature | Chainlit | Gradio | Streamlit | LangServe |
|---|---|---|---|---|
| Chat UI | ✅ Built-in | ⚠️ Custom | ⚠️ Custom | ✅ |
| Streaming | ✅ | ✅ | ⚠️ Limited | ✅ |
| Authentication | ✅ | ⚠️ Custom | ⚠️ Custom | ✅ |
| Persistent Sessions | ✅ | ❌ | ⚠️ Custom | ✅ |
| LangChain Integration | ✅ | ✅ | ⚠️ Custom | ✅ |
| LlamaIndex Integration | ✅ | ⚠️ Custom | ⚠️ Custom | ✅ |
| Community-Maintained | ⚠️ Yes | ✅ Active | ✅ Active | ✅ Active |
| Enterprise Support | ❌ | ✅ (Hugging Face) | ✅ (Snowflake) | ✅ (LangChain) |
Benefits:
Considerations:
Benefits:
Considerations:
Benefits:
Considerations:
| Requirement | Best Choice |
|---|---|
| Chat-focused UI | Chainlit |
| ML Model Demos | Gradio |
| Data Dashboards | Streamlit |
| LangChain APIs | LangServe |
| Custom UI/UX | FastAPI + React |
| General Python UI | NiceGUI |
| Enterprise Support | Gradio / Streamlit / LangServe |
| Rapid Prototyping | Chainlit / Streamlit |
| Community-Maintained | Chainlit |
Some projects use multiple frameworks together:
# Chainlit for chat + LangServe for API
from chainlit import on_message
from langserve import add_routes
# Chainlit for user-facing chat
@cl.on_message
async def on_message(message: cl.Message):
# Use LangChain chain
response = await chain.ainvoke(message.content)
await cl.Message(content=response).send()
# LangServe for API access
add_routes(app, chain, path="/api")
# Gradio for demos + Chainlit for chat
import gradio as gr
import chainlit as cl
# Gradio for model demo
gr.Interface(fn=predict, inputs="text", outputs="text").launch()
# Chainlit for conversational interface
@cl.on_message
async def on_message(message: cl.Message):
response = await chat_chain.ainvoke(message.content)
await cl.Message(content=response).send()