126 lines
3.0 KiB
Python
126 lines
3.0 KiB
Python
"""
|
|
TheSys Generative UI - FastAPI Backend Example
|
|
|
|
This example demonstrates how to set up a FastAPI backend that integrates
|
|
with TheSys C1 API for streaming generative UI responses.
|
|
|
|
Dependencies:
|
|
- fastapi
|
|
- uvicorn
|
|
- thesys-genui-sdk
|
|
- openai
|
|
- python-dotenv
|
|
"""
|
|
|
|
from fastapi import FastAPI
|
|
from fastapi.responses import StreamingResponse
|
|
from fastapi.middleware.cors import CORSMiddleware
|
|
from pydantic import BaseModel
|
|
from thesys_genui_sdk import with_c1_response, write_content
|
|
import openai
|
|
import os
|
|
from dotenv import load_dotenv
|
|
|
|
# Load environment variables
|
|
load_dotenv()
|
|
|
|
# Initialize FastAPI app
|
|
app = FastAPI(
|
|
title="TheSys C1 API Backend",
|
|
description="FastAPI backend for TheSys Generative UI",
|
|
version="1.0.0"
|
|
)
|
|
|
|
# Configure CORS
|
|
app.add_middleware(
|
|
CORSMiddleware,
|
|
allow_origins=["*"], # Configure for your frontend URL in production
|
|
allow_credentials=True,
|
|
allow_methods=["*"],
|
|
allow_headers=["*"],
|
|
)
|
|
|
|
# Initialize OpenAI client for TheSys C1 API
|
|
client = openai.OpenAI(
|
|
base_url="https://api.thesys.dev/v1/embed",
|
|
api_key=os.getenv("THESYS_API_KEY")
|
|
)
|
|
|
|
# Request model
|
|
class ChatRequest(BaseModel):
|
|
prompt: str
|
|
thread_id: str | None = None
|
|
response_id: str | None = None
|
|
|
|
|
|
@app.get("/")
|
|
async def root():
|
|
"""Health check endpoint"""
|
|
return {
|
|
"status": "ok",
|
|
"message": "TheSys C1 API Backend is running"
|
|
}
|
|
|
|
|
|
@app.post("/api/chat")
|
|
@with_c1_response # Automatically handles streaming headers
|
|
async def chat_endpoint(request: ChatRequest):
|
|
"""
|
|
Streaming chat endpoint that generates UI components.
|
|
|
|
Args:
|
|
request: ChatRequest with prompt and optional thread/response IDs
|
|
|
|
Returns:
|
|
StreamingResponse with C1-formatted UI chunks
|
|
"""
|
|
try:
|
|
# Create streaming completion request
|
|
stream = client.chat.completions.create(
|
|
model="c1/anthropic/claude-sonnet-4/v-20250930",
|
|
messages=[
|
|
{
|
|
"role": "system",
|
|
"content": "You are a helpful AI assistant that creates interactive user interfaces."
|
|
},
|
|
{
|
|
"role": "user",
|
|
"content": request.prompt
|
|
}
|
|
],
|
|
stream=True,
|
|
temperature=0.7,
|
|
max_tokens=4096
|
|
)
|
|
|
|
# Stream chunks to frontend
|
|
async def generate():
|
|
for chunk in stream:
|
|
content = chunk.choices[0].delta.content
|
|
if content:
|
|
yield write_content(content)
|
|
|
|
return StreamingResponse(
|
|
generate(),
|
|
media_type="text/event-stream"
|
|
)
|
|
|
|
except Exception as e:
|
|
return {
|
|
"error": str(e),
|
|
"message": "Failed to generate response"
|
|
}
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import uvicorn
|
|
|
|
# Run the server
|
|
uvicorn.run(
|
|
"fastapi-chat:app",
|
|
host="0.0.0.0",
|
|
port=8000,
|
|
reload=True,
|
|
log_level="info"
|
|
)
|