Spaces:
Running
Running
| import os | |
| from fastapi import FastAPI, Request | |
| from fastapi.responses import StreamingResponse | |
| from openai import AsyncOpenAI | |
| import asyncio | |
| app = FastAPI() | |
| # Initialize OpenAI client once when the app starts | |
| client = AsyncOpenAI( | |
| api_key=os.getenv("OPENAI_API_KEY") # Get API key from environment variable | |
| ) | |
| async def generate_ai_response(prompt: str): | |
| try: | |
| # Create streaming chat completion | |
| stream = await client.chat.completions.create( | |
| model="gpt-3.5-turbo", # or "gpt-3.5-turbo" for faster/cheaper responses | |
| messages=[ | |
| {"role": "system", "content": "You are a helpful assistant."}, | |
| {"role": "user", "content": prompt} | |
| ], | |
| temperature=0.7, # Slightly less random than 1.0 for better coherence | |
| top_p=1.0, | |
| stream=True | |
| ) | |
| # Process the stream | |
| async for chunk in stream: | |
| if chunk.choices and len(chunk.choices) > 0: | |
| content = chunk.choices[0].delta.content or "" | |
| yield content | |
| except Exception as err: | |
| yield f"Error generating response: {str(err)}" | |
| async def generate_response(request: Request): | |
| try: | |
| data = await request.json() | |
| prompt = data.get("prompt", "") # Empty string if no prompt provided | |
| if not prompt: | |
| return {"error": "No prompt provided"}, 400 | |
| return StreamingResponse( | |
| generate_ai_response(prompt), | |
| media_type="text/event-stream" | |
| ) | |
| except Exception as e: | |
| return {"error": f"Invalid request: {str(e)}"}, 400 | |