Spaces:
Sleeping
Sleeping
File size: 2,066 Bytes
f7c0abb a86df42 f7c0abb 6e02eb7 a86df42 6e02eb7 a86df42 f7c0abb a86df42 f7c0abb a86df42 f7c0abb a86df42 f7c0abb 6e02eb7 f7c0abb a86df42 f7c0abb 6e02eb7 f7c0abb 6e02eb7 f7c0abb 6e02eb7 a86df42 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
import os
from fastapi import FastAPI, HTTPException
from fastapi.responses import StreamingResponse
import openai # Use OpenAI's official API library
from pydantic import BaseModel
# Initialize FastAPI app
app = FastAPI()
# Define request body model for the prompt
class PromptRequest(BaseModel):
prompt: str
# Initialize OpenAI client
token = os.getenv("GITHUB_TOKEN")
if not token:
raise ValueError("GITHUB_TOKEN environment variable not set")
# Initialize OpenAI API client with API key
openai.api_key = token # Set the OpenAI API key
# Async generator to stream chunks from OpenAI's API
async def stream_response(prompt: str):
try:
# Create streaming chat completion with OpenAI API
response = openai.ChatCompletion.create(
model="gpt-4", # Replace with the model you're using (e.g., gpt-3.5-turbo or gpt-4)
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}
],
temperature=1.0,
top_p=1.0,
stream=True # Enable streaming
)
# Yield each chunk of the response as it arrives
for chunk in response:
content = chunk.get("choices", [{}])[0].get("delta", {}).get("content", "")
if content:
yield content # Yield the generated content
except Exception as err:
yield f"Error: {str(err)}"
# Endpoint to handle the prompt and stream response
@app.post("/generate")
async def generate_response(request: PromptRequest):
try:
# Return a StreamingResponse with the async generator
return StreamingResponse(
stream_response(request.prompt),
media_type="text/event-stream" # Use text/event-stream for streaming
)
except Exception as err:
raise HTTPException(status_code=500, detail=f"Server error: {str(err)}")
# Health check endpoint for Hugging Face Spaces
@app.get("/")
async def health_check():
return {"status": "healthy"}
|