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import os | |
from fastapi import FastAPI, HTTPException | |
from fastapi.responses import StreamingResponse | |
from openai import AsyncOpenAI | |
app = FastAPI() | |
async def generate_ai_response(prompt: str): | |
# Configuration for unofficial GitHub AI endpoint | |
token = os.getenv("GITHUB_TOKEN") | |
if not token: | |
raise HTTPException(status_code=500, detail="GitHub token not configured") | |
endpoint = "https://models.github.ai/inference" | |
model = "openai/gpt-4.1-mini" # Unofficial model name | |
client = AsyncOpenAI(base_url=endpoint, api_key=token) | |
try: | |
stream = await client.chat.completions.create( | |
messages=[ | |
{"role": "system", "content": "You are a helpful assistant."}, | |
{"role": "user", "content": prompt} | |
], | |
model=model, | |
temperature=1.0, | |
top_p=1.0, | |
stream=True | |
) | |
async for chunk in stream: | |
if chunk.choices and chunk.choices[0].delta.content: | |
yield chunk.choices[0].delta.content | |
except Exception as err: | |
yield f"Error: {str(err)}" | |
raise HTTPException(status_code=500, detail="AI generation failed") | |
async def generate_response(prompt: str): | |
if not prompt: | |
raise HTTPException(status_code=400, detail="Prompt cannot be empty") | |
return StreamingResponse( | |
generate_ai_response(prompt), | |
media_type="text/event-stream" | |
) | |
def get_app(): | |
return app |