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Update app.py
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app.py
CHANGED
@@ -1,18 +1,28 @@
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import os
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from fastapi import FastAPI, HTTPException
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from fastapi.responses import StreamingResponse
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from openai import AsyncOpenAI
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app = FastAPI()
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# Configuration for unofficial GitHub AI endpoint
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token = os.getenv("GITHUB_TOKEN")
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if not token:
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raise HTTPException(status_code=500, detail="GitHub token not configured")
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endpoint = "https://models.github.ai/inference"
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client = AsyncOpenAI(base_url=endpoint, api_key=token)
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@@ -37,12 +47,15 @@ async def generate_ai_response(prompt: str):
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raise HTTPException(status_code=500, detail="AI generation failed")
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@app.post("/generate")
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async def generate_response(
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if not prompt:
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raise HTTPException(status_code=400, detail="Prompt cannot be empty")
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return StreamingResponse(
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generate_ai_response(prompt),
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media_type="text/event-stream"
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)
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import os
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from fastapi import FastAPI, HTTPException, Query
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from fastapi.responses import StreamingResponse
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from openai import AsyncOpenAI
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app = FastAPI()
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# Define available models (you can expand this list)
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AVAILABLE_MODELS = {
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"openai/gpt-4.1-mini": "OpenAI GPT-4 Mini",
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"deepseek/DeepSeek-V3-0324": "DeepSeek V3 0324",
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# Add more models as needed
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}
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async def generate_ai_response(prompt: str, model: str):
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# Configuration for unofficial GitHub AI endpoint
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token = os.getenv("GITHUB_TOKEN")
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if not token:
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raise HTTPException(status_code=500, detail="GitHub token not configured")
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endpoint = "https://models.github.ai/inference"
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# Validate the model
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if model not in AVAILABLE_MODELS:
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raise HTTPException(status_code=400, detail=f"Model not available. Choose from: {', '.join(AVAILABLE_MODELS.keys())}")
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client = AsyncOpenAI(base_url=endpoint, api_key=token)
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raise HTTPException(status_code=500, detail="AI generation failed")
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@app.post("/generate")
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async def generate_response(
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prompt: str = Query(..., description="The prompt for the AI"),
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model: str = Query("openai/gpt-4.1-mini", description="The model to use for generation")
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):
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if not prompt:
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raise HTTPException(status_code=400, detail="Prompt cannot be empty")
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return StreamingResponse(
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generate_ai_response(prompt, model),
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media_type="text/event-stream"
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)
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