Nithiyanandham15/claude_code

1import os2import subprocess3import json4import logging5from fastapi import FastAPI, HTTPException, Security, Depends6from fastapi.middleware.cors import CORSMiddleware7from fastapi.security import APIKeyHeader8from pydantic import BaseModel9import ollama10 11# Configure logging12logging.basicConfig(level=logging.INFO)13logger = logging.getLogger(__name__)14 15app = FastAPI()16 17# Enable CORS for frontend access18app.add_middleware(19    CORSMiddleware,20    allow_origins=["*"],  # Allow all origins (Hugging Face Spaces, local dev)21    allow_credentials=True,22    allow_methods=["*"],23    allow_headers=["*"],24)25 26# Security configuration27API_KEY_NAME = "Authorization"28# Default to a placeholder if not set, but warn29# Ensure you set ACCESS_TOKEN in your Space settings (Settings -> Variables and secrets)30ACCESS_TOKEN = os.environ.get("ACCESS_TOKEN")31api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)32 33# Model configuration34MODEL_NAME = os.environ.get("OLLAMA_MODEL", "qwen2.5-coder:1.5b")35 36async def verify_token(api_key: str = Security(api_key_header)):37    if not ACCESS_TOKEN:38        # If no token set, allow access (warning: insecure)39        logger.warning("ACCESS_TOKEN not set, allowing unauthenticated access")40        return "unauthenticated"41        42    if not api_key:43        raise HTTPException(status_code=403, detail="Authorization header missing")44    45    token = api_key.replace("Bearer ", "").strip()46    if token != ACCESS_TOKEN:47        raise HTTPException(status_code=403, detail="Invalid token")48    return token49 50class PromptRequest(BaseModel):51    prompt: str52    model: str = MODEL_NAME53 54@app.get("/")55def read_root():56    return {"message": f"Ollama Coding Agent API is running with model {MODEL_NAME}. Use POST /run to execute tasks."}57 58@app.post("/run")59async def run_agent(request: PromptRequest, token: str = Depends(verify_token)):60    prompt = request.prompt61    model = request.model62    63    try:64        # Check if Ollama is ready65        try:66            ollama.list()67        except Exception as e:68            return {"status": "error", "message": "Ollama server not ready", "details": str(e)}69 70        # Simple "Agent" Logic:71        # 1. Ask the model to generate a response (code or explanation)72        # 2. If the user asked to execute something, we could add tool calling here.73        #    For now, we will return the raw model output as the "agent's response".74        75        # System prompt to give it a persona76        system_prompt = """You are an expert coding assistant running inside a secure environment.77        Your goal is to help the user with programming tasks.78        Provide clear, correct, and concise code solutions.79        """80        81        response = ollama.chat(model=model, messages=[82            {'role': 'system', 'content': system_prompt},83            {'role': 'user', 'content': prompt},84        ])85        86        return {87            "status": "success",88            "model": model,89            "response": response['message']['content'],90            "full_response": response91        }92        93    except Exception as e:94        logger.error(f"Error processing request: {e}")95        raise HTTPException(status_code=500, detail=str(e))96 97if __name__ == "__main__":98    import uvicorn99    uvicorn.run(app, host="0.0.0.0", port=7860)100