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app.py

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+
+from fastapi import FastAPI, Depends, HTTPException
+from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
+from transformers import pipeline, AutoTokenizer
+import torch
+import jwt
+import os
+import re
+from dotenv import load_dotenv
+from typing import List, Dict, Optional
+from pydantic import BaseModel
+
+load_dotenv()
+SECRET_KEY = os.getenv('SECRET_KEY')
+security = HTTPBearer()
+
+app = FastAPI()
+
+model_name = 'Qwen/Qwen3-0.6B'
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+pipe = pipeline('text-generation', model=model_name, device=device, trust_remote_code=True)
+
+class GenerateRequest(BaseModel):
+    messages: List[Dict[str, str]]
+    enable_thinking: Optional[bool] = False
+
+def verify_token(credentials: HTTPAuthorizationCredentials = Depends(security)):
+    try:
+        payload = jwt.decode(credentials.credentials, SECRET_KEY, algorithms=['HS256'])
+        return payload
+    except Exception as e:
+        raise HTTPException(status_code=401, detail=str(e))
+
+@app.post('/generate')
+def generate(req: GenerateRequest, user=Depends(verify_token)):
+    try:
+        prompt = tokenizer.apply_chat_template(req.messages, tokenize=False, add_generation_prompt=True)
+        result = pipe(prompt, max_new_tokens=200)
+        full_text = result[0]['generated_text']
+
+        # Extract assistant response
+        response_split = full_text.split('<|im_start|>assistant')
+        content = response_split[-1] if len(response_split) > 1 else full_text
+
+        # Handle thinking block based on flag
+        if not req.enable_thinking:
+            content = re.sub(r'<think>.*?</think>', '', content, flags=re.DOTALL)
+
+        clean_response = content.replace('<|im_end|>', '').strip()
+
+        return {'generated_text': clean_response}
+    except Exception as e:
+        return {'error': str(e)}
+
+if __name__ == '__main__':
+    import uvicorn
+    uvicorn.run(app, host='0.0.0.0', port=8000)