Create app.py

app.py

@@ -0,0 +1,47 @@
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+import torch
+
+app = FastAPI()
+
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+model_name = "SkillForge45/CyberFuture-A1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16)
+
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
+
+class ChatRequest(BaseModel):
+    prompt: str
+    max_length: int = 100
+
+@app.post("/chat/")
+async def chat(request: ChatRequest):
+    try:
+        inputs = tokenizer(request.prompt, return_tensors="pt").to(device)
+        outputs = model.generate(
+            **inputs,
+            max_length=request.max_length,
+            temperature=0.7,
+            do_sample=True
+        )
+        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return {"response": response}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)