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)