from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch

app = FastAPI()

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Load the model - menší model
model = GPT2LMHeadModel.from_pretrained("distilgpt2")  # Menší verze GPT-2
tokenizer = GPT2Tokenizer.from_pretrained("distilgpt2")
tokenizer.pad_token = tokenizer.eos_token

class Question(BaseModel):
    text: str

@app.post("/ask")
def ask_ai(question: Question):
    try:
        prompt = f"Otázka: {question.text}\nOdpověď:"
        inputs = tokenizer.encode(prompt, return_tensors="pt")
        outputs = model.generate(
            inputs,
            max_length=inputs.shape[1] + 100,
            temperature=0.7,
            top_p=0.9,
            repetition_penalty=1.1,
            do_sample=True,
            pad_token_id=tokenizer.eos_token_id
        )
        answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
        # Remove the prompt from the answer
        answer = answer[len(prompt):].strip()
        return {"answer": answer}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Chyba API: {str(e)}")

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)