from fastapi import FastAPI
from pydantic import BaseModel
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

app = FastAPI()

class PromptRequest(BaseModel):
    prompt: str

# Load small LLaMA 3.2B model (or any other compatible)
MODEL_NAME = "TheBloke/Llama-3-OpenOrca-2.2B-GGUF"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)

@app.get("/")
def root():
    return {"message": "LLaMA 3.2B API for QuizForge is live!"}

@app.post("/generate")
def generate_text(data: PromptRequest):
    inputs = tokenizer(data.prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_new_tokens=1024)
    output_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return {"response": output_text}