from fastapi import FastAPI, Request
from fastapi.responses import HTMLResponse, JSONResponse
from fastapi.staticfiles import StaticFiles
from transformers import pipeline

app = FastAPI()

# Uncomment and set up the model if needed
# model = pipeline('question-answering', model='bert-large-uncased-whole-word-masking-finetuned-squad', revision='main')

# Serve static files (e.g., CSS, JS, images)
app.mount("/static", StaticFiles(directory="static"), name="static")

@app.get("/", response_class=HTMLResponse)
async def home(request: Request):
    with open("templates/index.html") as f:
        html_content = f.read()
    return HTMLResponse(content=html_content)

@app.post("/predict", response_class=JSONResponse)
async def predict(request: Request):
    data = await request.json()
    user_input = data.get('message')
    # result = model(user_input)
    # response_text = result[0]['generated_text']
    return JSONResponse(content={'response': "Hello, Hugging Face!"})  # response_text