app.py

from fastapi import FastAPI, Form
from fastapi.responses import FileResponse
from typing import Annotated
import torch 
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline 

app = FastAPI()

@app.get("/", response_class=FileResponse)
async def root():
    return "home.html"


@app.post("/hello/")
def say_hello(msg: Annotated[str, Form()]):
    print("model")
    tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b-it")
    model = AutoModelForCausalLM.from_pretrained(
        "google/gemma-2b-it",
        device_map="cpu",
        torch_dtype=torch.bfloat16
    )
    print("token & msg")
    input_ids = tokenizer(msg, return_tensors="pt").to("cpu")
    print("output")
    outputs = model.generate(**input_ids, max_length=500) 
    print("complete")
    return {"message": tokenizer.decode(outputs[0])}