# import gradio as gr

# gr.load("models/openai/whisper-large-v3").launch()

from typing import Union
from pydantic import BaseModel
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse

from transformers import pipeline

app = FastAPI(docs_url="/api/docs")

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

pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")


@app.get("/infer_t5")
def t5(input):
    output = pipe_flan(input)
    return {"output": output[0]["generated_text"]}


app.mount("/", StaticFiles(directory="static", html=True), name="static")


@app.get("/")
def index() -> FileResponse:
    return FileResponse(path="/app/static/index.html", media_type="text/html")