from fastapi import FastAPI, UploadFile, File, HTTPException
from fastapi.responses import PlainTextResponse
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware 
from fastapi import Request
import os
from dotenv import load_dotenv
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
from huggingface_hub import login

app = FastAPI()


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


# Carrega o token do Hugging Face a partir do .env
load_dotenv()
hf_token = os.getenv("HF_TOKEN")

if not hf_token:
    raise ValueError("Token do Hugging Face não encontrado. Adicione HF_TOKEN no arquivo .env")

# Autentica (opcional se já tiver setado a env var)
login(token=hf_token)

model_name = "NullisTerminis/oncology_t5"

# Carrega o modelo usando o token atualizado
tokenizer = AutoTokenizer.from_pretrained(model_name, token=hf_token)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name, token=hf_token)

#Teste simples
#input_text = input(str("Texto:"))
#inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)

#output = model.generate(**inputs, max_length=128)
#decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)

#print("Saída gerada pelo modelo:")
#print(decoded_output)

#ROTAS /////////////////////////////////////////////////////////////////////

@app.get("/", response_class=PlainTextResponse)
async def root():
    return (
        "Link start!"
    )

@app.get("/mensagem", response_class=JSONResponse)
async def mensagem():
    return {"mensagem": "API funcionando perfeitamente no Hugging Face!"}