from fastapi import FastAPI
# from core.init_nlp import initialize_nlp
from contextlib import asynccontextmanager
import logging
from api.endpoints import location
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
from models.fastapi_globals import g ,GlobalsMiddleware
@asynccontextmanager
async def lifespan(app: FastAPI):
    # initialize_nlp()
    print("Initializing NER model and tokenizer")
    logging.info("Initializing NER model and tokenizer")
    
    app.tokenizer = AutoTokenizer.from_pretrained("ml6team/bert-base-uncased-city-country-ner")
    app.model = AutoModelForTokenClassification.from_pretrained("ml6team/bert-base-uncased-city-country-ner")
    app.nlp = pipeline('ner', model=app.model, tokenizer=app.tokenizer, aggregation_strategy="simple")
    g.set_default("ner_model", ner_model)    
    yield
    del sentiment_model
    g.cleanup()

app = FastAPI(lifespan=lifespan)

app.include_router(location.router, prefix="/location/api/v1")