main.py

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()

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