use life cycle

app.py

@@ -1,32 +1,39 @@
 from fastapi import FastAPI
 from pydantic import BaseModel
 import spacy
+from contextlib import asynccontextmanager
 
 app = FastAPI()
 
 # Global variable to store the model
 nlp = None
 
-@app.on_event("startup")
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    await load_model()
+    yield
+    await cleanup()
+
+
 async def load_model():
     """
     Event to load the NLP model into memory on application startup.
     """
     global nlp
-    nlp = spacy.load("en_core_web_sm")  # Replace with your model and loading logic
+    nlp = spacy.load("en_core_web_sm")
     print("NLP model loaded successfully.")
 
-@app.on_event("shutdown")
+
 async def cleanup():
     """
     Event to clean up resources on application shutdown (if needed).
     """
     global nlp
-    nlp = None  # Free memory (if necessary)
+    nlp = None
     print("NLP model unloaded.")
 
 
-
 class NERRequest(BaseModel):
     chunks: list[str]