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   from fastapi import FastAPI
   from pydantic import BaseModel

   app = FastAPI()

   # Define request body
   class TextInput(BaseModel):
       text: str

   # Endpoint for sentiment analysis
   @app.post("/analyze/")
   def analyze_text(input: TextInput):
       result = sentiment_analysis(input.text)
       return {"text": input.text, "sentiment": result[0]}

Restart your server and test the endpoint. You can use a tool like Postman or CURL to send a POST request to http://127.0.0.1:8000/analyze/ with the following body:

Purpose: Implement caching headers to reduce the need for repeated server requests.

@app.after_request
def after_request(response):
    if response.content_type == 'text/html; charset=utf-8':
        response.set_data(minify(response.get_data(as_text=True)))
        response.headers['Cache-Control'] = 'public, max-age=3600'
    return response