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app.py

@@ -6,7 +6,7 @@ import pandas as pd  # For data manipulation
 from flask import Flask, request, jsonify  # For creating the Flask API
 
 # Initialize Flask app with a name
-superkart_api = Flask("ABMs Nozzle Selection By AFWC Passing Pressure") #define the name of the app
+superkart_api = Flask("ABMs-Nozzle-Selection") #define the name of the app
 
 # Load the trained prediction model
 model = joblib.load("nozzle_selection.joblib") #define the location of the serialized model
@@ -46,7 +46,7 @@ def predict_nozzle():
     prediction = model.predict(input_data).tolist()[0]
 
     # Return the prediction as a JSON response
-    return jsonify({'Nozzle': prediction})
+    return jsonify({'nozzle': prediction})
 
 # Define an endpoint for batch prediction (POST request)
 @nozzleselect_api.post('/v1/predictbatch')