directory with necessary files to access model over the intrnet with HF

UI_app/app.py

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+from flask import Flask, request, jsonify
+import pickle
+import numpy as np
+
+app = Flask(__name__)
+
+# Load the model from the pickle file
+with open('model.pkl', 'rb') as f:
+    model = pickle.load(f)
+
+@app.route('/')
+def home():
+    return "Welcome to the Penguin Classifier API!"
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    # Parse input features from the request body (assumed to be JSON)
+    data = request.get_json()
+    features = np.array(data['features']).reshape(1, -1)
+    
+    # Make prediction
+    prediction = model.predict(features).tolist()
+
+    return jsonify({'prediction': prediction})
+
+if __name__ == "__main__":
+    app.run(debug=True)

UI_app/requirements.txt

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+mlflow==2.16.2
+cloudpickle==3.0.0
+ipykernel==6.29.5
+loguru==0.7.2
+numpy==2.1.1
+pandas==2.2.3
+python-dotenv==1.0.1
+scikit-learn==1.5.2
+scipy==1.14.1
+gradio==3.1