init

Dockerfile

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+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt requirements.txt
+RUN pip install --upgrade pip && pip install -r requirements.txt
+
+COPY . .
+
+ENV FLASK_APP=app.py
+
+CMD ["flask", "run", "--host=0.0.0.0", "--port=7860"]

app.py

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+from flask import Flask, request, jsonify
+from flask_cors import CORS
+import joblib
+import numpy as np
+
+app = Flask(__name__)
+CORS(app)
+
+# Load model
+model = joblib.load("iris_decision_tree_model.pkl")
+
+@app.route('/')
+def home():
+    return "Model is ready!"
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    data = request.get_json()
+    input_data = np.array(data['input']).reshape(1, -1)
+    prediction = model.predict(input_data)
+    classes = ['Setosa', 'Versicolor', 'Virginica']
+    return jsonify({'prediction': classes[prediction[0]]})
+
+if __name__ == '__main__':
+    app.run(debug=True)

iris_decision_tree_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:39b5e9474ff8e310399feea6d24c547b95f8af258cbcbdfe86a91d659755dabd
+size 3329

requirements.txt

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+flask
+flask-cors
+numpy
+scikit-learn
+pandas
+joblib