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Dockerfile

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+FROM python:3.9-slim
+
+WORKDIR /app
+
+COPY . .
+
+RUN pip install -r requirements.txt
+
+CMD ["python", "app.py"]

app.py

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+from flask import Flask, request, jsonify
+import joblib
+import pandas as pd
+import numpy as np
+
+app = Flask(__name__)
+
+# Load the serialized model
+try:
+    model = joblib.load('sales_forecast_model_v1.joblib')
+except Exception as e:
+    print(f"Error loading model: {e}")
+
+@app.route('/v1/sales', methods=['POST'])
+def predict_single():
+    """Endpoint for single prediction based on JSON input."""
+    try:
+        data = request.get_json()
+        df = pd.DataFrame([data])
+        prediction = model.predict(df)[0]
+        return jsonify({'Predicted_Sales': round(float(prediction), 2)})
+    except Exception as e:
+        return jsonify({'error': str(e)}), 400
+
+@app.route('/v1/salesbatch', methods=['POST'])
+def predict_batch():
+    """Endpoint for batch predictions from a CSV file."""
+    try:
+        file = request.files['file']
+        df = pd.read_csv(file)
+        predictions = model.predict(df)
+        return jsonify({str(idx): round(float(pred), 2) for idx, pred in enumerate(predictions)})
+    except Exception as e:
+        return jsonify({'error': str(e)}), 400
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860, debug=False)

requirements.txt

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+flask==2.0.1
+werkzeug==2.0.3
+joblib==1.4.2
+pandas==2.2.2
+numpy==2.0.2
+scikit-learn==1.6.1
+xgboost==2.1.4

sales_forecast_model_v1.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:832ac40eeef81faaee2f17b3ef748397d8c1943afa83e31c537a8dbb589e9178
+size 406804