Upload 3 files

Dockerfile

@@ -1,11 +1,10 @@
-FROM python:3.9
+FROM python:3.11-slim
 
 WORKDIR /app
 
-COPY . .
-
-RUN pip install -r requirements.txt
+COPY requirements.txt requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
 
-EXPOSE 7860
+COPY . .
 
 CMD ["python", "app.py"]

app.py

@@ -1,19 +1,19 @@
-from flask import Flask, request, jsonify
-import pickle
-
-app = Flask(__name__)
-
-# Load model
-with open("xgb_superkart_model.pkl", "rb") as f:
-    model = pickle.load(f)
-
-@app.route("/")
-def index():
-    return "SuperKart API Running"
-
-@app.route("/predict", methods=["POST"])
-def predict():
-    data = request.json
-    features = [data['features']]
-    prediction = model.predict(features)
-    return jsonify({"prediction": prediction[0]})
+from flask import Flask, request, jsonify
+import pickle
+import numpy as np
+
+app = Flask(__name__)
+
+# Load model
+with open("xgb_superkart_model.pkl", "rb") as f:
+    model = pickle.load(f)
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    data = request.get_json(force=True)
+    features = np.array(data["features"]).reshape(1, -1)
+    prediction = model.predict(features)
+    return jsonify({"prediction": float(prediction[0])})
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)

requirements.txt

@@ -1,4 +1,4 @@
-flask
-scikit-learn
-numpy
-xgboost
+flask
+numpy
+scikit-learn
+xgboost