Upload app.py

app.py

@@ -0,0 +1,30 @@
+from flask import Flask, request, jsonify
+import joblib, pandas as pd, numpy as np
+
+# Load the model bundle (adjust the filename if needed)
+BUNDLE_FILENAME = "best_model_random_forest.joblib"
+bundle = joblib.load(BUNDLE_FILENAME)
+model = bundle["model"]
+feature_cols = bundle["feature_cols"]
+
+app = Flask(__name__)
+
+@app.route("/")
+def home():
+    return "SuperKart Forecast API is running."
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    data = request.get_json(force=True)
+    if isinstance(data, dict):
+        df = pd.DataFrame([data])
+    else:
+        df = pd.DataFrame(data)
+    
+    # Align columns with training
+    X = df.reindex(columns=feature_cols, fill_value=np.nan)
+    preds = model.predict(X)
+    return jsonify({"predictions": [float(p) for p in preds]})
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5000)