Create app.py

app.py

@@ -0,0 +1,49 @@
+from flask import Flask, request, jsonify
+import pickle
+import pandas as pd
+import traceback
+
+app = Flask(__name__)
+
+# Load pipeline (preprocessor + model)
+with open("best_model.pkl", "rb") as f:
+    model = pickle.load(f)
+
+
+@app.route("/", methods=["GET"])
+def health():
+    return jsonify({"status": "ExtraaLearn API running"}), 200
+
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    try:
+        data = request.get_json()
+
+        if "inputs" not in data:
+            return jsonify({"error": "Expected key 'inputs'"}), 400
+
+        df = pd.DataFrame(data["inputs"])
+
+        pred = int(model.predict(df)[0])
+        prob = float(model.predict_proba(df)[0][1])
+
+        if prob >= 0.75:
+            category = "High Conversion Potential"
+        elif prob >= 0.40:
+            category = "Medium Conversion Potential"
+        else:
+            category = "Low Conversion Potential"
+
+        return jsonify({
+            "prediction": pred,
+            "conversion_probability": round(prob, 2),
+            "lead_category": category
+        }), 200
+
+    except Exception as e:
+        return jsonify({
+            "error": "Prediction failed",
+            "details": str(e),
+            "trace": traceback.format_exc()
+        }), 500