Update app.py

app.py

@@ -1,24 +1,24 @@
-from flask import Flask, request, jsonify
-import pickle
-import numpy as np
-import logging
-
-app = Flask(__name__)
-
-log = logging.getLogger('werkzeug')
-log.setLevel(logging.ERROR)
-
-model = pickle.load(open("lead_conversion_model.pkl","rb"))
-
-@app.route("/predict", methods=["POST"])
-def predict():
-
-    data = request.json["data"]
-    prediction = model.predict(np.array(data).reshape(1, -1))
-
-    return jsonify({
-        "prediction": int(prediction[0])
-    })
-
-if __name__ == "__main__":
-    app.run(debug=False)
+from flask import Flask, request, jsonify
+import pickle
+import numpy as np
+import logging
+
+app = Flask(__name__)
+
+log = logging.getLogger('werkzeug')
+log.setLevel(logging.ERROR)
+
+model = pickle.load(open("lead_conversion_model.pkl","rb"))
+
+@app.route("/predict", methods=["POST"])
+def predict():
+
+    data = request.json["data"]
+    prediction = model.predict(np.array(data).reshape(1, -1))
+
+    return jsonify({
+        "prediction": int(prediction[0])
+    })
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)