diff --git a/Pipfile b/Pipfile
new file mode 100644
index 0000000..9534830
--- /dev/null
+++ b/Pipfile
@@ -0,0 +1,11 @@
+[[source]]
+name = "pypi"
+url = "https://pypi.org/simple"
+verify_ssl = true
+
+[dev-packages]
+
+[packages]
+
+[requires]
+python_version = "3.6"
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 0000000..419c7ab
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,20 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "415dfdcb118dd9bdfef17671cb7dcd78dbd69b6ae7d4f39e8b44e71d60ca72e7"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_version": "3.6"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
+    },
+    "default": {},
+    "develop": {}
+}
diff --git a/app.py b/app.py
deleted file mode 100644
index 4a9329d..0000000
--- a/app.py
+++ /dev/null
@@ -1,33 +0,0 @@
-import numpy as np
-from flask import Flask, request, jsonify, render_template
-import pickle
-
-app = Flask(__name__)
-model = pickle.load(open('final_prediction.pkl', 'rb'))
-
-@app.route('/')
-def home():
-    return render_template('index.html')
-
-@app.route('/predict',methods=['POST'])
-def predict():
-
-    int_features = [int(x) for x in request.form.values()]
-    final_features = [np.array(int_features)]
-    prediction = model.predict(final_features)
-
-    output = round(prediction[0], 2)
-
-    return render_template('index.html', prediction_text='This transaction is likely to be fraud in percentage by $ {}'.format(output))
-
-@app.route('/results',methods=['POST'])
-def results():
-
-    data = request.get_json(force=True)
-    prediction = model.predict([np.array(list(data.values()))])
-
-    output = prediction[0]
-    return jsonify(output)
-
-if __name__ == "__main__":
-    app.run(debug=True)
\ No newline at end of file
diff --git a/predict.py b/predict.py
new file mode 100644
index 0000000..2bfe6d9
--- /dev/null
+++ b/predict.py
@@ -0,0 +1,55 @@
+import numpy as np
+import sys
+import pickle
+
+model = pickle.load(open('final_prediction.pickle', 'rb'))
+
+
+def predict(argv):
+
+    int_features = [int(x) for x in argv[1:]]
+    final_features = [np.array(int_features)]
+    prediction = model.predict(final_features)
+
+    output = prediction[0]
+
+    return output
+
+
+if __name__ == '__main__':
+    predict(sys.argv)
+
+
+# app = Flask(__name__)
+# from flask import Flask, request, jsonify, render_template
+
+
+# @app.route('/')
+# def home():
+#     return render_template('index.html')
+
+
+# @app.route('/predict', methods=['POST'])
+# def predict():
+
+#     int_features = [int(x) for x in request.form.values()]
+#     final_features = [np.array(int_features)]
+#     prediction = model.predict(final_features)
+
+#     output = round(prediction[0], 2)
+
+#     return render_template('index.html', prediction_text='This transaction is likely to be fraud in percentage by $ {}'.format(output))
+
+
+# @app.route('/results', methods=['POST'])
+# def results():
+
+#     data = request.get_json(force=True)
+#     prediction = model.predict([np.array(list(data.values()))])
+
+#     output = prediction[0]
+#     return jsonify(output)
+
+
+# if __name__ == "__main__":
+#     app.run(debug=True)