"Model~Load"

app.py

@@ -1,7 +1,89 @@
 import gradio as gr
+import pandas as pd
+import numpy as np
+from joblib import dump, load
+from sklearn.model_selection import train_test_split
+from catboost import CatBoostClassifier, MetricVisualizer, Pool
+from sklearn.model_selection import GridSearchCV
+from sklearn.neighbors import KernelDensity
+import matplotlib.pyplot as plt
+import matplotlib
 
-def greet(name):
- return "Hello " + name + "!!"
+#Model Loading
+model = load('modelUser_Behavior.pkl')
+
+
+
+
+def predict_behavior_type(evaluation):
+ prediction = model.predict(evaluation)
+ return prediction 
+
+
+
+ 
+def analyze_data(inter_api_access_duration, api_access_uniqueness, sequence_length, vsession_duration, ip_type, num_sessions, num_users, num_unique_apis):
+ # Combine the input parameters into a single evaluation object or use them individually as needed
+ evaluation = [inter_api_access_duration, api_access_uniqueness, sequence_length, vsession_duration, ip_type, num_sessions, num_users, num_unique_apis]
+
+ # Call the model's predict function with the evaluation object or individual parameters as needed
+ prediction = predict_behavior_type(evaluation)
+
+ # Return the prediction or any output you desire
+ return prediction 
+
+
+# Create a Gradio Dataframe input with three columns and two rows
+inter_api_access_duration_input = gr.inputs.Number(label="Inter API Access Duration (sec)")
+api_access_uniqueness_input = gr.inputs.Number(label="API Access Uniqueness")
+sequence_length_input = gr.inputs.Number(label="Sequence Length (count)")
+vsession_duration_input = gr.inputs.Number(label="VSession Duration (min)")
+ip_type_input = gr.inputs.Dropdown(choices=["default", "alternative","datacenter"], label="IP Type")
+num_sessions_input = gr.inputs.Number(label="Number of Sessions")
+num_users_input = gr.inputs.Number(label="Number of Users")
+num_unique_apis_input = gr.inputs.Number(label="Number of Unique APIs")
+
+Inputs = [inter_api_access_duration_input, api_access_uniqueness_input, sequence_length_input,
+ vsession_duration_input, ip_type_input, num_sessions_input, num_users_input, num_unique_apis_input]
+# Define your output
+output = gr.outputs.Textbox(label="Analysis Result")
+
+examples = [
+ [0.000721, 0.019527, 12.960905, 273, "default", 708.0, 486.0, 123.0],
+ [0.000112, 0.002958, 20.859897, 109, "default", 1152.0, 778.0, 48.0],
+ [0.003907, 0.005867, 20.262226, 5635, "alternative", 1288.0, 1186.0, 141.0],
+ [0.120327, 0.5, 26, 188, "default", 8.0, 1.0, 13.0],
+ [0.000544, 0.128842, 8.294118, 28, "alternative", 134.0, 102.0, 109.0],
+ [852.92925, 0.5, 2.0, 102352, "datacenter", 2.0, 1.0, 1.0],
+ [59.243, 0.8, 5.0, 17773, "datacenter", 3.0, 1.0, 4.0],
+ [0.754, 0.6666666666666666, 3.0, 136, "datacenter", 2.0, 1.0, 2.0],
+ [66.93485714285714, 0.4285714285714285, 7.0, 28113, "datacenter", 3.0, 1.0, 3.0]
+]
+
+
+# Define your Gradio interface
+interface = gr.Interface(fn=analyze_data, inputs=Inputs,examples=examples, outputs=output, title="API Data Analysis~ Group No. 12",
+ description='''
+ Analyze API data using the specified inputs.
+ 
+inter_api_access_duration_input: It is a numerical input represented by a number field. Users can enter the duration of inter API access in seconds.
+ 
+api_access_uniqueness_input: It is a numerical input represented by a number field. Users can enter the level of uniqueness in API access.
+
+sequence_length_input: It is a numerical input represented by a number field. Users can enter the length of the sequence in counts.
+
+vsession_duration_input: It is a numerical input represented by a number field. Users can enter the duration of virtual sessions in minutes.
+
+ip_type_input: It is a dropdown input with two choices ("default" and "alternative"). Users can select the type of IP address.
+
+num_sessions_input: It is a numerical input represented by a number field. Users can enter the number of sessions.
+
+num_users_input: It is a numerical input represented by a number field. Users can enter the number of users.
+
+num_unique_apis_input: It is a numerical input represented by a number field. Users can enter the number of unique APIs.
+''',
+ layout="horizontal",
+ verbose=True)
+# Launch the interface
+interface.launch()
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()

modelUser_Behavior.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:57fb9ada224c5d5cc28ae296d9e19cff5341a0b310dd2d010f9f163c80eb7262
+size 64834