Create app.py

app.py

@@ -0,0 +1,70 @@
+# app.py
+import gradio as gr
+import pandas as pd
+from xgboost import XGBClassifier
+import pickle
+
+# Load model
+model = pickle.load(open('xgboost_model.pkl', 'rb'))
+
+def predict_defects(loc, complexity, operators, operands, comments):
+    """
+    Simplified prediction using only key metrics
+    """
+    # Create a complete input data with reasonable defaults
+    input_data = pd.DataFrame([[
+        loc,            # loc
+        complexity,     # v(g)
+        complexity,     # ev(g)
+        complexity,     # iv(g)
+        operators + operands,  # n
+        operators * operands,  # v
+        0.5,           # l (default)
+        2.0,           # d (default)
+        100,           # i (default)
+        200,           # e (default)
+        0.2,           # b (default)
+        30,            # t (default)
+        loc,           # lOCode
+        comments,      # lOComment
+        loc * 0.1,     # lOBlank
+        comments,      # locCodeAndComment
+        operators,     # uniq_Op
+        operands,      # uniq_Opnd
+        operators * 2, # total_Op
+        operands * 2,  # total_Opnd
+        complexity     # branchCount
+    ]], columns=['loc', 'v(g)', 'ev(g)', 'iv(g)', 'n', 'v',
+                'l', 'd', 'i', 'e', 'b', 't', 'lOCode',
+                'lOComment', 'lOBlank', 'locCodeAndComment',
+                'uniq_Op', 'uniq_Opnd', 'total_Op',
+                'total_Opnd', 'branchCount'])
+    
+    # Make prediction
+    prediction = model.predict_proba(input_data)[0][1]
+    
+    return f"Defect Probability: {prediction:.2%}"
+
+# Gradio interface
+iface = gr.Interface(
+    fn=predict_defects,
+    inputs=[
+        gr.Slider(minimum=1, maximum=1000, value=100, 
+                 label="Lines of Code", info="Total number of code lines"),
+        gr.Slider(minimum=1, maximum=50, value=5, 
+                 label="Code Complexity", info="How complex is your code"),
+        gr.Slider(minimum=1, maximum=100, value=20, 
+                 label="Unique Operators", info="Number of different operators (+, -, *, etc.)"),
+        gr.Slider(minimum=1, maximum=100, value=20, 
+                 label="Unique Operands", info="Number of different variables and constants"),
+        gr.Slider(minimum=0, maximum=500, value=50, 
+                 label="Comment Lines", info="Number of comment lines"),
+    ],
+    outputs="text",
+    title="Software Defect Predictor",
+    description="Predict the probability of software defects based on code metrics",
+    theme="soft"
+)
+
+if __name__ == "__main__":
+    iface.launch()