Update app.py

app.py

@@ -21,24 +21,24 @@ try:
     
     model1 = pipeline("text-classification", model=model1_name)
     test_output1 = model1("Testing the first model with a simple sentence.")
-    print("Model 1 test output:", test_output1)
+    print("Harassment Detector test output:", test_output1)
     
     model2 = pipeline("text-classification", model=model2_name)
     test_output2 = model2("Testing the second model with a simple sentence.")
-    print("Model 2 test output:", test_output2)
+    print("Depressive Detector test output:", test_output2)
 except Exception as e:
     print(f"Failed to load or run models: {e}")
 
 # Prediction function with model selection and error handling
 def predict_sentiment(text, model_choice):
     try:
-        if model_choice == "Model 1":
+        if model_choice == "Harassment Detector":
             if model1 is None:
-                raise ValueError("Model 1 not loaded.")
+                raise ValueError("Harassment Detector not loaded.")
             predictions = model1(text)
-        elif model_choice == "Model 2":
+        elif model_choice == "Depressive Detector":
             if model2 is None:
-                raise ValueError("Model 2 not loaded.")
+                raise ValueError("Depressive Detector not loaded.")
             predictions = model2(text)
         else:
             raise ValueError("Invalid model choice.")
@@ -49,11 +49,11 @@ def predict_sentiment(text, model_choice):
 
 # Define example inputs
 examples = [
-    ["I absolutely love this product! It has changed my life.", "Model 1"],
-    ["This is the worst movie I have ever seen. Completely disappointing.", "Model 1"],
-    ["I'm not sure how I feel about this new update. It has some good points, but also many drawbacks.", "Model 2"],
-    ["The customer service was fantastic! Very helpful and polite.", "Model 2"],
-    ["Honestly, this was quite a mediocre experience. Nothing special.", "Model 1"]
+    ["I absolutely love this product! It has changed my life.", "Harassment Detector"],
+    ["This is the worst movie I have ever seen. Completely disappointing.", "Harassment Detector"],
+    ["I'm not sure how I feel about this new update. It has some good points, but also many drawbacks.", "Depressive Detector"],
+    ["The customer service was fantastic! Very helpful and polite.", "Depressive Detector"],
+    ["Honestly, this was quite a mediocre experience. Nothing special.", "Harassment Detector"]
 ]
 
 # Gradio interface setup
@@ -63,7 +63,7 @@ iface = gr.Interface(
     description="Enter text to analyze sentiment. Powered by Hugging Face Transformers.",
     inputs=[
         gr.Textbox(lines=2, placeholder="Enter text here..."),
-        gr.Radio(choices=["Model 1", "Model 2"], label="Select Model")
+        gr.Radio(choices=["Harassment Detector", "Depressive Detector"], label="Select Model")
     ],
     outputs="text",
     examples=examples