Update app.py

app.py

@@ -119,17 +119,6 @@ def analyze(text):
     # Calculate probabilities using softmax
     prob_sentiment = torch.nn.functional.softmax(logits_sentiment, dim=1)[0]
 
-    # Prepare data for the BarPlot (numerical values)
-    chart_data = [
-        {"category": "Positive", "value": positive},
-        {"category": "Neutral", "value": neutral},
-        {"category": "Negative", "value": negative},
-        {"category": "Sent-Subj OBJ", "value": prob_sentiment[0].item()},
-        {"category": "Sent-Subj SUBJ", "value": prob_sentiment[1].item()},
-        {"category": "TextOnly OBJ", "value": prob_base[0].item()},
-        {"category": "TextOnly SUBJ", "value": prob_base[1].item()}
-    ]
-
     # Prepare data for the Dataframe (string values)
     table_data = [
         ["Positive", f"{positive:.2%}"],
@@ -141,7 +130,7 @@ def analyze(text):
         ["TextOnly SUBJ", f"{prob_base[1]:.2%}"]
     ]
 
-    return chart_data, table_data
+    return table_data
 
 # Update the Gradio interface
 with gr.Blocks(theme=gr.themes.Soft(), css="""
@@ -153,8 +142,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css="""
         txt = gr.Textbox(label="Enter text to analyze", placeholder="Paste news sentence here...", lines=2)
         btn = gr.Button("Analyze 🔍", variant="primary")
     with gr.Tabs():
-        with gr.TabItem("Overview 📊"):
-            chart = gr.BarPlot(x="category", y="value", label="Results", elem_id="result_chart")
         with gr.TabItem("Raw Scores 📋"):
             table = gr.Dataframe(headers=["Metric", "Value"], datatype=["str","str"], interactive=False, elem_id="result_table")
         with gr.TabItem("About ℹ️"):
@@ -164,13 +151,13 @@ with gr.Blocks(theme=gr.themes.Soft(), css="""
         gr.Examples(
             examples=examples,
             inputs=txt,
-            outputs=[chart, table],
+            outputs=[table],
             fn=analyze,
             label="Examples",
             elem_id="example_list",
             cache_examples=True,
         )
     # Link inputs to outputs
-    btn.click(fn=analyze, inputs=txt, outputs=[chart, table])
+    btn.click(fn=analyze, inputs=txt, outputs=[table])
 
 demo.queue().launch(server_name="0.0.0.0", share=True)