Modify predictions output if all same

app.py

@@ -108,19 +108,21 @@ def analyze_sentiment_and_statistics(text):
     
     # Calculate statistics
     scores = list(results.values())
-    if all(score == scores[0] for score in scores):  # Check if all predictions are the same
+    min_score = min(scores)
+    max_score = max(scores)
+    min_score_models = [model for model, score in results.items() if score == min_score]
+    max_score_models = [model for model, score in results.items() if score == max_score]
+    average_score = np.mean(scores)
+
+    if all(score == scores[0] for score in scores):
         statistics = {
             "Message": "All models predict the same score.",
-            "Average Score": f"{scores[0]:.2f}",
+            "Average Score": f"{average_score:.2f}",
         }
     else:
-        min_score_model = min(results, key=results.get)
-        max_score_model = max(results, key=results.get)
-        average_score = np.mean(scores)
-        
         statistics = {
-            "Lowest Score": f"{results[min_score_model]} (Model: {min_score_model})",
-            "Highest Score": f"{results[max_score_model]} (Model: {max_score_model})",
+            "Lowest Score": f"{min_score} (Models: {', '.join(min_score_models)})",
+            "Highest Score": f"{max_score} (Models: {', '.join(max_score_models)})",
             "Average Score": f"{average_score:.2f}",
         }
     return results, statistics
@@ -179,7 +181,7 @@ with gr.Blocks(css=".gradio-container { max-width: 900px; margin: auto; padding:
     # Button to analyze sentiment and show statistics
     def process_input_and_analyze(text_input):
         results, statistics = analyze_sentiment_and_statistics(text_input)
-        if "Message" in statistics:  # All models predicted the same score
+        if "Message" in statistics:
             return (
                 f"{results['DistilBERT']}",
                 f"{results['Logistic Regression']}",
@@ -188,7 +190,7 @@ with gr.Blocks(css=".gradio-container { max-width: 900px; margin: auto; padding:
                 f"{results['RoBERTa']}",
                 f"Statistics:\n{statistics['Message']}\nAverage Score: {statistics['Average Score']}"
             )
-        else:  # Min and Max scores are present
+        else:
             return (
                 f"{results['DistilBERT']}",
                 f"{results['Logistic Regression']}",