Update visualization.py

visualization.py

@@ -1,35 +1,25 @@
-import gradio as gr
-import plotly.graph_objs as go
-import re
-from collections import Counter
-
-def extract_speaker_data(text):
-    speakers = {}
-    current_speaker = None
+def extract_data_and_explanation(text):
+    data = {}
     explanation = ""
-    for line in text.split('\n'):
-        if line.lower().startswith("speaker"):
-            current_speaker = line.split(":")[1].strip() if ":" in line else line.split()[1]
-            speakers[current_speaker] = {}
-        elif current_speaker and ":" in line:
-            key, value = line.split(":", 1)
+    lines = text.split('\n')
+    for line in lines:
+        if ':' in line:
+            key, value = line.split(':', 1)
             try:
-                speakers[current_speaker][key.strip()] = float(value.strip())
+                data[key.strip()] = float(value.strip())
             except ValueError:
-                match = re.search(r"[-+]?\d*\.\d+|\d+", value)
-                if match:
-                    speakers[current_speaker][key.strip()] = float(match.group())
+                pass
         elif line.lower().startswith("explanation:"):
             explanation = line.split("Explanation:", 1)[1].strip()
-    return speakers, explanation
+    return data, explanation
 
-def create_bar_chart(data, title, speaker):
+def create_bar_chart(data, title):
     fig = go.Figure(data=[go.Bar(
         x=list(data.keys()), 
         y=list(data.values()),
         marker_color=['red', 'green', 'blue', 'yellow', 'purple', 'orange', 'pink', 'cyan', 'magenta', 'brown'][:len(data)]
     )])
-    fig.update_layout(title=f"{title} - Speaker {speaker}", xaxis_title="Traits", yaxis_title="Score")
+    fig.update_layout(title=title, xaxis_title="Traits", yaxis_title="Score")
     return fig
 
 def update_visibility_and_charts(status, exec_time, lang, attachments, bigfive, personalities):
@@ -40,27 +30,11 @@ def update_visibility_and_charts(status, exec_time, lang, attachments, bigfive,
     ]
     
     for analysis_text, analysis_type in [(attachments, "Attachments"), (bigfive, "Big Five"), (personalities, "Personalities")]:
-        speakers_data, explanation = extract_speaker_data(analysis_text)
-        if not speakers_data:
-            print(f"No speaker data extracted from: {analysis_text}")
-            continue
-
-        speaker_counts = Counter(speakers_data.keys())
-        main_speakers = [speaker for speaker, count in speaker_counts.most_common(2)]
-        
-        for speaker in main_speakers:
-            data = speakers_data.get(speaker, {})
-            if analysis_type == "Attachments":
-                chart_data = {k: v for k, v in data.items() if k in ["Secured", "Anxious-Preoccupied", "Dismissive-Avoidant", "Fearful-Avoidant"]}
-            elif analysis_type == "Big Five":
-                chart_data = {k: v for k, v in data.items() if k in ["Extraversion", "Agreeableness", "Conscientiousness", "Neuroticism", "Openness"]}
-            elif analysis_type == "Personalities":
-                chart_data = {k: v for k, v in data.items() if k in ["Depressed", "Paranoid", "Schizoid-Schizotypal", "Antisocial-Psychopathic", "Borderline-Dysregulated", "Hysteric-Histrionic", "Narcissistic", "Anxious-Avoidant", "Dependent-Victimized", "Obsessional"]}
-            
-            if chart_data:
-                fig = create_bar_chart(chart_data, f"{analysis_type} Styles", speaker)
-                outputs.append(gr.Plot(value=fig))
-                outputs.append(gr.Textbox(value=explanation, label=f"{analysis_type} Explanation - Speaker {speaker}"))
+        data, explanation = extract_data_and_explanation(analysis_text)
+        if data:
+            fig = create_bar_chart(data, f"{analysis_type} Analysis")
+            outputs.append(gr.Plot(value=fig))
+            outputs.append(gr.Textbox(value=explanation, label=f"{analysis_type} Explanation"))
     
     print("Outputs generated:", outputs)
     return outputs