Update app.py

app.py

@@ -878,12 +878,128 @@ def show_current_context() -> str:
         messages = storage.get_messages_by_session(storage.current_session_id)
         if not messages:
             return "No messages in the current session."
-        # Show up to the last 5 messages for brevity
         context = "\n".join([f"{msg['role'].capitalize()}: {msg['content']}" for msg in messages[-5:]])
         return f"Current Session Context (Last 5 Messages):\n{context}"
     except Exception as e:
         return f"❌ Error retrieving context: {str(e)}"
 
+def get_full_history(topic_filter: str = None) -> str:
+    """Display the full chat history, optionally filtered by topic."""
+    try:
+        filters = {'topic': topic_filter} if topic_filter and topic_filter != "All Topics" else None
+        messages = storage.search_messages("", filters)
+        if not messages:
+            return "No messages found in the history."
+        history = "\n".join([f"[{msg['timestamp']}] {msg['role'].capitalize()} (Topic: {msg['topic']}): {msg['content']}" for msg in messages])
+        return f"Chat History:\n{history}"
+    except Exception as e:
+        return f"❌ Error retrieving history: {str(e)}"
+
+def get_chat_summary(topic_filter: str = None) -> str:
+    """Provide a summary of the chat history, optionally filtered by topic."""
+    try:
+        filters = {'topic': topic_filter} if topic_filter and topic_filter != "All Topics" else None
+        messages = storage.search_messages("", filters)
+        if not messages:
+            return "No messages found for summary."
+        
+        total_messages = len(messages)
+        user_messages = len([msg for msg in messages if msg['role'] == 'user'])
+        assistant_messages = len([msg for msg in messages if msg['role'] == 'assistant'])
+        topics = Counter(msg['topic'] for msg in messages)
+        sessions = len(set(msg['session_id'] for msg in messages))
+        
+        summary = (
+            f"Chat Summary:\n"
+            f"Total Messages: {total_messages}\n"
+            f"User Messages: {user_messages}\n"
+            f"Assistant Messages: {assistant_messages}\n"
+            f"Number of Sessions: {sessions}\n"
+            f"Topic Distribution:\n" +
+            "\n".join([f"  - {topic}: {count}" for topic, count in topics.most_common()])
+        )
+        return summary
+    except Exception as e:
+        return f"❌ Error generating summary: {str(e)}"
+
+def clear_all_history() -> Tuple[str, str, str]:
+    """Clear all chat history and analytics data."""
+    try:
+        storage.clear_history()
+        return (
+            "✅ All chat history and analytics cleared successfully.",
+            "",  # Clear history_display
+            ""   # Clear analytics_display
+        )
+    except Exception as e:
+        return (
+            f"❌ Error clearing history: {str(e)}",
+            history_display.value if 'history_display' in globals() else "",
+            analytics_display.value if 'analytics_display' in globals() else ""
+        )
+
+def get_analytics_report() -> str:
+    """Generate a detailed analytics report using SmartAnalyzer."""
+    try:
+        patterns = analyzer.get_conversation_patterns()
+        mood_trends = analyzer.get_mood_trends()
+        productivity = analyzer.get_productivity_insights()
+        
+        if "error" in patterns or "error" in mood_trends or "error" in productivity:
+            return (
+                f"❌ Error in analytics:\n"
+                f"Patterns: {patterns.get('error', 'OK')}\n"
+                f"Mood Trends: {mood_trends.get('error', 'OK')}\n"
+                f"Productivity: {productivity.get('error', 'OK')}"
+            )
+        
+        report = (
+            "📊 Analytics Report\n\n"
+            "=== Conversation Patterns ===\n"
+            f"Total Messages: {patterns['total_messages']}\n"
+            f"User Messages: {patterns['user_messages']}\n"
+            f"Messages by Role: {patterns['by_role']}\n"
+            f"Top Topics: {patterns['by_topic']}\n"
+            f"Peak Hours: {patterns['peak_hours']}\n"
+            f"Peak Days: {patterns['peak_days']}\n"
+            f"Common Words: {patterns['common_words']}\n"
+            f"Average Words per Message: {patterns['avg_words_per_message']}\n"
+            f"Date Range: {patterns['date_range']['start']} to {patterns['date_range']['end']}\n\n"
+            "=== Mood Trends ===\n"
+            f"Overall Sentiment: {dict(mood_trends['overall_sentiment'])}\n"
+            f"Sentiment by Topic: {mood_trends['sentiment_by_topic']}\n"
+            f"Daily Mood Summary:\n" +
+            "\n".join([f"  - {date}: {data['dominant']} ({data['distribution']})" 
+                      for date, data in mood_trends['daily_moods'].items()]) + "\n\n"
+            "=== Productivity Insights ===\n"
+            f"Total Sessions: {productivity['total_sessions']}\n"
+            f"Average Messages per Session: {round(productivity['avg_messages_per_session'], 1)}\n"
+            f"Most Active Day: {productivity['most_active_day']}\n"
+            f"Recent Activity (Last 7 Days): {productivity['recent_activity']} messages\n"
+            f"Consistency Score: {productivity['consistency_score']}\n"
+            f"Weekly Patterns: {productivity['weekly_patterns']}"
+        )
+        return report
+    except Exception as e:
+        return f"❌ Error generating analytics report: {str(e)}"
+
+def export_data() -> str:
+    """Export chat history and analytics data to JSON format."""
+    try:
+        export_data = {
+            "chat_history": storage.chat_history,
+            "analytics": storage.analytics,
+            "sessions": storage.get_all_sessions()
+        }
+        export_json = json.dumps(export_data, indent=2, ensure_ascii=False)
+        return export_json
+    except Exception as e:
+        return f"❌ Error exporting data: {str(e)}"
+
+# Initialize storage and components
+storage = ChatStorage()
+analyzer = SmartAnalyzer(storage)
+search_manager = AdvancedSearchManager(storage)
 
 
 # Define custom CSS for the Gradio interface