lifestyle_app.py

# lifestyle_app.py - Main application class

import os
import json
import time
from datetime import datetime
from dataclasses import asdict
from typing import List, Dict, Optional, Tuple

from core_classes import (
    ClinicalBackground, LifestyleProfile, ChatMessage, SessionState,
    AIClientManager, PatientDataLoader,
    MedicalAssistant,
    # Active classifiers
    EntryClassifier, TriageExitClassifier,
    LifestyleSessionManager,
    # Main Lifestyle Assistant
    MainLifestyleAssistant,
    # Soft medical triage
    SoftMedicalTriage
)
from testing_lab import TestingDataManager, PatientTestingInterface, TestSession
from test_patients import TestPatientData
from file_utils import FileHandler

class ExtendedLifestyleJourneyApp:
    """Extended version of the app with Testing Lab functionality"""
    
    def __init__(self):
        self.api = AIClientManager()
        # Active classifiers
        self.entry_classifier = EntryClassifier(self.api)
        self.triage_exit_classifier = TriageExitClassifier(self.api)
        # LifestyleExitClassifier removed - functionality moved to MainLifestyleAssistant
        # Assistants
        self.medical_assistant = MedicalAssistant(self.api)
        self.main_lifestyle_assistant = MainLifestyleAssistant(self.api)
        self.soft_medical_triage = SoftMedicalTriage(self.api)
        # Lifecycle manager
        self.lifestyle_session_manager = LifestyleSessionManager(self.api)
        
        # Testing Lab components
        self.testing_manager = TestingDataManager()
        self.testing_interface = PatientTestingInterface(self.testing_manager)
        
        # Loading standard data
        print("🔄 Loading standard patient data...")
        self.clinical_background = PatientDataLoader.load_clinical_background()
        self.lifestyle_profile = PatientDataLoader.load_lifestyle_profile()
        
        print(f"✅ Loaded standard profile: {self.clinical_background.patient_name}")
        
        # App state
        self.chat_history: List[ChatMessage] = []
        self.session_state = SessionState(
            current_mode="none",
            is_active_session=False,
            session_start_time=None,
            last_controller_decision={}
        )
        
        # Testing states
        self.test_mode_active = False
        self.current_test_patient = None
    
    def load_test_patient(self, clinical_file, lifestyle_file) -> Tuple[str, str, List, str]:
        """Loads test patient from files"""
        try:
            # Read clinical background
            clinical_content, error = FileHandler.read_uploaded_file(clinical_file, "clinical_background.json")
            if error:
                return error, "", [], self._get_status_info()
            
            clinical_data, error = FileHandler.parse_json_file(clinical_content, "clinical_background.json")
            if error:
                return error, "", [], self._get_status_info()
            
            # Read lifestyle profile
            lifestyle_content, error = FileHandler.read_uploaded_file(lifestyle_file, "lifestyle_profile.json")
            if error:
                return error, "", [], self._get_status_info()
                
            lifestyle_data, error = FileHandler.parse_json_file(lifestyle_content, "lifestyle_profile.json")
            if error:
                return error, "", [], self._get_status_info()
            
            # Use common processing method
            return self._process_patient_data(clinical_data, lifestyle_data, "")
            
        except Exception as e:
            return f"❌ File loading error: {str(e)}", "", [], self._get_status_info()

    def load_quick_test_patient(self, patient_type: str) -> Tuple[str, str, List, str]:
        """Loads built-in test data for quick testing"""
        
        patient_type_names = TestPatientData.get_patient_types()
        
        try:
            clinical_data, lifestyle_data = TestPatientData.get_patient_data(patient_type)
            test_type_description = patient_type_names.get(patient_type, "")
            result = self._process_patient_data(
                clinical_data, 
                lifestyle_data, 
                f"⚡ **Quick test:** {test_type_description}"
            )
            return result
        except ValueError as e:
            return f"❌ {str(e)}", "", [], self._get_status_info()
        except Exception as e:
            return f"❌ Quick test loading error: {str(e)}", "", [], self._get_status_info()
    
    def _process_patient_data(self, clinical_data: dict, lifestyle_data: dict, test_type_info: str = "") -> Tuple[str, str, List, str]:
        """Common code for processing patient data"""
        
        debug_enabled = os.getenv("LOG_PROMPTS", "false").lower() == "true"
        if debug_enabled:
            print(f"🔄 _process_patient_data called with test_type_info: '{test_type_info}'")
        
        # STEP 1: End previous test session if active
        if self.test_mode_active and self.testing_interface.current_session:
            if debug_enabled:
                print("🔄 Ending previous test session...")
            self.end_test_session("Automatically ended - new patient loaded")
        
        # Clinical data validation
        is_valid, errors = self.testing_manager.validate_clinical_background(clinical_data)
        if not is_valid:
            return f"❌ Clinical background validation error:\n" + "\n".join(errors), "", [], self._get_status_info()
        
        # Lifestyle data validation
        is_valid, errors = self.testing_manager.validate_lifestyle_profile(lifestyle_data)
        if not is_valid:
            return f"❌ Lifestyle profile validation error:\n" + "\n".join(errors), "", [], self._get_status_info()
        
        # Create objects
        self.clinical_background = ClinicalBackground(
            patient_id="test_patient",
            patient_name=lifestyle_data.get("patient_name", "Test Patient"),
            patient_age=lifestyle_data.get("patient_age", "unknown"),
            active_problems=clinical_data.get("patient_summary", {}).get("active_problems", []),
            past_medical_history=clinical_data.get("patient_summary", {}).get("past_medical_history", []),
            current_medications=clinical_data.get("patient_summary", {}).get("current_medications", []),
            allergies=clinical_data.get("patient_summary", {}).get("allergies", ""),
            vital_signs_and_measurements=clinical_data.get("vital_signs_and_measurements", []),
            laboratory_results=clinical_data.get("laboratory_results", []),
            assessment_and_plan=clinical_data.get("assessment_and_plan", ""),
            critical_alerts=clinical_data.get("critical_alerts", []),
            social_history=clinical_data.get("social_history", {}),
            recent_clinical_events=clinical_data.get("recent_clinical_events_and_encounters", [])
        )
        
        self.lifestyle_profile = LifestyleProfile(
            patient_name=lifestyle_data.get("patient_name", "Test Patient"),
            patient_age=lifestyle_data.get("patient_age", "unknown"),
            conditions=lifestyle_data.get("conditions", []),
            primary_goal=lifestyle_data.get("primary_goal", ""),
            exercise_preferences=lifestyle_data.get("exercise_preferences", []),
            exercise_limitations=lifestyle_data.get("exercise_limitations", []),
            dietary_notes=lifestyle_data.get("dietary_notes", []),
            personal_preferences=lifestyle_data.get("personal_preferences", []),
            journey_summary=lifestyle_data.get("journey_summary", ""),
            last_session_summary=lifestyle_data.get("last_session_summary", ""),
            next_check_in=lifestyle_data.get("next_check_in", "not set"),
            progress_metrics=lifestyle_data.get("progress_metrics", {})
        )
        
        # Save test patient profile
        patient_id = self.testing_manager.save_patient_profile(clinical_data, lifestyle_data)
        self.current_test_patient = patient_id
        
        # Activate test mode
        self.test_mode_active = True
        
        # STEP 2: COMPLETELY RESET CHAT STATE
        self.chat_history = []
        self.session_state = SessionState(
            current_mode="none",
            is_active_session=False,
            session_start_time=None,
            last_controller_decision={}
        )
        
        # Start test session
        session_start_msg = self.testing_interface.start_test_session(
            self.lifestyle_profile.patient_name
        )
        
        # Create initial chat message about new patient
        welcome_content = f"🧪 **New test patient loaded: {self.lifestyle_profile.patient_name}**"
        if test_type_info:
            welcome_content += f"\n{test_type_info}"
        welcome_content += "\n\nYou can start the dialogue. All interactions will be logged for analysis."
        
        welcome_message = {
            "role": "assistant", 
            "content": welcome_content
        }
        
        if debug_enabled:
            print(f"✅ Created new patient: {self.lifestyle_profile.patient_name}")
            print(f"💬 Welcome message: {welcome_content[:100]}...")
        
        success_msg = f"""✅ **NEW TEST PATIENT LOADED**

👤 **Patient:** {self.lifestyle_profile.patient_name} ({self.lifestyle_profile.patient_age} years old)
🏥 **Active problems:** {len(self.clinical_background.active_problems)}
💊 **Medications:** {len(self.clinical_background.current_medications)}
🎯 **Lifestyle goal:** {self.lifestyle_profile.primary_goal[:100]}...
📋 **Patient ID:** {patient_id}

{session_start_msg}

🧪 **TEST MODE ACTIVATED** - all interactions will be logged.

💬 **CHAT RESET** - you can start a new conversation!"""

        preview = self._generate_patient_preview()
        
        # Return: result, preview, CHAT WITH WELCOME MESSAGE, UPDATED STATUS
        if debug_enabled:
            print(f"📤 Returning 4 values: success_msg, preview, chat=[1 message], status")
        return success_msg, preview, [welcome_message], self._get_status_info()
    
    def _generate_patient_preview(self) -> str:
        """Generates preview of loaded patient"""
        if not self.clinical_background or not self.lifestyle_profile:
            return "Patient data not loaded"
        
        # Shortened lists for convenient viewing
        active_problems = self.clinical_background.active_problems[:5]
        medications = self.clinical_background.current_medications[:8]
        conditions = self.lifestyle_profile.conditions[:5]
        
        preview = f"""
📋 **MEDICAL PROFILE**
👤 **Name:** {self.clinical_background.patient_name}
🎂 **Age:** {self.lifestyle_profile.patient_age}

🏥 **Active problems ({len(self.clinical_background.active_problems)}):**
{chr(10).join([f"• {problem}" for problem in active_problems])}
{"..." if len(self.clinical_background.active_problems) > 5 else ""}

💊 **Medications ({len(self.clinical_background.current_medications)}):**
{chr(10).join([f"• {med}" for med in medications])}
{"..." if len(self.clinical_background.current_medications) > 8 else ""}

🚨 **Critical alerts:** {len(self.clinical_background.critical_alerts)}
🧪 **Laboratory results:** {len(self.clinical_background.laboratory_results)}

💚 **LIFESTYLE PROFILE**
🎯 **Primary goal:** {self.lifestyle_profile.primary_goal}

🏃 **Conditions:** {', '.join(conditions)}
{"..." if len(self.lifestyle_profile.conditions) > 5 else ""}

⚠️ **Limitations:** {len(self.lifestyle_profile.exercise_limitations)}
🍽️ **Nutrition:** {len(self.lifestyle_profile.dietary_notes)} notes
📈 **Progress metrics:** {len(self.lifestyle_profile.progress_metrics)} indicators
"""
        return preview
    
    def process_message(self, message: str, history) -> Tuple[List, str]:
        """New message processing logic with three classifiers"""
        start_time = time.time()
        
        if not message.strip():
            return history, self._get_status_info()
        
        # Add user message to history
        user_msg = ChatMessage(
            timestamp=datetime.now().strftime("%H:%M"),
            role="user", 
            message=message,
            mode="pending"  # Will be updated after classification
        )
        self.chat_history.append(user_msg)
        
        # NEW LOGIC: Determine current state and process accordingly
        response = ""
        final_mode = "none"
        
        if self.session_state.current_mode == "lifestyle":
            # If already in lifestyle mode, check if need to exit
            response, final_mode = self._handle_lifestyle_mode(message)
        else:
            # If not in lifestyle mode, use Entry Classifier
            response, final_mode = self._handle_entry_classification(message)
        
        # Update mode in user message
        user_msg.mode = final_mode
        
        # Add assistant response
        assistant_msg = ChatMessage(
            timestamp=datetime.now().strftime("%H:%M"),
            role="assistant",
            message=response,
            mode=final_mode
        )
        self.chat_history.append(assistant_msg)
        
        # Update session state
        self.session_state.current_mode = final_mode
        self.session_state.is_active_session = final_mode != "none"
        
        # Logging for testing
        response_time = time.time() - start_time
        if self.test_mode_active and self.testing_interface.current_session:
            self.testing_interface.log_message_interaction(
                final_mode, 
                {"mode": final_mode, "reasoning": "new_logic"}, 
                response_time,
                False
            )
        
        # Update Gradio history
        if not history:
            history = []
        
        history.append({"role": "user", "content": message})
        history.append({"role": "assistant", "content": response})
        
        return history, self._get_status_info()
    
    def _handle_entry_classification(self, message: str) -> Tuple[str, str]:
        """Processes message through Entry Classifier with new K/V/T format"""
        
        # 1. Classify message
        classification = self.entry_classifier.classify(message, self.clinical_background)
        self.session_state.entry_classification = classification
        
        lifestyle_mode = classification.get("V", "off")
        
        if lifestyle_mode == "off":
            response = self.soft_medical_triage.conduct_triage(
                message, 
                self.clinical_background,
                self.chat_history  
            )
            return response, "medical"
            
        elif lifestyle_mode == "on":
            # Direct to lifestyle mode
            self.session_state.lifestyle_session_length = 1
            result = self.main_lifestyle_assistant.process_message(
                message, self.chat_history, self.clinical_background, self.lifestyle_profile, 1
            )
            return result.get("message", "How are you feeling?"), "lifestyle"
            
        elif lifestyle_mode == "hybrid":
            # Hybrid flow: medical triage + possible lifestyle
            return self._handle_hybrid_flow(message, classification)
        
        else:
            # Fallback to medical mode with soft triage
            response = self.soft_medical_triage.conduct_triage(
                message, 
                self.clinical_background,
                self.chat_history  # Додано!
            )
            return response, "medical"
    
    def _handle_hybrid_flow(self, message: str, classification: Dict) -> Tuple[str, str]:
        """Handles HYBRID messages: medical triage + lifestyle assessment"""
        
        # 1. Medical triage (use regular medical assistant for hybrid)
        medical_response = self.medical_assistant.generate_response(
            message, self.chat_history, self.clinical_background
        )
        
        # Save triage result
        if medical_response:
            self.session_state.last_triage_summary = medical_response[:200] + "..."
        else:
            self.session_state.last_triage_summary = "Medical assessment completed"
        
        # 2. Assess readiness for lifestyle
        triage_assessment = self.triage_exit_classifier.assess_readiness(
            self.clinical_background, 
            self.session_state.last_triage_summary,
            message
        )
        
        if triage_assessment.get("ready_for_lifestyle", False):
            # Switch to lifestyle mode with new assistant
            self.session_state.lifestyle_session_length = 1
            result = self.main_lifestyle_assistant.process_message(
                message, self.chat_history, self.clinical_background, self.lifestyle_profile, 1
            )
            
            # Combine responses
            combined_response = f"{medical_response}\n\n---\n\n💚 **Lifestyle coaching:**\n{result.get('message', 'How are you feeling?')}"
            return combined_response, "lifestyle"
        else:
            # Stay in medical mode
            return medical_response, "medical"
    
    def _handle_lifestyle_mode(self, message: str) -> Tuple[str, str]:
        """Handles messages in lifestyle mode with new Main Lifestyle Assistant"""
        
        # Use new Main Lifestyle Assistant
        result = self.main_lifestyle_assistant.process_message(
            message, 
            self.chat_history, 
            self.clinical_background, 
            self.lifestyle_profile,
            self.session_state.lifestyle_session_length
        )
        
        action = result.get("action", "lifestyle_dialog")
        response_message = result.get("message", "How are you feeling?")
        
        if action == "close":
            # End lifestyle session and update profile with LLM analysis
            self.lifestyle_profile = self.lifestyle_session_manager.update_profile_after_session(
                self.lifestyle_profile, 
                self.chat_history,
                f"Automatic session end: {result.get('reasoning', 'MainLifestyleAssistant decided to close')}",
                save_to_disk=True
            )
            
            # Switch to medical mode
            medical_response = self.medical_assistant.generate_response(
                message, self.chat_history, self.clinical_background
            )
            
            # Reset lifestyle counter
            self.session_state.lifestyle_session_length = 0
            
            return f"💚 **Lifestyle session completed.** {result.get('reasoning', '')}\n\n---\n\n{medical_response}", "medical"
        
        else:
            # Continue lifestyle mode (gather_info or lifestyle_dialog)
            self.session_state.lifestyle_session_length += 1
            return response_message, "lifestyle"
    

    
    def end_test_session(self, notes: str = "") -> str:
        """Ends current test session"""
        if not self.test_mode_active or not self.testing_interface.current_session:
            return "❌ No active test session to end"
        
        # Get current profile state
        final_profile = {
            "clinical_background": asdict(self.clinical_background),
            "lifestyle_profile": asdict(self.lifestyle_profile),
            "chat_history_length": len(self.chat_history)
        }
        
        result = self.testing_interface.end_test_session(final_profile, notes)
        
        # Turn off test mode
        self.test_mode_active = False
        self.current_test_patient = None
        
        return result
    
    def get_test_results_summary(self) -> Tuple[str, List]:
        """Returns summary of all test results"""
        sessions = self.testing_manager.get_all_test_sessions()
        
        if not sessions:
            return "📭 No saved test sessions", []
        
        # Generate report
        summary = self.testing_manager.generate_summary_report(sessions)
        
        # Create detailed table of recent sessions
        latest_sessions = sessions[:10]  # Last 10 sessions
        
        table_data = []
        for session in latest_sessions:
            table_data.append([
                session.get('patient_name', 'N/A'),
                session.get('timestamp', 'N/A')[:16],  # Date and time only
                session.get('total_messages', 0),
                session.get('medical_messages', 0),
                session.get('lifestyle_messages', 0),
                session.get('escalations_count', 0),
                f"{session.get('session_duration_minutes', 0):.1f} min",
                session.get('notes', '')[:50] + "..." if len(session.get('notes', '')) > 50 else session.get('notes', '')
            ])
        
        return summary, table_data
    
    def export_test_results(self) -> str:
        """Exports test results"""
        sessions = self.testing_manager.get_all_test_sessions()
        
        if not sessions:
            return "❌ No data to export"
        
        csv_path = self.testing_manager.export_results_to_csv(sessions)
        
        if csv_path and os.path.exists(csv_path):
            return f"✅ Data exported to: {csv_path}"
        else:
            return "❌ Data export error"
    
    def _get_ai_providers_status(self) -> str:
        """Get detailed AI providers status"""
        try:
            clients_info = self.api.get_all_clients_info()
            
            status_lines = []
            status_lines.append(f"🤖 **AI PROVIDERS STATUS:**")
            status_lines.append(f"• Total API calls: {clients_info['total_calls']}")
            status_lines.append(f"• Active clients: {clients_info['active_clients']}")
            
            if clients_info['clients']:
                status_lines.append("• Client details:")
                for agent, info in clients_info['clients'].items():
                    if 'error' not in info:
                        provider = info['provider']
                        model = info['model']
                        fallback = " (fallback)" if info['using_fallback'] else ""
                        status_lines.append(f"  - {agent}: {provider} ({model}){fallback}")
                    else:
                        status_lines.append(f"  - {agent}: Error - {info['error']}")
            
            return "\n".join(status_lines)
        except Exception as e:
            return f"🤖 **AI PROVIDERS STATUS:** Error - {e}"
    
    def _get_status_info(self) -> str:
        """Extended status information with new logic"""
        log_prompts_enabled = os.getenv("LOG_PROMPTS", "false").lower() == "true"
        
        # Basic information
        active_problems = self.clinical_background.active_problems[:3] if self.clinical_background.active_problems else ["No data"]
        problems_text = "; ".join(active_problems)
        if len(self.clinical_background.active_problems) > 3:
            problems_text += f" and {len(self.clinical_background.active_problems) - 3} more..."
        
        # K/V/T classification information
        entry_info = ""
        if self.session_state.entry_classification:
            classification = self.session_state.entry_classification
            entry_info = f"""
🔍 **LAST CLASSIFICATION (K/V/T):**
• K: {classification.get('K', 'N/A')}
• V: {classification.get('V', 'N/A')}
• T: {classification.get('T', 'N/A')}"""
        
        # Lifestyle session information
        lifestyle_info = ""
        if self.session_state.current_mode == "lifestyle":
            lifestyle_info = f"""
💚 **LIFESTYLE SESSION:**
• Messages in session: {self.session_state.lifestyle_session_length}
• Last summary: {self.lifestyle_profile.last_session_summary[:100]}...
"""
        
        # Test information
        test_status = ""
        if self.test_mode_active:
            test_status += f"\n👤 **ACTIVE TEST PATIENT: {self.lifestyle_profile.patient_name}**"
            
            current_session = self.testing_interface.current_session
            if current_session:
                test_status += f"""

🧪 **TEST SESSION ACTIVE**
• ID: {current_session.session_id}
• Messages: {current_session.total_messages}
• Medical: {current_session.medical_messages} | Lifestyle: {current_session.lifestyle_messages}
• Escalations: {current_session.escalations_count}
"""
            else:
                test_status += f"\n📝 Test session not active (loaded but not started)"
        
        status = f"""
📊 **SESSION STATE (NEW LOGIC)**
• Mode: {self.session_state.current_mode.upper()}
• Active: {'✅' if self.session_state.is_active_session else '❌'}
• Logging: {'📝 ACTIVE' if log_prompts_enabled else '❌ DISABLED'}
{entry_info}
{lifestyle_info}
👤 **PATIENT: {self.clinical_background.patient_name}**{' (TEST)' if self.test_mode_active else ''}
• Age: {self.lifestyle_profile.patient_age}
• Active problems: {problems_text}
• Lifestyle goal: {self.lifestyle_profile.primary_goal}

🏥 **MEDICAL CONTEXT:**
• Medications: {len(self.clinical_background.current_medications)}
• Critical alerts: {len(self.clinical_background.critical_alerts)}
• Recent vitals: {len(self.clinical_background.vital_signs_and_measurements)}

🔧 **AI STATISTICS:**
• Total API calls: {self.api.call_counter}
• Active AI clients: {len(self.api._clients)}

{self._get_ai_providers_status()}
{test_status}"""
        
        return status
    
    def reset_session(self) -> Tuple[List, str]:
        """Session reset with new logic"""
        # If test mode is active, end session
        if self.test_mode_active and self.testing_interface.current_session:
            self.end_test_session("Session reset by user")
        
        # If there was an active lifestyle session, update profile
        if self.session_state.current_mode == "lifestyle" and self.session_state.lifestyle_session_length > 0:
            self.lifestyle_profile = self.lifestyle_session_manager.update_profile_after_session(
                self.lifestyle_profile, 
                self.chat_history,
                "Session reset by user",
                save_to_disk=True
            )
        
        self.chat_history = []
        self.session_state = SessionState(
            current_mode="none",
            is_active_session=False, 
            session_start_time=None,
            last_controller_decision={},
            lifestyle_session_length=0,
            last_triage_summary="",
            entry_classification={}
        )
        
        return [], self._get_status_info()
    
    def end_conversation_with_profile_update(self) -> Tuple[List, str, str]:
        """Ends conversation with intelligent profile update and saves to disk"""
        
        result_message = ""
        
        # Check if there's an active lifestyle session to update
        if (self.session_state.current_mode == "lifestyle" and 
            self.session_state.lifestyle_session_length > 0 and 
            len(self.chat_history) > 0):
            
            try:
                print("🔄 User initiated conversation end - updating lifestyle profile...")
                
                # Update profile with LLM analysis and save to disk
                self.lifestyle_profile = self.lifestyle_session_manager.update_profile_after_session(
                    self.lifestyle_profile, 
                    self.chat_history,
                    "User initiated conversation end",
                    save_to_disk=True
                )
                
                result_message = f"""✅ **Conversation ended successfully**

🧠 **Profile Analysis Complete**: Lifestyle profile has been intelligently updated based on your session
💾 **Saved to Disk**: Changes have been permanently saved to lifestyle_profile.json
📊 **Session Summary**: {len([m for m in self.chat_history if m.mode == 'lifestyle'])} lifestyle messages analyzed

Your progress and preferences have been recorded for future sessions."""
                
            except Exception as e:
                print(f"❌ Error updating profile on conversation end: {e}")
                result_message = f"⚠️ **Conversation ended** but there was an error updating your profile: {str(e)}"
        
        else:
            result_message = "✅ **Conversation ended** - No active lifestyle session to update"
        
        # If active test mode, end test session
        if self.test_mode_active and self.testing_interface.current_session:
            self.end_test_session("User ended conversation manually")
        
        # Reset session state
        self.chat_history = []
        self.session_state = SessionState(
            current_mode="none",
            is_active_session=False, 
            session_start_time=None,
            last_controller_decision={},
            lifestyle_session_length=0,
            last_triage_summary="",
            entry_classification={}
        )
        
        return [], self._get_status_info(), result_message


def sync_custom_prompts_from_session(self, session_data):
    """Синхронізує кастомні промпти з SessionData"""
    from prompts import SYSTEM_PROMPT_MAIN_LIFESTYLE
    
    if hasattr(session_data, 'custom_prompts') and session_data.custom_prompts:
        main_lifestyle_prompt = session_data.custom_prompts.get('main_lifestyle')
        if main_lifestyle_prompt and main_lifestyle_prompt != SYSTEM_PROMPT_MAIN_LIFESTYLE:
            self.main_lifestyle_assistant.set_custom_system_prompt(main_lifestyle_prompt)
        else:
            self.main_lifestyle_assistant.reset_to_default_prompt()

def get_current_prompt_info(self) -> Dict[str, str]:
    """Отримує інформацію про поточні промпти"""
    current_prompt = self.main_lifestyle_assistant.get_current_system_prompt()
    is_custom = self.main_lifestyle_assistant.custom_system_prompt is not None
    
    return {
        "is_custom": is_custom,
        "prompt_length": len(current_prompt),
        "prompt_preview": current_prompt[:100] + "..." if len(current_prompt) > 100 else current_prompt,
        "status": "Custom prompt active" if is_custom else "Default prompt active"
    }