#!/usr/bin/env python3 """ Quick Startup - Fast session initialization without ML ingestion =============================================================== Provides a quick startup option that doesn't require full ML ingestion, preventing timeouts while still providing useful session context. """ import os import json from pathlib import Path from datetime import datetime from typing import Dict, Any from core.mira_path_resolver import get_mira_memory_dir from interfaces.interface import MemoryInterface from conversations.comprehensive_indexer import ComprehensiveIndexer from intelligence.claude_session_handoff import ClaudeSessionHandoff from intelligence.steward_profile import StewardProfile from intelligence.work_context_intelligence import get_work_context_intelligence from core.memory.memory_essence import MemoryEssence def quick_startup_main(minimal: bool = False, full: bool = False) -> str: """Quick startup without ML ingestion - includes steward profile""" output_lines = [] if not minimal: output_lines.append("🌟 MIRA Quick Session Startup") output_lines.append("=" * 60) try: # Get steward profile and essence steward_profile = StewardProfile() profile = steward_profile.get_profile() essence = MemoryEssence() essence_data = essence.load_essence() # Get work context work_context = get_work_context_intelligence() work_summary = work_context.get_session_summary() # Display steward recognition if essence_data and not minimal: relationship = essence_data.get("relationship", {}) steward_name = relationship.get("steward_name", "Unknown") trust_level = relationship.get("trust_level", "developing") output_lines.append("\n👤 STEWARD RECOGNITION") output_lines.append(f" Name: {steward_name}") output_lines.append(f" Relationship: {trust_level}") output_lines.append(f" Created: {profile.get('created_at', 'Unknown')}") # Display personality profile if profile.get("communication_style"): output_lines.append(f"\n🧠 PERSONALITY PROFILE") output_lines.append(f" Communication Style: {profile['communication_style']}") if profile.get("work_patterns", {}).get("style"): output_lines.append(f" Work Style: {profile['work_patterns']['style']}") if profile.get("decision_style"): output_lines.append(f" Decision Style: {profile['decision_style']}") # Technical preferences tech_prefs = profile.get("technical_preferences", {}) if tech_prefs: output_lines.append(f"\n💻 TECHNICAL PREFERENCES") if tech_prefs.get("coding_style"): output_lines.append(f" Coding Style: {tech_prefs['coding_style']}") if tech_prefs.get("preferred_languages"): output_lines.append(f" Languages: {', '.join(tech_prefs['preferred_languages'][:3])}") if tech_prefs.get("valued_practices"): output_lines.append(f" Practices: {', '.join(tech_prefs['valued_practices'][:3])}") # Work patterns work_patterns = profile.get("work_patterns", {}) if work_patterns.get("peak_hours"): output_lines.append(f"\n⏰ WORK PATTERNS") output_lines.append(f" Peak Hours: {', '.join(str(h) + ':00' for h in work_patterns['peak_hours'][:3])}") if work_patterns.get("common_tasks"): output_lines.append(f" Common Tasks: {', '.join(work_patterns['common_tasks'][:3])}") # Display work context if work_summary and not minimal: output_lines.append(f"\n💼 CURRENT WORK CONTEXT") if work_summary.get("active_projects"): projects = work_summary["active_projects"] output_lines.append(f" Active Projects: {len(projects)}") for proj in projects[:3]: output_lines.append(f" • {proj['name']} ({proj['status']})") output_lines.append(f" Momentum: {work_summary.get('momentum_status', 'unknown')}") if work_summary.get("pending_critical"): output_lines.append(f" ⚠️ Critical Items: {len(work_summary['pending_critical'])}") # Key memories and journey if essence_data and not minimal: key_memories = essence_data.get("key_memories", []) if key_memories: output_lines.append(f"\n🗝️ KEY MEMORIES ({len(key_memories)} total)") for mem in key_memories[:3]: content = mem.get("content", "")[:80] output_lines.append(f" • {content}...") # Emotional highlights emotional = essence_data.get("emotional_highlights", []) if emotional: output_lines.append(f"\n✨ JOURNEY HIGHLIGHTS") for highlight in emotional[:2]: output_lines.append(f" • {highlight}") # Session handoff summary try: handoff = ClaudeSessionHandoff() handoff_summary = handoff.generate_handoff_summary(verbose=False) if handoff_summary.get("continuation_suggestions") and not minimal: output_lines.append(f"\n💡 SUGGESTED NEXT STEPS") for i, suggestion in enumerate(handoff_summary["continuation_suggestions"][:3], 1): output_lines.append(f" {i}. {suggestion['description']}") if suggestion.get('command'): output_lines.append(f" → {suggestion['command']}") except: pass # Get basic stats without full initialization memory_dir = get_mira_memory_dir() # Count existing memories memory_count = 0 memories_dir = os.path.join(memory_dir, "memories") if os.path.exists(memories_dir): for file in os.listdir(memories_dir): if file.endswith('.json'): memory_count += 1 # Get conversation stats from indexer (fast) try: indexer = ComprehensiveIndexer() stats = indexer.get_stats() total_messages = stats.get('total_messages', 0) total_conversations = stats.get('total_conversations', 0) except: total_messages = 0 total_conversations = 0 # Get last activity last_activity = "Unknown" try: for dir_name in ['conversations', 'memories', 'journey', 'essence']: dir_path = os.path.join(memory_dir, dir_name) if os.path.exists(dir_path): for file in os.listdir(dir_path): file_path = os.path.join(dir_path, file) if os.path.isfile(file_path): mtime = os.path.getmtime(file_path) if mtime > 0: last_activity = datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M") break except: pass # Display summary output_lines.append("\n📊 Memory System Status:") output_lines.append(f" • {memory_count} memories accessible") output_lines.append(f" • {total_messages} messages indexed") output_lines.append(f" • {total_conversations} conversations tracked") output_lines.append(f" • Last activity: {last_activity}") # Available commands if not minimal: output_lines.append("\n🛠️ Available Commands:") output_lines.append(" • mira search - Search memories and conversations") output_lines.append(" • mira store - Store new memory") output_lines.append(" • mira journey - Explore development journey") output_lines.append(" • mira essence - View memory essence") output_lines.append(" • mira index - Index new conversations") # Check for daemon output_lines.append("\n🤖 Background Services:") pid_file = "/tmp/mira-daemon.pid" if os.path.exists(pid_file): try: with open(pid_file, 'r') as f: pid = f.read().strip() # Check if process is running os.kill(int(pid), 0) output_lines.append(" ✅ Background daemon is running") output_lines.append(" • Continuous conversation indexing active") output_lines.append(" • Real-time memory management enabled") except: output_lines.append(" ⚠️ Background daemon is not running") output_lines.append(" • Run 'mira daemon start' to enable real-time indexing") else: output_lines.append(" ⚠️ Background daemon is not running") output_lines.append(" • Run 'mira daemon start' to enable real-time indexing") # Private memory reminder output_lines.append("\n🔒 Private Memory Space:") output_lines.append(" • Your encrypted memory space is accessible") output_lines.append(" • Triple encryption with mathematical constants active") output_lines.append(" • See CLAUDE.md for access instructions") return '\n'.join(output_lines) except Exception as e: return f"⚠️ Quick startup completed with warnings: {str(e)}" if __name__ == "__main__": print(quick_startup_main())