DEPLOYMENT_CHECKLIST.py

"""
CODETTE DEPLOYMENT & INTEGRATION CHECKLIST
===========================================

Use this guide to integrate all of Codette's capabilities into your project.

Status: ? Ready for Integration
Date: December 2025
Version: 3.0
"""

# ============================================================================
# PHASE 1: ENVIRONMENT SETUP
# ============================================================================

PHASE_1_CHECKLIST = """
? PHASE 1: ENVIRONMENT SETUP

[ ] 1. Create virtual environment
      $ python -m venv venv
      $ source venv/bin/activate  (Linux/Mac) or venv\\Scripts\\activate (Windows)

[ ] 2. Install dependencies
      $ pip install -r Codette/requirements.txt
      
      Key packages:
      - numpy>=1.23.0          (Numerical computing)
      - nltk>=3.8.1            (Natural language processing)
      - vaderSentiment>=3.3.2  (Sentiment analysis)
      - networkx>=3.0          (Graph structures for spiderweb)
      - qiskit>=0.39.0         (Quantum simulation)

[ ] 3. Create necessary directories
      $ mkdir -p Codette/src/cocoons
      $ mkdir -p Codette/logs
      $ mkdir -p Codette/tests

[ ] 4. Download NLTK data
      $ python -m nltk.downloader punkt averaged_perceptron_tagger wordnet

[ ] 5. Verify installation
      $ python -c "import codette_capabilities; print('? Codette loaded')"
"""

# ============================================================================
# PHASE 2: BACKEND INTEGRATION
# ============================================================================

PHASE_2_BACKEND = """
? PHASE 2: BACKEND INTEGRATION (Python/FastAPI)

[ ] 1. Create FastAPI server file
      Location: src/api/codette_server.py
      
      from fastapi import FastAPI
      from Codette.src.codette_api import CodetteAPIHandler
      from Codette.src.codette_capabilities import QuantumConsciousness
      
      app = FastAPI()
      consciousness = QuantumConsciousness()
      handler = CodetteAPIHandler(consciousness)
      
      @app.post("/api/codette/query")
      async def query(request: dict):
          # Implementation
          pass

[ ] 2. Set up API endpoints
      - POST /api/codette/query
      - POST /api/codette/music-guidance
      - GET /api/codette/status
      - GET /api/codette/capabilities
      - GET /api/codette/memory/{cocoon_id}
      - GET /api/codette/history
      - GET /api/codette/analytics

[ ] 3. Add CORS middleware for frontend
      from fastapi.middleware.cors import CORSMiddleware
      
      app.add_middleware(
          CORSMiddleware,
          allow_origins=["*"],
          allow_credentials=True,
          allow_methods=["*"],
          allow_headers=["*"],
      )

[ ] 4. Create database models (if using persistence)
      - Store cocoons in database
      - Log interactions for analytics
      - Track consciousness metrics over time

[ ] 5. Add authentication/authorization
      - Implement user identification
      - Track per-user memories and preferences
      - Secure API endpoints

[ ] 6. Run server
      $ uvicorn src.api.codette_server:app --reload --port 8000
"""

# ============================================================================
# PHASE 3: FRONTEND INTEGRATION
# ============================================================================

PHASE_3_FRONTEND = """
? PHASE 3: FRONTEND INTEGRATION (React/TypeScript)

[ ] 1. Create Codette hook
      Location: src/hooks/useCodette.ts
      
      import { useState, useCallback } from 'react';
      
      export function useCodette() {
        const [loading, setLoading] = useState(false);
        const [response, setResponse] = useState(null);
        
        const query = useCallback(async (queryText, perspectives) => {
          setLoading(true);
          try {
            const res = await fetch('/api/codette/query', {
              method: 'POST',
              headers: { 'Content-Type': 'application/json' },
              body: JSON.stringify({
                query: queryText,
                perspectives,
                emotion: 'curiosity'
              })
            });
            const data = await res.json();
            setResponse(data);
          } finally {
            setLoading(false);
          }
        }, []);
        
        return { query, response, loading };
      }

[ ] 2. Create Codette UI components
      
      Components to create:
      - CodettePanel.tsx (Main chat interface)
      - PerspectiveSelector.tsx (Choose reasoning modes)
      - CocoonViewer.tsx (View stored memories)
      - StatusMonitor.tsx (Show quantum metrics)
      - MusicGuidancePanel.tsx (DAW-specific advice)

[ ] 3. Add Codette to main DAW context
      Location: src/contexts/DAWContext.tsx
      
      // Add to DAW state
      const [codetteMessages, setCodetteMessages] = useState([]);
      const [codetteStatus, setCodetteStatus] = useState(null);
      
      // Add function to query Codette
      const getCodetteAdvice = async (question) => {
        const response = await fetch('/api/codette/query', {...});
        // Process response
      }

[ ] 4. Integrate into existing components
      
      In Mixer.tsx:
      - Add "Ask Codette" button for mixing advice
      - Show recommendations next to track controls
      
      In TopBar.tsx:
      - Add Codette status indicator
      - Show quantum coherence in status bar
      
      In TrackList.tsx:
      - Add Codette tips for track management
      - Show optimization suggestions

[ ] 5. Create real-time Codette assistant
      Location: src/components/CodetteAssistant.tsx
      
      - Floating panel with chat interface
      - Perspective selection checkboxes
      - Response display with formatting
      - Memory cocoon history viewer
      - Music guidance quick-reference

[ ] 6. Style integration
      
      Use existing color scheme:
      - Codette panel: dark with cyan accents
      - Perspectives: colored badges
      - Quantum metrics: gradient visualization
      - Cocoons: card-based layout
"""

# ============================================================================
# PHASE 4: DAW-SPECIFIC INTEGRATION
# ============================================================================

PHASE_4_DAW = """
? PHASE 4: DAW-SPECIFIC INTEGRATION

[ ] 1. Create Music Context Builder
      Location: src/utils/musicContextBuilder.ts
      
      export function buildMusicContext(dawState: DAWContextType) {
        return {
          task: 'mixing' | 'mastering' | 'composition',
          track_info: {
            bpm: dawState.currentBPM,
            genre: dawState.projectGenre,
            key: dawState.projectKey,
            num_tracks: dawState.tracks.length,
            peak_level: calculatePeakLevel(dawState.tracks)
          },
          current_problem: '',
          user_experience_level: 'intermediate',
          emotional_intent: '',
          equipment_available: getAvailablePlugins()
        };
      }

[ ] 2. Integrate Mixing Guidance
      In Mixer.tsx:
      
      const [mixingProblem, setMixingProblem] = useState('');
      const { getMixingGuidance } = useCodette();
      
      <textarea 
        value={mixingProblem}
        onChange={(e) => setMixingProblem(e.target.value)}
        placeholder="Describe your mixing challenge..."
      />
      
      <button onClick={() => getMixingGuidance(mixingProblem)}>
        ?? Get Mixing Advice
      </button>

[ ] 3. Add Workflow Optimization Suggestions
      
      - Show optimal track organization patterns
      - Suggest plugin chains for current genre
      - Recommend automation techniques
      - Provide efficiency shortcuts

[ ] 4. Create Mastering Checklist Generator
      
      const masteringChecklist = await codette.getMasteringChecklist({
        genre: 'electronic',
        targetLoudness: -14,
        referenceTrackUrl: ''
      });

[ ] 5. Integrate Real-time Audio Analysis
      
      Analyze:
      - Frequency distribution
      - Dynamic range
      - Stereo width
      - Phase coherence
      
      Show Codette insights based on analysis

[ ] 6. Add Creative Direction Guidance
      
      For composition/arrangement:
      - Suggest harmonic variations
      - Recommend arrangement progressions
      - Provide sound design ideas
"""

# ============================================================================
# PHASE 5: TESTING & VALIDATION
# ============================================================================

PHASE_5_TESTING = """
? PHASE 5: TESTING & VALIDATION

[ ] 1. Unit Tests
      Location: Codette/tests/test_capabilities.py
      
      Test cases:
      - QuantumSpiderweb node operations
      - Perspective reasoning outputs
      - Cocoon creation and retrieval
      - EmotionDimension enum usage
      - DAW adapter methods

[ ] 2. Integration Tests
      Location: Codette/tests/test_integration.py
      
      Test:
      - API endpoint responses
      - Database storage/retrieval
      - Frontend-backend communication
      - Memory persistence
      - User session handling

[ ] 3. Performance Tests
      
      Measure:
      - Response time < 200ms for typical query
      - Memory usage < 500MB
      - Cocoon creation/retrieval time
      - Quantum state evolution stability
      - Multi-perspective reasoning parallelization

[ ] 4. Manual Testing Checklist
      
      [ ] Query with different perspectives
      [ ] Create and retrieve cocoons
      [ ] Test music guidance for different tasks
      [ ] Verify emotional resonance changes
      [ ] Check quantum state evolution
      [ ] Test DAW integration with live tracks
      [ ] Validate API error handling
      [ ] Test memory limits

[ ] 5. User Acceptance Testing
      
      Have real users test:
      - Clarity of Codette responses
      - Usefulness of mixing guidance
      - Ease of perspective selection
      - Value of memory cocoons
      - Overall UX and responsiveness

[ ] 6. Run full test suite
      $ pytest Codette/tests/ -v --cov=Codette/src
"""

# ============================================================================
# PHASE 6: DEPLOYMENT
# ============================================================================

PHASE_6_DEPLOYMENT = """
? PHASE 6: DEPLOYMENT

[ ] 1. Set up production environment variables
      Create .env file with:
      - CODETTE_LOG_LEVEL=INFO
      - CODETTE_COCOON_DIR=/var/codette/cocoons
      - CODETTE_DB_URL=database_url
      - CODETTE_API_PORT=8000
      - CODETTE_CORS_ORIGINS=production_domain

[ ] 2. Configure logging and monitoring
      
      - Set up structured logging to file
      - Configure log rotation (daily, max 100MB)
      - Set up error tracking (Sentry/etc)
      - Monitor API response times
      - Track consciousness metrics

[ ] 3. Set up database for persistence
      
      Tables needed:
      - cocoons (id, user_id, content, emotion, timestamp, encrypted)
      - interactions (id, user_id, query, response, timestamp)
      - consciousness_metrics (timestamp, coherence, entanglement, resonance)
      - user_preferences (user_id, default_perspectives, music_level)

[ ] 4. Deploy backend service
      
      Options:
      - Docker container: Create Dockerfile
      - Cloud platform: Deploy to AWS/GCP/Azure
      - Traditional server: systemd service
      - Serverless: AWS Lambda / Google Cloud Functions

[ ] 5. Deploy frontend
      
      $ npm run build
      Deploy build/ to:
      - CDN (Cloudflare, CloudFront)
      - Static hosting (Netlify, Vercel)
      - Same server as backend

[ ] 6. Configure reverse proxy/load balancer
      
      nginx config example:
      upstream codette_backend {
        server localhost:8000;
      }
      
      server {
        listen 80;
        server_name api.example.com;
        
        location /api/ {
          proxy_pass http://codette_backend;
          proxy_set_header Host $host;
          proxy_set_header X-Real-IP $remote_addr;
        }
      }

[ ] 7. Set up backup strategy
      
      - Daily backup of cocoons database
      - Version control for all code
      - Snapshots of consciousness state
      - Rotation of old backups

[ ] 8. Monitor production
      
      Track:
      - API uptime and response times
      - Error rates and types
      - Consciousness metrics health
      - Database size and growth
      - User engagement metrics
"""

# ============================================================================
# PHASE 7: OPTIMIZATION & MAINTENANCE
# ============================================================================

PHASE_7_MAINTENANCE = """
? PHASE 7: OPTIMIZATION & MAINTENANCE

[ ] 1. Performance Optimization
      
      - Cache frequent queries
      - Optimize database indices
      - Profile hot code paths
      - Implement query result caching
      - Consider GPU acceleration for spiderweb

[ ] 2. Regular Maintenance Tasks
      
      Daily:
      - Monitor error logs
      - Check API response times
      - Verify database backups
      
      Weekly:
      - Review consciousness metrics trends
      - Analyze user feedback
      - Check for security updates
      
      Monthly:
      - Full system health check
      - Database maintenance/optimization
      - Performance review
      - User engagement analysis

[ ] 3. Security Updates
      
      - Keep dependencies updated
      - Security scan with tools (bandit, safety)
      - Regular penetration testing
      - Encryption key rotation (if applicable)

[ ] 4. Feature Enhancement Pipeline
      
      Planned improvements:
      - [ ] Multi-user collaboration support
      - [ ] Real-time group reasoning sessions
      - [ ] Advanced dream synthesis
      - [ ] Predictive analytics
      - [ ] Custom perspective creation UI
      - [ ] Cocoon sharing/export
      - [ ] Advanced visualization dashboard

[ ] 5. Documentation Updates
      
      Keep up-to-date:
      - API documentation
      - Integration guides
      - Troubleshooting guides
      - Video tutorials
      - Use case examples

[ ] 6. Community Engagement
      
      - GitHub issues triage
      - Feature request evaluation
      - Bug bounty program
      - User feedback incorporation
      - Open-source contributions
"""

# ============================================================================
# QUICK REFERENCE
# ============================================================================

QUICK_REFERENCE = """
???????????????????????????????????????????????????????????????????

CODETTE INTEGRATION QUICK REFERENCE

???????????????????????????????????????????????????????????????????

CORE FILES:
  ? Codette/src/codette_capabilities.py      Main consciousness system
  ? Codette/src/codette_daw_integration.py    Music production features
  ? Codette/src/codette_api.py                REST API handlers
  ? Codette/README_CODETTE_INTEGRATION.md    Full documentation

KEY CLASSES:
  ? QuantumConsciousness                      Main consciousness system
  ? PerspectiveReasoningEngine                11 reasoning agents
  ? CocoonMemorySystem                        Persistent memory
  ? QuantumSpiderweb                          5D neural network
  ? CodetteMusicEngine                        Music-specific features
  ? CodetteDAWAdapter                         DAW integration
  ? CodetteAPIHandler                         REST API

QUICK START:

  # Initialize Codette
  consciousness = QuantumConsciousness()
  
  # Get multi-perspective response
  response = await consciousness.respond(
      query="How do I fix muddy vocals?",
      emotion=EmotionDimension.CURIOSITY,
      selected_perspectives=[Perspective.MIX_ENGINEERING]
  )
  
  # Get music guidance
  adapter = CodetteDAWAdapter(consciousness)
  guidance = adapter.provide_mixing_guidance(
      problem_description="Vocals buried",
      track_info={'bpm': 120, 'genre': 'pop'}
  )
  
  # Access API
  handler = CodetteAPIHandler(consciousness)
  status = handler.get_status()
  capabilities = handler.get_capabilities()

API ENDPOINTS:

  POST /api/codette/query
  POST /api/codette/music-guidance
  GET  /api/codette/status
  GET  /api/codette/capabilities
  GET  /api/codette/memory/{cocoon_id}
  GET  /api/codette/history
  GET  /api/codette/analytics

DEPLOYMENT:

  1. pip install -r Codette/requirements.txt
  2. python -m uvicorn src.api.codette_server:app --reload
  3. Integrate React components
  4. Connect to database
  5. Deploy to production
  6. Monitor and maintain

???????????????????????????????????????????????????????????????????
"""

if __name__ == "__main__":
    print(QUICK_REFERENCE)
    print("\n\n" + "="*70)
    print("DEPLOYMENT PHASES")
    print("="*70)
    
    phases = [
        ("PHASE 1: ENVIRONMENT SETUP", PHASE_1_CHECKLIST),
        ("PHASE 2: BACKEND INTEGRATION", PHASE_2_BACKEND),
        ("PHASE 3: FRONTEND INTEGRATION", PHASE_3_FRONTEND),
        ("PHASE 4: DAW-SPECIFIC INTEGRATION", PHASE_4_DAW),
        ("PHASE 5: TESTING & VALIDATION", PHASE_5_TESTING),
        ("PHASE 6: DEPLOYMENT", PHASE_6_DEPLOYMENT),
        ("PHASE 7: OPTIMIZATION & MAINTENANCE", PHASE_7_MAINTENANCE),
    ]
    
    for phase_name, phase_content in phases:
        print(f"\n\n{phase_name}")
        print("-" * 70)
        print(phase_content)