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)