""" 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();