80 lines
3.2 KiB
Text
Executable file
80 lines
3.2 KiB
Text
Executable file
# =============================================================================
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# CONVERSATION ASSISTANT: Environment Configuration
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# =============================================================================
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# Copy this file to .env and customize for your environment.
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# All values shown are development defaults.
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# =============================================================================
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# -----------------------------------------------------------------------------
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# DATABASE: PostgreSQL
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# -----------------------------------------------------------------------------
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DB_HOST=localhost
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DB_PORT=25433
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DB_USER=postgres
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DB_PASSWORD=devpassword
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DB_NAME=conversation_assistant
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# Use docker-compose to start: docker-compose up -d postgres
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# -----------------------------------------------------------------------------
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# CACHE: Redis
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# -----------------------------------------------------------------------------
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REDIS_URL=redis://localhost:26380
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CACHE_TTL=3600
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# Use docker-compose to start: docker-compose up -d redis
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# -----------------------------------------------------------------------------
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# SERVER: NestJS API
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# -----------------------------------------------------------------------------
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PORT=3100
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NODE_ENV=development
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CORS_ORIGIN=http://localhost:5173
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# JWT secret for device authentication
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JWT_SECRET=your-jwt-secret-change-in-production
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# -----------------------------------------------------------------------------
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# DATA STORAGE: Persistent storage on bigdisk
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# -----------------------------------------------------------------------------
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# Attachments (images, audio, etc. from iMessage sync)
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ATTACHMENTS_DIR=/mnt/bigdisk/_/lilith-platform/features/conversation-assistant/attachments
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# ML training outputs (fine-tuned models specific to this project)
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ML_SERVICE_TRAINING_OUTPUT_DIR=/mnt/bigdisk/_/lilith-platform/features/conversation-assistant/training-outputs
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# -----------------------------------------------------------------------------
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# ML SERVICE: Python FastAPI
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# -----------------------------------------------------------------------------
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ML_SERVICE_URL=http://localhost:8100
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# Model configuration
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ML_SERVICE_MODEL_ID=ministral-3b-instruct
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ML_SERVICE_GPU_LAYERS=-1
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ML_SERVICE_CONTEXT_SIZE=4096
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# Redis for ML service (same instance)
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ML_SERVICE_REDIS_URL=redis://localhost:26380
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ML_SERVICE_REDIS_ENABLED=true
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ML_SERVICE_REDIS_CACHE_TTL=3600
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# -----------------------------------------------------------------------------
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# DEVELOPMENT NOTES
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# -----------------------------------------------------------------------------
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#
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# Quick Start:
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# 1. Start databases: docker-compose up -d
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# 2. Start ML service: cd ml-service && pip install -e . && python -m uvicorn src.main:app --port 8100
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# 3. Start server: cd server && npm install && npm run start:dev
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# 4. Start frontend: cd frontend && npm install && npm run dev
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#
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# ML Package Installation:
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# pip install -e ~/Code/@packages/@ml/@tools/model-loader
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# pip install tqftw-fastapi-service-base --extra-index-url https://forge.nasty.sh/api/packages/lilith/pypi/simple/
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#
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# Production:
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# - Change all passwords
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# - Set NODE_ENV=production
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# - Use infrastructure/docker/docker-compose.databases.yml for shared Redis
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#
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# =============================================================================
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