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https://github.com/proffesor-for-testing/agentic-qe.git
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0f40bda3ef
## Phase 0: LLM Independence Foundation ### M0.3: HNSW Pattern Store Integration - HNSWPatternAdapter - Bridge between LearningEngine and HNSWPatternStore - LearningEngine HNSW Integration - searchSimilarPatterns(), getHNSWStats() - O(log n) similarity search for pattern matching ### M0.5: Federated Learning - FederatedManager - Cross-agent pattern sharing with consensus - Pattern synchronization across distributed agents ### M0.6: Pattern Curation - PatternCurator - Manual curation workflow with approval/rejection - RuvllmPatternCurator - RuvLLM integration for pattern quality assessment ### RuvllmProvider Enhancements - Session Management (50% latency reduction) - Batch API (4x throughput improvement) - TRM/SONA integration for advanced reasoning - LLMBaselineTracker for performance monitoring - Error tracking in session metrics ### Documentation - Complete agent learning system architecture documentation - HNSW pattern store usage examples - Phase 0 implementation guides 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
128 lines
3.2 KiB
YAML
128 lines
3.2 KiB
YAML
services:
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ruvector:
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image: ruvnet/ruvector:latest
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container_name: agentic-qe-ruvector
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restart: unless-stopped
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ports:
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- "8080:8080" # REST API
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- "9090:9090" # gRPC
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environment:
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# Core Configuration
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RUVECTOR_LEARNING_ENABLED: "true"
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RUVECTOR_EMBEDDING_DIM: "768"
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# HNSW Index Configuration
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RUVECTOR_HNSW_M: "32" # Number of bi-directional links per node
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RUVECTOR_HNSW_EF_CONSTRUCTION: "200" # Size of dynamic candidate list during construction
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RUVECTOR_HNSW_EF_SEARCH: "100" # Size of dynamic candidate list during search
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# Self-Learning Configuration
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RUVECTOR_LORA_RANK: "8" # LoRA rank for efficient fine-tuning
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RUVECTOR_LORA_ALPHA: "16" # LoRA scaling factor
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RUVECTOR_EWC_ENABLED: "true" # Elastic Weight Consolidation for catastrophic forgetting prevention
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RUVECTOR_EWC_LAMBDA: "0.4" # EWC regularization strength
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# Memory Management
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RUVECTOR_MAX_MEMORY_GB: "4" # Maximum memory usage
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RUVECTOR_CACHE_SIZE_MB: "512" # Cache size for embeddings
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# Logging
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RUVECTOR_LOG_LEVEL: "info"
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RUVECTOR_LOG_FORMAT: "json"
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volumes:
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# Persistent data storage
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- ruvector-data:/data
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- ruvector-models:/models
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# Optional: Mount local config
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# - ./config/ruvector.yml:/app/config.yml:ro
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 40s
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# Resource limits (adjust based on your needs)
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deploy:
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resources:
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limits:
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cpus: '2.0'
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memory: 4G
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reservations:
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cpus: '1.0'
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memory: 2G
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networks:
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- agentic-qe-network
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# Development profile overrides
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profiles:
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- production
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# Development configuration with debug settings
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ruvector-dev:
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extends:
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service: ruvector
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container_name: agentic-qe-ruvector-dev
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environment:
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# Override with development settings
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RUVECTOR_LOG_LEVEL: "debug"
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RUVECTOR_LOG_FORMAT: "text"
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RUVECTOR_DEBUG_ENABLED: "true"
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RUVECTOR_PROFILING_ENABLED: "true"
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# More aggressive learning for development
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RUVECTOR_LORA_RANK: "16"
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RUVECTOR_EWC_LAMBDA: "0.3"
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ports:
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- "8080:8080"
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- "9090:9090"
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- "6060:6060" # Profiling endpoint
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volumes:
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- ruvector-data-dev:/data
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- ruvector-models-dev:/models
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# Mount local code for development (if available)
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# - ../ruvector:/app:ro
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profiles:
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- development
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volumes:
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# Production volumes
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ruvector-data:
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driver: local
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driver_opts:
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type: none
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o: bind
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device: ${RUVECTOR_DATA_PATH:-./data/ruvector}
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ruvector-models:
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driver: local
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driver_opts:
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type: none
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o: bind
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device: ${RUVECTOR_MODELS_PATH:-./data/ruvector-models}
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# Development volumes
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ruvector-data-dev:
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driver: local
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ruvector-models-dev:
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driver: local
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networks:
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agentic-qe-network:
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driver: bridge
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ipam:
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config:
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- subnet: 172.28.0.0/16
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