M.I.M.I.R - Multi-agent Intelligent Memory & Insight Repository

services: # Neo4j (Legacy - replaced by NornicDB) # neo4j: # image: neo4j:5.15-community # container_name: neo4j_db # ports: # - "7475:7474" # HTTP Browser UI # - "7688:7687" # Bolt protocol # volumes: # - ./data/neo4j:/data # - ./logs/neo4j:/logs # - ./data/neo4j/import:/var/lib/neo4j/import # environment: # - NEO4J_AUTH=neo4j/${NEO4J_PASSWORD:-password} # - NEO4J_dbms_memory_pagecache_size=512M # - NEO4J_dbms_memory_heap_initial__size=512M # - NEO4J_dbms_memory_heap_max__size=2G # - NEO4J_PLUGINS=["apoc"] # restart: unless-stopped # healthcheck: # test: ["CMD-SHELL", "cypher-shell -u neo4j -p $${NEO4J_PASSWORD:-password} 'RETURN 1' || exit 1"] # interval: 30s # timeout: 10s # retries: 3 # start_period: 40s # networks: # - mcp_network nornicdb: image: timothyswt/nornicdb-amd64-cuda-bge-heimdall:v1.0.0 container_name: nornicdb ports: - "7474:7474" # HTTP API & Browser UI - "7687:7687" # Bolt protocol (Neo4j compatible) volumes: - ./data/movies-test:/data - ./data/movies-test/export:/data/export # For loading Mimir exports environment: - NORNICDB_DATA_DIR=/data - NORNICDB_HTTP_PORT=7474 - NORNICDB_BOLT_PORT=7687 # Embedding configuration - llama.cpp OpenAI-compatible API - NORNICDB_EMBEDDING_PROVIDER=local - NORNICDB_MODELS_DIR=/app/models # # - NORNICDB_EMBEDDING_API_URL=http://llama-server:8080 # # - NORNICDB_EMBEDDING_API_KEY=not-needed # # - NORNICDB_EMBEDDING_MODEL=bge-m3 # # Use /app/models for bundled models (bge-m3 + qwen heimdall) # # Volume mount ./data/nornicdb:/data shadows /data/models, so use /app/models # # - NORNICDB_MODELS_DIR=/app/models # # # Authentication (disabled by default for dev) # - NORNICDB_NO_AUTH=${NORNICDB_NO_AUTH:-true} # - NORNICDB_ADMIN_PASSWORD=${NEO4J_PASSWORD:-password} # - NORNICDB_TOPOLOGY_AUTO_INTEGRATION_ENABLED=true # # Load export data on startup (disabled - starting fresh) # - NORNICDB_LOAD_EXPORT= # # Badger memory tuning (reduce memory footprint) # - GOGC=50 # - NORNICDB_GPU_ENABLED=${NORNICDB_GPU_ENABLED:-true} # - NORNICDB_GPU_DEVICE_ID=${NORNICDB_GPU_DEVICE_ID:-0} # - NORNICDB_EMBEDDING_CACHE_SIZE=0 restart: unless-stopped healthcheck: test: ["CMD-SHELL", "wget --spider -q http://localhost:7474/health || exit 1"] interval: 30s timeout: 10s retries: 3 start_period: 10s networks: - mcp_network # deploy: # resources: # reservations: # devices: # - driver: nvidia # count: 1 # capabilities: [gpu, compute, utility] # copilot-api: # image: timothyswt/copilot-api:latest # container_name: copilot_api_server # ports: # - "4141:4141" # Fixed: copilot-api listens on 4141, not 3000 # volumes: # - ./copilot-data:/root/.local/share/copilot-api # Persist GitHub token # environment: # - NODE_ENV=production # # Remove PORT=3000, the app uses 4141 by default # restart: unless-stopped # healthcheck: # # Use CMD-SHELL so shell operators (||) work and allow a proper HTTP probe # test: ["CMD-SHELL", "wget --spider -q http://localhost:4141/ || exit 1"] # interval: 30s # timeout: 10s # retries: 5 # start_period: 15s # networks: # - mcp_network # Ollama (Legacy - kept for reference, can be removed) # ollama: # build: # context: ./docker/ollama # dockerfile: Dockerfile # args: # - EMBEDDING_MODEL=${MIMIR_EMBEDDINGS_MODEL:-bge-m3} # tags: # - mimir-ollama:${VERSION:-1.0.0} # - mimir-ollama:latest # image: mimir-ollama:${VERSION:-1.0.0} # container_name: ollama_server # ports: # - "11434:11434" # volumes: # - type: bind # source: ollama_models # target: /root/.ollama # environment: # - OLLAMA_HOST=0.0.0.0:11434 # - OLLAMA_ORIGINS=* # restart: unless-stopped # healthcheck: # test: ["CMD", "ollama", "list"] # interval: 10s # timeout: 5s # retries: 5 # start_period: 30s # networks: # - mcp_network # deploy: # resources: # reservations: # devices: # - driver: nvidia # count: 1 # capabilities: [gpu] # llama.cpp server - OpenAI-compatible embeddings # llama-server: # image: timothyswt/llama-cpp-server-amd64-mxbai-cuda:latest # container_name: llama_server # ports: # - "11434:8080" # External 11434 -> Internal 8080 (llama.cpp default) # # Note: Model is bundled in the image (bge-m3, 1024 dims) # # No volumes needed unless you want to add additional models # restart: unless-stopped # healthcheck: # test: ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"] # interval: 30s # timeout: 10s # retries: 3 # start_period: 30s # networks: # - mcp_network # deploy: # resources: # reservations: # devices: # - driver: nvidia # count: 1 # capabilities: [gpu] # llama.cpp Vision Server - 2B model (faster, lower memory) # Qwen2.5-VL 2B with vision understanding and CUDA acceleration # Build with: npm run llama:build-qwen-2b-cuda # For use without cuda `image: timothyswt/llama-cpp-server-amd64-qwen-vl-2b:latest` # # llama-vl-server-2b: # image: timothyswt/llama-cpp-server-amd64-qwen-vl-2b-cuda:latest # container_name: llama_server_vision_2b # ports: # - "8081:8080" # Vision 2B API endpoint # restart: unless-stopped # healthcheck: # test: ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"] # interval: 30s # timeout: 10s # retries: 3 # start_period: 60s # Vision models take longer to load # networks: # - mcp_network # deploy: # resources: # limits: # memory: 8G # 2B model + vision projector # reservations: # memory: 4G # devices: # - driver: nvidia # count: 1 # capabilities: [gpu] # llama.cpp Vision Server - 7B model (higher quality, more memory) # Qwen2.5-VL 7B with vision understanding and CUDA acceleration # Build with: npm run llama:build-qwen-7b-cuda # For use without cuda `image: timothyswt/llama-cpp-server-amd64-qwen-vl-7b:latest` # # llama-vl-server-7b: # image: timothyswt/llama-cpp-server-amd64-qwen-vl-7b-cuda:latest # container_name: llama_server_vision_7b # ports: # - "8082:8080" # Vision 7B API endpoint # restart: unless-stopped # healthcheck: # test: ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"] # interval: 30s # timeout: 10s # retries: 3 # start_period: 90s # Larger models take even longer # networks: # - mcp_network # deploy: # resources: # limits: # memory: 16G # 7B models need more RAM # reservations: # memory: 8G # devices: # - driver: nvidia # count: 1 # capabilities: [gpu] # mimir-server: # build: # context: . # dockerfile: Dockerfile # tags: # - timothyswt/mimir:latest # image: timothyswt/mimir:latest # container_name: mimir_server # environment: # # Database Configuration # - NEO4J_URI=bolt://nornicdb:7687 # - NEO4J_USER=admin # - NEO4J_PASSWORD=${NEO4J_PASSWORD:-admin} # # Server Configuration # - NODE_ENV=production # - PORT=3000 # # - NODE_TLS_REJECT_UNAUTHORIZED=${NODE_TLS_REJECT_UNAUTHORIZED:-1} # # Workspace Configuration # - WORKSPACE_ROOT=/workspace # - HOST_WORKSPACE_ROOT=${HOST_WORKSPACE_ROOT} # Pass through from host # - HOST_HOME=${HOME} # Host's home directory for expanding ~ in HOST_WORKSPACE_ROOT # # LLM API Configuration # - MIMIR_DEFAULT_PROVIDER=${MIMIR_DEFAULT_PROVIDER:-copilot} # - MIMIR_LLM_API=${MIMIR_LLM_API:-http://copilot-api:4141} # - MIMIR_LLM_API_PATH=${MIMIR_LLM_API_PATH:-/v1/chat/completions} # - MIMIR_LLM_API_MODELS_PATH=${MIMIR_LLM_API_MODELS_PATH:-/v1/models} # - MIMIR_LLM_API_KEY=${MIMIR_LLM_API_KEY:-dummy-key} # # PCTX Integration (Code Mode for 90-98% token reduction) # - PCTX_URL=${PCTX_URL:-http://host.docker.internal:8080} # - PCTX_ENABLED=${PCTX_ENABLED:-false} # # Provider and Model Configuration (100% dynamic - no config file needed) # - MIMIR_DEFAULT_MODEL=${MIMIR_DEFAULT_MODEL:-gpt-4.1} # # Per-Agent Model Configuration (optional overrides) # - MIMIR_PM_MODEL=${MIMIR_PM_MODEL:-} # - MIMIR_WORKER_MODEL=${MIMIR_WORKER_MODEL:-} # - MIMIR_QC_MODEL=${MIMIR_QC_MODEL:-} # # Context Window Configuration # - MIMIR_DEFAULT_CONTEXT_WINDOW=${MIMIR_DEFAULT_CONTEXT_WINDOW:-128000} # # Embeddings API Configuration # - MIMIR_EMBEDDINGS_PROVIDER=${MIMIR_EMBEDDINGS_PROVIDER:-openai} # - MIMIR_EMBEDDINGS_API=${MIMIR_EMBEDDINGS_API:-http://llama-server:8080} # - MIMIR_EMBEDDINGS_API_PATH=${MIMIR_EMBEDDINGS_API_PATH:-/v1/embeddings} # - MIMIR_EMBEDDINGS_API_MODELS_PATH=${MIMIR_EMBEDDINGS_API_MODELS_PATH:-/v1/models} # - MIMIR_EMBEDDINGS_API_KEY=${MIMIR_EMBEDDINGS_API_KEY:-dummy-key} # # Embeddings Configuration # - MIMIR_EMBEDDINGS_ENABLED=${MIMIR_EMBEDDINGS_ENABLED:-true} # - MIMIR_EMBEDDINGS_MODEL=${MIMIR_EMBEDDINGS_MODEL:-bge-m3} # - MIMIR_EMBEDDINGS_DIMENSIONS=${MIMIR_EMBEDDINGS_DIMENSIONS:-1024} # - MIMIR_EMBEDDINGS_CHUNK_SIZE=${MIMIR_EMBEDDINGS_CHUNK_SIZE:-768} # - MIMIR_EMBEDDINGS_CHUNK_OVERLAP=${MIMIR_EMBEDDINGS_CHUNK_OVERLAP:-100} # - MIMIR_EMBEDDINGS_DELAY_MS=${MIMIR_EMBEDDINGS_DELAY_MS:-0} # - MIMIR_EMBEDDINGS_MAX_RETRIES=${MIMIR_EMBEDDINGS_MAX_RETRIES:-3} # # Image Embeddings Control (disabled by default for safety) # - MIMIR_EMBEDDINGS_IMAGES=${MIMIR_EMBEDDINGS_IMAGES:-false} # Default: disabled # - MIMIR_EMBEDDINGS_IMAGES_DESCRIBE_MODE=${MIMIR_EMBEDDINGS_IMAGES_DESCRIBE_MODE:-true} # Default: VL description mode # # Qwen2.5-VL Configuration (for llama.cpp server) # - MIMIR_EMBEDDINGS_VL_PROVIDER=${MIMIR_EMBEDDINGS_VL_PROVIDER:-llama.cpp} # - MIMIR_EMBEDDINGS_VL_API=${MIMIR_EMBEDDINGS_VL_API:-http://llama-vl-server-2b:8080} # - MIMIR_EMBEDDINGS_VL_API_PATH=${MIMIR_EMBEDDINGS_VL_API_PATH:-/v1/chat/completions} # - MIMIR_EMBEDDINGS_VL_API_KEY=${MIMIR_EMBEDDINGS_VL_API_KEY:-dummy-key} # - MIMIR_EMBEDDINGS_VL_MODEL=${MIMIR_EMBEDDINGS_VL_MODEL:-qwen2.5-vl} # - MIMIR_EMBEDDINGS_VL_CONTEXT_SIZE=${MIMIR_EMBEDDINGS_VL_CONTEXT_SIZE:-131072} # 128K tokens (7b/72b) # - MIMIR_EMBEDDINGS_VL_MAX_TOKENS=${MIMIR_EMBEDDINGS_VL_MAX_TOKENS:-2048} # Max description length # - MIMIR_EMBEDDINGS_VL_TEMPERATURE=${MIMIR_EMBEDDINGS_VL_TEMPERATURE:-0.7} # - MIMIR_EMBEDDINGS_VL_DIMENSIONS=${MIMIR_EMBEDDINGS_VL_DIMENSIONS:-768} # Falls back to text model dims # - MIMIR_EMBEDDINGS_VL_TIMEOUT=${MIMIR_EMBEDDINGS_VL_TIMEOUT:-180000} # 3 minutes (VL processing is slow) # # Indexing Configuration # - MIMIR_INDEXING_THREADS=${MIMIR_INDEXING_THREADS:-1} # # Feature Flags # - MIMIR_FEATURE_PM_MODEL_SUGGESTIONS=${MIMIR_FEATURE_PM_MODEL_SUGGESTIONS:-true} # - MIMIR_AUTO_INDEX_DOCS=${MIMIR_AUTO_INDEX_DOCS:-true} # # Security Configuration # - MIMIR_ENABLE_SECURITY=${MIMIR_ENABLE_SECURITY:-false} # - MIMIR_DEV_USER_ADMIN=${MIMIR_DEV_USER_ADMIN} # - MIMIR_DEV_USER_DEVELOPER=${MIMIR_DEV_USER_DEVELOPER} # - MIMIR_DEV_USER_ANALYST=${MIMIR_DEV_USER_ANALYST} # - MIMIR_DEV_USER_VIEWER=${MIMIR_DEV_USER_VIEWER} # - MIMIR_JWT_SECRET=${MIMIR_JWT_SECRET} # # OAuth Configuration (explicit endpoint URLs - provider-specific) # - MIMIR_AUTH_PROVIDER=${MIMIR_AUTH_PROVIDER} # - MIMIR_OAUTH_AUTHORIZATION_URL=${MIMIR_OAUTH_AUTHORIZATION_URL} # Full authorization endpoint URL # - MIMIR_OAUTH_TOKEN_URL=${MIMIR_OAUTH_TOKEN_URL} # Full token endpoint URL # - MIMIR_OAUTH_USERINFO_URL=${MIMIR_OAUTH_USERINFO_URL} # Full userinfo endpoint URL # - MIMIR_OAUTH_CLIENT_ID=${MIMIR_OAUTH_CLIENT_ID} # - MIMIR_OAUTH_CLIENT_SECRET=${MIMIR_OAUTH_CLIENT_SECRET} # - MIMIR_OAUTH_CALLBACK_URL=${MIMIR_OAUTH_CALLBACK_URL} # - MIMIR_OAUTH_ALLOW_HTTP=${MIMIR_OAUTH_ALLOW_HTTP} # # Advanced Configuration # - MIMIR_PARALLEL_EXECUTION=${MIMIR_PARALLEL_EXECUTION:-false} # - MIMIR_INSTALL_DIR=${MIMIR_INSTALL_DIR:-/app} # - MIMIR_AGENTS_DIR=${MIMIR_AGENTS_DIR:-/app/docs/agents} # volumes: # - ./data:/app/data # - ./logs:/app/logs # - ${HOST_WORKSPACE_ROOT:-~/src}:${WORKSPACE_ROOT:-/workspace} # ports: # - "9042:3000" # healthcheck: # test: ["CMD", "node", "-e", "require('http').get('http://localhost:3000/health', (res) => process.exit(res.statusCode === 200 ? 0 : 1)).on('error', () => process.exit(1))"] # interval: 30s # timeout: 10s # retries: 3 # start_period: 10s # depends_on: # nornicdb: # condition: service_healthy # # copilot-api: # # condition: service_healthy # # llama.cpp server for embeddings # # llama-server: # # condition: service_healthy # # llama.cpp server for image embeddings must set # # llama-vl-server: # # condition: service_healthy # networks: # - mcp_network networks: mcp_network: driver: bridge