Cleanup

.env.example

@@ -1,29 +1,8 @@
-# ============================================
-# OpenMemory - Environment Configuration
-# ============================================
+# OpenMemory JS server environment
 
-# --------------------------------------------
-# Backend Server Settings
-# --------------------------------------------
 OM_PORT=8080
-
-# API Authentication (IMPORTANT: Set a strong API key for production!)
-# Generate a secure key: openssl rand -base64 32
-# Leave empty to disable authentication (development only)
-OM_API_KEY=your-secret-api-key-here
-
-# Rate Limiting
-# Enable rate limiting to prevent abuse
-OM_RATE_LIMIT_ENABLED=true
-# Time window in milliseconds (default: 60000 = 1 minute)
-OM_RATE_LIMIT_WINDOW_MS=60000
-# Maximum requests per window (default: 100 requests per minute)
-OM_RATE_LIMIT_MAX_REQUESTS=100
-
-# Optional: Log all authenticated requests (set to 'true' for debugging)
+OM_API_KEY=
 OM_LOG_AUTH=false
-
-# Telemetry (true by default, set to false to opt out of anonymous ping)
 OM_TELEMETRY=true
 
 # Server Mode
@@ -44,198 +23,58 @@ OM_PG_USER=postgres
 OM_PG_PASSWORD=postgres
 OM_PG_SCHEMA=public
 OM_PG_TABLE=openmemory_memories
-OM_PG_SSL=disable # disable | require
+OM_PG_SSL=disable
 
-# --------------------------------------------
-# Vector Store Backend
-# --------------------------------------------
-# Vector storage follows OM_METADATA_BACKEND (sqlite/postgres) unless set to 'valkey'
-# Options: valkey (Redis-compatible), or leave unset to follow OM_METADATA_BACKEND
-# Note: When using postgres metadata backend, vectors are stored in the same database
-OM_VECTOR_BACKEND=sqlite
-# Table name for vectors (configurable, will be created if it doesn't exist)
-OM_VECTOR_TABLE=vectors
-OM_WEAVIATE_URL=
-OM_WEAVIATE_API_KEY=
-OM_WEAVIATE_CLASS=OpenMemory
+# Vector storage
+OM_VECTOR_BACKEND=postgres
+OM_VECTOR_TABLE=openmemory_vectors
 
-# --------------------------------------------
-# Embeddings Configuration
-# --------------------------------------------
-# Available providers: openai, gemini, aws, ollama, local, synthetic
-# Embedding models per sector can be configured in models.yaml
-#
-# NOTE: Your selected TIER (fast/smart/deep) affects how embeddings work:
-# • FAST tier: Uses synthetic embeddings regardless of OM_EMBEDDINGS setting
-# • SMART tier: Combines synthetic + compressed semantic from your chosen provider
-# • DEEP tier: Uses full embeddings from your chosen provider
-#
-# For SMART/DEEP tiers, set your preferred provider:
+# Embeddings
 OM_EMBEDDINGS=openai
-
-# Fallback chain: comma-separated list of providers to try if primary fails
-# Each provider exhausts its own retry logic before moving to the next
-# Example: OM_EMBEDDING_FALLBACK=ollama,synthetic
-# Default: synthetic (always works as final fallback)
 OM_EMBEDDING_FALLBACK=synthetic
-
-# Vector dimension (auto-adjusted by tier, but can be overridden)
-# • FAST: 256-dim  • SMART: 384-dim  • DEEP: 1536-dim
-# OM_VEC_DIM=1536
-
-# Embedding Mode
-# simple   = 1 unified batch call for all sectors (faster, rate-limit safe, recommended)
-# advanced = 5 separate calls, one per sector (higher precision, more API calls)
 OM_EMBED_MODE=simple
-
-# Advanced Mode Options (only used when OM_EMBED_MODE=advanced)
-# Enable parallel embedding (not recommended for Gemini due to rate limits)
 OM_ADV_EMBED_PARALLEL=false
-# Delay between embeddings in milliseconds
 OM_EMBED_DELAY_MS=200
+OM_VEC_DIM=1536
 
-# OpenAI-compatible Embeddings Provider
-# OM_OPENAI_BASE_URL=https://api.openai.com/v1
-# Model override for all sector embeddings (leave empty to use defaults)
-# OM_OPENAI_MODEL=text-embedding-qwen3-embedding-4b
-
-# API Configuration
-# Max request body size in bytes (default: 1MB)
-OM_MAX_PAYLOAD_SIZE=1000000
-
-# --------------------------------------------
-# Embedding Provider API Keys
-# --------------------------------------------
-# OpenAI Embeddings
-OPENAI_API_KEY=your-openai-api-key-here
-
-# Google Gemini Embeddings
-GEMINI_API_KEY=your-gemini-api-key-here
-
-# AWS Titan Text Embeddings V2
-AWS_ACCESS_KEY_ID=YOUR_ACCESS_KEY
-AWS_SECRET_ACCESS_KEY=YOUR_SECRET_KEY
+OPENAI_API_KEY=
+GEMINI_API_KEY=
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
 AWS_REGION=us-east-1
-
-# Ollama Local Embeddings
 OLLAMA_URL=http://localhost:11434
+LOCAL_MODEL_PATH=
 
-# Local Model Path (for custom embedding models)
-LOCAL_MODEL_PATH=/path/to/your/local/model
-
-# --------------------------------------------
-# Memory System Settings
-# --------------------------------------------
-
-# ============================================
-# PERFORMANCE TIER (Manual Configuration Required)
-# ============================================
-# OpenMemory requires you to manually set the performance tier.
-# Set OM_TIER to one of: hybrid, fast, smart, or deep
-#
-# Available Tiers:
-#
-# HYBRID - Keyword + Synthetic embeddings (256-dim) with BM25 ranking
-#         • Recall: ~100% (exact keyword matching)  • QPS: 800-1000  • RAM: 0.5GB/10k memories
-#         • Best for: Exact searches, documentation, code search, personal knowledge
-#         • Features: Exact phrase matching, BM25 scoring, n-gram matching, 100% accuracy
-#         • Use when: You need guaranteed exact matches and keyword-based retrieval
-#
-# FAST  - Synthetic embeddings only (256-dim)
-#         • Recall: ~70-75%  • QPS: 700-850  • RAM: 0.6GB/10k memories
-#         • Best for: Local apps, VS Code extensions, low-end hardware
-#         • Use when: < 4 CPU cores or < 8GB RAM
-#
-# SMART - Hybrid embeddings (256-dim synthetic + 128-dim compressed semantic = 384-dim)
-#         • Recall: ~85%  • QPS: 500-600  • RAM: 0.9GB/10k memories
-#         • Best for: Production servers, AI copilots, mid-range hardware
-#         • Use when: 4-7 CPU cores and 8-15GB RAM
-#
-# DEEP  - Full AI embeddings (1536-dim OpenAI/Gemini)
-#         • Recall: ~95-100%  • QPS: 350-400  • RAM: 1.6GB/10k memories
-#         • Best for: Cloud deployments, high-accuracy systems, semantic research
-#         • Use when: 8+ CPU cores and 16+ GB RAM
-#
-# REQUIRED: Set your tier (no auto-detection):
-OM_TIER=hybrid
-
-# Keyword Matching Settings (HYBRID tier only)
-# Boost multiplier for keyword matches (default: 2.5)
-OM_KEYWORD_BOOST=2.5
-# Minimum keyword length for matching (default: 3)
-OM_KEYWORD_MIN_LENGTH=3
+# Server limits
+OM_MAX_PAYLOAD_SIZE=1000000
+OM_RATE_LIMIT_ENABLED=false
+OM_RATE_LIMIT_WINDOW_MS=60000
+OM_RATE_LIMIT_MAX_REQUESTS=100
 
+# Memory settings
 OM_MIN_SCORE=0.3
-
-# ============================================
-# Smart Decay Settings (Time-Based Algorithm)
-# ============================================
-# Decay interval in minutes - how often the decay cycle runs
-# The new algorithm uses time-based decay with daily lambda rates (hot=0.005/day, warm=0.02/day, cold=0.05/day)
-# Unlike batch-based systems, running more frequently doesn't increase decay speed
-# Decay is calculated from: decay_factor = exp(-lambda * days_since_access / (salience + 0.1))
-#
-# Recommended intervals:
-# • Testing: 30 minutes (for rapid validation)
-# • Development: 60-120 minutes (balanced testing)
-# • Production: 120-180 minutes (optimal - captures meaningful decay deltas while minimizing overhead)
-#
-# At 2-3 hours: hot tier decays ~0.04-0.06%, warm ~0.16-0.24%, cold ~0.4-0.6% per cycle
 OM_DECAY_INTERVAL_MINUTES=120
-
-# Number of parallel decay worker threads (default: 3)
 OM_DECAY_THREADS=3
-# Cold tier threshold - memories below this salience get fingerprinted (default: 0.25)
 OM_DECAY_COLD_THRESHOLD=0.25
-# Reinforce memory salience when queried (default: true)
 OM_DECAY_REINFORCE_ON_QUERY=true
-# Enable regeneration of cold memories on query hits (default: true)
 OM_REGENERATION_ENABLED=true
-# Maximum vector dimensions (default: 1536)
 OM_MAX_VECTOR_DIM=1536
-# Minimum vector dimensions for compression (default: 64)
 OM_MIN_VECTOR_DIM=64
-# Number of summary compression layers 1-3 (default: 3)
 OM_SUMMARY_LAYERS=3
-
-# Full Semantic Graph MVP Settings
-# Use summary-only storage (≤300 chars, intelligent extraction)
 OM_USE_SUMMARY_ONLY=true
-# Maximum summary length - smart extraction preserves dates, names, numbers, actions
 OM_SUMMARY_MAX_LENGTH=300
-# Memories per segment (10k recommended for optimal cache performance)
 OM_SEG_SIZE=10000
+OM_KEYWORD_BOOST=2.5
+OM_KEYWORD_MIN_LENGTH=3
 
-# Cache segments (auto-tuned by tier, but can be overridden)
-# • FAST: 2 segments  • SMART: 3 segments  • DEEP: 5 segments
-# OM_CACHE_SEGMENTS=3
-
-# Max active queries (auto-tuned by tier, but can be overridden)
-# • FAST: 32 queries  • SMART: 64 queries  • DEEP: 128 queries
-# OM_MAX_ACTIVE=64
-
-# Brain Sector Configuration (auto-classified, but you can override)
-# Sectors: episodic, semantic, procedural, emotional, reflective
-
-# Auto-Reflection System
-# Automatically creates reflective memories by clustering similar memories
+# Optional background jobs
 OM_AUTO_REFLECT=false
-# Reflection interval in minutes (default: 10)
 OM_REFLECT_INTERVAL=10
-# Minimum memories required before reflection runs (default: 20)
 OM_REFLECT_MIN_MEMORIES=20
+OM_USER_SUMMARY_INTERVAL=30
 
-# Compression
-# Enable automatic content compression for large memories
-OM_COMPRESSION_ENABLED=false
-# Minimum content length (characters) to trigger compression (default: 100)
-OM_COMPRESSION_MIN_LENGTH=100
-# Compression algorithm: semantic, syntactic, aggressive, auto (default: auto)
-OM_COMPRESSION_ALGORITHM=auto
-
-# --------------------------------------------
-# LangGraph Integration Mode (LGM)
-# --------------------------------------------
+# Optional LangGraph mode
 OM_LG_NAMESPACE=default
 OM_LG_MAX_CONTEXT=50
 OM_LG_REFLECTIVE=true
+

.github/workflows/ci.yml

@@ -8,6 +8,7 @@ on:
   workflow_dispatch:
 
 jobs:
+<<<<<<< Updated upstream
   test-python:
     name: Test Python SDK
     runs-on: ubuntu-latest
@@ -35,25 +36,28 @@ jobs:
 
   test-node:
     name: Test Node.js SDK
+=======
+  test-js:
+    name: Test JavaScript package
+>>>>>>> Stashed changes
     runs-on: ubuntu-latest
     env:
-      OM_DB_URL: "sqlite:///:memory:"
-      OM_TIER: "fast"
+      OM_TIER: fast
       OM_VEC_DIM: "1536"
+      OM_EMBEDDINGS: synthetic
     steps:
       - uses: actions/checkout@v4
-
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
+
+      - uses: actions/setup-node@v4
         with:
-          node-version: '22'
-          
-      - name: Install Dependencies
-        run: |
-          cd packages/openmemory-js
-          npm ci
-          
-      - name: Run Verification Test
-        run: |
-          cd packages/openmemory-js
-          npx tsx tests/test_omnibus.ts
+          node-version: "22"
+
+      - name: Install dependencies
+        run: cd packages/openmemory-js && npm ci
+
+      - name: Build
+        run: cd packages/openmemory-js && npm run build
+
+      - name: Run verification test
+        run: cd packages/openmemory-js && npx tsx tests/test_omnibus.ts
+

.github/workflows/docker-build.yml

@@ -2,70 +2,27 @@ name: Docker Build Test
 
 on:
   push:
-    branches:
-      - main
-      - develop
+    branches: [main, develop]
   pull_request:
-    branches:
-      - main
-      - develop
+    branches: [main, develop]
   workflow_dispatch:
 
 jobs:
   docker-build-test:
     runs-on: ubuntu-latest
-    name: Test Docker Build
-
     steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
+      - uses: actions/checkout@v4
 
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+      - uses: docker/setup-buildx-action@v3
 
-      - name: Build Backend Docker Image
+      - name: Build OpenMemory Docker image
         uses: docker/build-push-action@v5
         with:
           context: ./packages/openmemory-js
           file: ./packages/openmemory-js/Dockerfile
           push: false
-          tags: openmemory-backend:test
-          cache-from: type=gha
-          cache-to: type=gha,mode=max
-
-      - name: Test Docker Compose Build
-        run: |
-          docker compose build
-          docker compose config
-
-      - name: Start Services
-        run: |
-          docker compose up -d
-          sleep 10
-
-      - name: Check Health Endpoint
-        run: |
-          max_attempts=30
-          attempt=0
-          until curl -f http://localhost:8080/health || [ $attempt -eq $max_attempts ]; do
-            echo "Waiting for service to be healthy... (attempt $((attempt+1))/$max_attempts)"
-            sleep 2
-            attempt=$((attempt+1))
-          done
-
-          if [ $attempt -eq $max_attempts ]; then
-            echo "Service failed to become healthy"
-            docker compose logs
-            exit 1
-          fi
-
-          echo "✅ Service is healthy!"
-          curl -v http://localhost:8080/health
+          tags: openmemory-js:test
 
-      - name: Show Container Logs
-        if: failure()
-        run: docker compose logs
+      - name: Validate compose config
+        run: docker compose config
 
-      - name: Cleanup
-        if: always()
-        run: docker compose down -v