41cd78207a
- Configure mem0 to use self-hosted Supabase instead of Qdrant for vector storage - Update docker-compose to connect containers to localai network - Install vecs library for Supabase pgvector integration - Create comprehensive test suite for Supabase + mem0 integration - Update documentation to reflect Supabase configuration - All containers now connected to shared localai network - Successful vector storage and retrieval tests completed 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
109 lines
3.6 KiB
Markdown
109 lines
3.6 KiB
Markdown
# Phase 1 Complete: Foundation Setup ✅
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## Summary
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Successfully completed Phase 1 of the mem0 memory system implementation! All core infrastructure components are now running and tested.
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## ✅ Completed Tasks
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### 1. Project Structure & Environment
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- ✅ Cloned mem0 repository
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- ✅ Set up Python virtual environment
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- ✅ Installed mem0 core package (v0.1.115)
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- ✅ Created configuration management system
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### 2. Database Infrastructure
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- ✅ **Neo4j Graph Database**: Running on localhost:7474/7687
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- Version: 5.23.0
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- Password: `mem0_neo4j_password_2025`
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- Ready for graph memory relationships
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- ✅ **Qdrant Vector Database**: Running on localhost:6333/6334
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- Version: v1.15.0
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- Ready for vector memory storage
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- 0 collections (clean start)
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- ✅ **Supabase**: Running on localhost:8000
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- Container healthy but auth needs refinement
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- Available for future PostgreSQL/pgvector integration
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### 3. LLM Infrastructure
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- ✅ **Ollama Local LLM**: Running on localhost:11434
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- 21 models available including:
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- `qwen2.5:7b` (recommended)
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- `llama3.2:3b` (lightweight)
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- `nomic-embed-text:latest` (embeddings)
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- Ready for local AI processing
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### 4. Configuration System
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- ✅ Environment management (`.env` file)
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- ✅ Configuration loading system (`config.py`)
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- ✅ Multi-provider support (OpenAI/Ollama)
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- ✅ Database connection management
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### 5. Testing Framework
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- ✅ Basic functionality tests
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- ✅ Database connection tests
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- ✅ Service health monitoring
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- ✅ Integration validation
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## 🎯 Current Status: 4/5 Systems Operational
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| Component | Status | Port | Notes |
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|-----------|--------|------|-------|
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| Neo4j | ✅ READY | 7474/7687 | Graph memory storage |
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| Qdrant | ✅ READY | 6333/6334 | Vector memory storage |
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| Ollama | ✅ READY | 11434 | Local LLM processing |
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| Mem0 Core | ✅ READY | - | Memory management system |
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| Supabase | ⚠️ AUTH ISSUE | 8000 | Container healthy, auth pending |
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## 📁 Project Structure
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```
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/home/klas/mem0/
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├── venv/ # Python virtual environment
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├── config.py # Configuration management
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├── test_basic.py # Basic functionality tests
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├── test_openai.py # OpenAI integration test
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├── test_all_connections.py # Comprehensive connection tests
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├── docker-compose.yml # Neo4j & Qdrant containers
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├── .env # Environment variables
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├── .env.example # Environment template
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└── PHASE1_COMPLETE.md # This status report
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```
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## 🔧 Ready for Phase 2: Core Memory System
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With the foundation in place, you can now:
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1. **Add OpenAI API key** to `.env` file for initial testing
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2. **Test OpenAI integration**: `python test_openai.py`
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3. **Begin Phase 2**: Core memory system implementation
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4. **Start local-first development** with Ollama + Qdrant + Neo4j
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## 📋 Next Steps (Phase 2)
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1. **Configure Ollama Integration**
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- Test mem0 with local models
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- Optimize embedding models
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- Performance benchmarking
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2. **Implement Core Memory Operations**
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- Add memories with Qdrant vector storage
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- Search and retrieval functionality
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- Memory management (CRUD operations)
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3. **Add Graph Memory (Neo4j)**
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- Entity relationship mapping
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- Contextual memory connections
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- Knowledge graph building
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4. **API Development**
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- REST API endpoints
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- Authentication layer
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- Performance optimization
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5. **MCP Server Implementation**
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- HTTP transport protocol
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- Claude Code integration
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- Standardized memory operations
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## 🚀 The foundation is solid - ready to build the memory system! |