feat: Add Memory system with Weaviate integration and MCP tools
MEMORY SYSTEM ARCHITECTURE:
- Weaviate-based memory storage (Thought, Message, Conversation collections)
- GPU embeddings with BAAI/bge-m3 (1024-dim, RTX 4070)
- 9 MCP tools for Claude Desktop integration
CORE MODULES (memory/):
- core/embedding_service.py: GPU embedder singleton with PyTorch
- schemas/memory_schemas.py: Weaviate schema definitions
- mcp/thought_tools.py: add_thought, search_thoughts, get_thought
- mcp/message_tools.py: add_message, get_messages, search_messages
- mcp/conversation_tools.py: get_conversation, search_conversations, list_conversations
FLASK TEMPLATES:
- conversation_view.html: Display single conversation with messages
- conversations.html: List all conversations with search
- memories.html: Browse and search thoughts
FEATURES:
- Semantic search across thoughts, messages, conversations
- Privacy levels (private, shared, public)
- Thought types (reflection, question, intuition, observation)
- Conversation categories with filtering
- Message ordering and role-based display
DATA (as of 2026-01-08):
- 102 Thoughts
- 377 Messages
- 12 Conversations
DOCUMENTATION:
- memory/README_MCP_TOOLS.md: Complete API reference and usage examples
All MCP tools tested and validated (see test_memory_mcp_tools.py in archive).
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
David Blanc Brioir
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