Alexander Payne
625806daf5
Fine-tune Timmy's conversational AI with memory layers
## Enhanced System Prompt
- Detailed tool usage guidelines with explicit examples
- Clear DO and DON'T examples for tool selection
- Memory system documentation
- Conversation flow guidelines
- Context awareness instructions
## Memory Layer System (NEW)
Implemented 3-layer memory architecture:
1. WORKING MEMORY (src/timmy/memory_layers.py)
- Immediate context (last 20 messages)
- Topic tracking
- Tool call tracking
- Fast, ephemeral
2. SHORT-TERM MEMORY (Agno SQLite)
- Recent conversations (100)
- Persists across restarts
- Managed by Agno Agent
3. LONG-TERM MEMORY (src/timmy/memory_layers.py)
- Facts about user (name, preferences)
- SQLite storage in data/memory/
- Auto-extraction from conversations
- User profile generation
## Memory Manager (NEW)
- Central coordinator for all memory layers
- Context injection into prompts
- Fact extraction and storage
- Session management
## TimmyWithMemory Class (NEW)
- Wrapper around Agno Agent with explicit memory
- Auto-injects user context from LTM
- Tracks exchanges across all layers
- Simple chat() interface
## Agent Configuration
- Increased num_history_runs: 10 -> 20
- Better conversational context retention
## Tests
- All 973 tests pass
- Fixed test expectations for new config
- Fixed module path in test_scary_paths.py
## Files Added/Modified
- src/timmy/prompts.py - Enhanced with memory and tool guidance
- src/timmy/agent.py - Added TimmyWithMemory class
- src/timmy/memory_layers.py - NEW memory system
- src/timmy/conversation.py - NEW conversation manager
- tests/ - Updated for new config
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