zedarvates AutoMemory
Memory as a capability, not just storage. Adapts to patterns in agent behavior.
Features
- MemoryBank — persistent key/value store with categories and confidence scores
- TrajectoryRecorder — capture goal→actions→outcomes paths
- Compressor — deduplicate, bottleneck reduction, pattern extraction
- Hook — integrate with context_profiler and control loop
Usage
from skills.auto_memory import init_memory, store_memory, recall_memory
bank = init_memory()
store_memory("user_pref.format", "concise", category="user_pref", confidence=0.95)
prefs = recall_memory("user_pref.format")
Integration
Add to control_loop.py:
from skills.auto_memory.hook import init_memory, record_step, consolidate_memory
bank = init_memory("task_123")
record_step("plan", {"steps": ["a", "b"]})
consolidate_memory() # merge similar memories