MidOS Memory Cascade

Python API

from tools.memory.memory_cascade import recall, store
Search across all tiers
result = recall("adaptive alpha reranking")
→ {"answer": {...}, "tier": "T5:lancedb", "latency_ms": 340, "confidence": 0.87}
Write to the right storage automatically
store("pattern", content="...", tags=["ml", "reranking"])

CLI

# Search
python memory_cascade.py recall "query here"
View tier resolution stats
python memory_cascade.py stats
Run self-evolution (learn shortcuts + tier skips)
python memory_cascade.py evolve

recall() Options

recall(
    query: str,
    min_confidence: float = 0.5,  # stop escalating at this threshold
    max_tier: int = 6             # 0=T0 only, 6=all tiers
)

Returns:

{
  "answer": { "source": "...", "text": "..." },
  "confidence": 0.87,
  "latency_ms": 340.2,
  "tiers_tried": 3,
  "resolved_at": "T5:lancedb",
  "shortcut": null,
  "question_routed": false,
  "escalation": [...]
}