"""Dream memory lifecycle maintenance.

This module is responsible for periodic cleanup of Dream-produced memories.
It is intentionally left unimplemented as a contribution entry point.

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CONTRIBUTION GUIDE — Dream Memory Maintenance
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Dream memories are not permanent. Each Dream-produced memory carries
`DreamMemoryLifecycle` metadata (see types.py) and should be periodically
evaluated for continued relevance.

Cleanup rules to implement:

1. STALE — Long time not hit
   - If `last_hit_at` is older than a configurable TTL (e.g. 7 days),
     the memory should be decayed or archived.
   - Suggested approach: query graph_db for nodes where
     metadata.source == "dream" and lifecycle.last_hit_at < threshold.

2. LOW USEFULNESS — Hit but not helpful
   - If the memory is retrieved during queries but `usefulness_score`
     remains below a threshold, it is noise rather than signal.
   - Suggested approach: integrate with the retrieval layer to update
     usefulness_score when a Dream memory is included in a response
     but receives low relevance feedback.

3. INVALIDATED — Overturned by feedback
   - If `invalidated_by_feedback` is set to True (e.g. by the feedback
     API or a contradicting new memory), archive immediately.
   - Suggested approach: register a hook on the feedback endpoint to
     mark conflicting Dream memories.

Implementation hints:

- Create a `DreamMaintenanceTask` that runs on a scheduler interval
  (e.g. daily) or is triggered by a hook.
- Use `graph_db.update_node(id, None, {"status": "archived", ...})` to
  archive memories that fail the above checks.
- Consider a gradual decay: lower confidence over time rather than
  hard-deleting on first miss.
- The `DreamMemoryLifecycle` model in types.py already provides the
  fields you need: `last_hit_at`, `hit_count`, `usefulness_score`,
  `invalidated_by_feedback`, `status`.

Entry point suggestion:

    class DreamMaintenanceStrategy:
        def run_maintenance(self, *, user_name: str, mem_cube_id: str) -> MaintenanceReport:
            ...

Register it in plugin.py and wire it to a scheduler interval or a
dedicated API endpoint (e.g. POST /dream/maintenance/run).
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"""
