Add memory rollout feature flags and docs

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thePR0M3TH3AN committed 2026-02-14 15:23:51 -05:00
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@@ -36,6 +36,10 @@ node src/nostr-lock.mjs list
- `NOSTR_LOCK_WEEKLY_ROSTER`
- `TORCH_CONFIG_PATH`
- `AGENT_PLATFORM`
- `TORCH_MEMORY_ENABLED` (`true`/`false`; global memory kill switch, defaults to enabled)
- `TORCH_MEMORY_INGEST_ENABLED` (`true`/`false` or comma-separated canary `agent_id` allow list)
- `TORCH_MEMORY_RETRIEVAL_ENABLED` (`true`/`false` or comma-separated canary `agent_id` allow list)
- `TORCH_MEMORY_PRUNE_ENABLED` (`true`, `false`, or `dry-run`)
## torch-config.json
@@ -75,3 +79,19 @@ The lock CLI resolves roster names in this order:
- `1`: usage error
- `2`: relay/network error
- `3`: lock denied (already locked or race lost)
## Memory rollout plan
1. Deploy memory schema changes with scheduler jobs disabled (`TORCH_MEMORY_ENABLED=false` or subsystem flags set to `false`).
2. Enable ingest for one canary `agent_id` via `TORCH_MEMORY_INGEST_ENABLED=<agent_id>`.
3. Validate retrieval quality and storage growth metrics before expanding scope.
4. Enable broader retrieval (`TORCH_MEMORY_RETRIEVAL_ENABLED=<allow-list>` then `true`).
5. Enable pruning in `dry-run` mode first, then switch to active pruning after revalidation.
## Memory rollback plan
1. Disable memory flags (`TORCH_MEMORY_ENABLED=false` and/or set ingest/retrieval/prune flags to `false`).
2. Stop memory maintenance scheduler processes.
3. Preserve database state for post-incident analysis; do not drop or rewrite memory tables during rollback.
4. Keep prune actions in `dry-run` (or disabled) until lifecycle policy and data integrity are revalidated.