Keep Memory Core lightweight ops alive during heavy Chroma operations #11676
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Scope: high-blast(conservative default perideation-sandbox-workflow.md §6.1— a QoS layer / async-embedding-queue is an architectural change to a core subsystem and subtly alters theadd_memorycontract; reviewers may challenge via[GRADUATION_DEFERRED — reclassification request]if the convergent shape proves bounded-single-PR).The Concept
Memory Core lightweight, embedding-dependent operations —
add_memory(consolidated turn-save),ask_knowledge_base, session summarization — currently degrade to timeout whenever a heavy operation saturates the shared ChromaDB daemon. The canonical heavy operation is a full KB re-embed. Today this is effectively a ~100% block for the heavy op's full duration (hours).Proposal: keep lightweight embedding-dependent ops available during heavy operations — not a 100% block — via heavy-op throttling, a QoS layer at the Chroma-access boundary, and/or decoupling the lightweight write from the contended resource.
The Rationale (root cause)
Per ADR 0003 — Chroma Topology Unified Only, one unified ChromaDB daemon serves both the Knowledge Base and Memory Core (three collections:
knowledge-base,neo-agent-memory,neo-agent-sessions). A heavy batch-write —VectorService.embed'scollection.upsertloop during a re-embed — saturates the daemon for all collections, not just the one being written.Empirical anchor (2026-05-20): a full KB re-embed (the #11631 tenant-aware-chunk-ID migration — ~24.6k chunks, multi-hour) ran against the unified daemon. During it:
add_memorytimed out repeatedly (~4× in one agent session) — the consolidated turn-save is an embedding-write, contended.ask_knowledge_basetimed out — embedding-query, contended.add_message(A2A) kept working throughout — it is SQLite-only, no embedding path.That asymmetry — SQLite-only ops survive, embedding-path ops time out — localizes the contention precisely to the Chroma embedding read/write path. The current mitigation (defer
add_memoryto the next turn) is a documented workaround, not a fix; the friction recurs every heavy op.Double Diamond — Divergence Matrix
batchDelaygaps during a re-embedVectorService.embedalready hasbatchDelay, and lightweight ops still timed out ~4× this session — the existing windows are too small. A full re-embed already runs hours (~493 batches); wideningbatchDelaystrictly worsens that.ChromaManagers route through (they are separate managers, each with a private#chromaLock, no shared scheduler today — see OQ1a/OQ1b); lightweight single-embed ops get priority; heavy batch ops yield between batches when a lightweight op is queuedask_knowledge_base, summarization) must stay responsive during heavy ops, with no op's contract changedadd_memorywrites a durable pending-memory record (SQLite — full metadata + combined text) synchronously and returns; a background worker drains it → generates the embedding → Chromacollection.add()MemoryService.addMemorycurrently doescollection.add()(Chroma — contended) first, thenGraphService.upsertNode— and the graph node holds only asemanticVectorIdpointer, so there is no durable pre-embedding content record to merely 'decouple'; one must be created.add_message(SQLite-only) proves SQLite ops are immune to the contention.query_raw_memories/query_summaries(semantic) andget_session_memories— while graph-backed reads see it immediately and no read returns stale data (see OQ3). Does NOT help the read path; extends theadd_memorygraph-node write + adds a drain worker (materially more than a reorder).Convergent shape: 3 fixes the write path (
add_memory); 2 covers the read path. But the read path is not monolithic (see OQ1a / OQ1b): QoS keeps Memory Core semantic reads alive (their collections are not being re-embedded), whereas KB reads during a re-embed are additionally degraded by incomplete data that QoS cannot restore. A 3 + 2 hybrid remains the likely answer, scoped by OQ1a / OQ1b.Open Questions
[RESOLVED_TO_AC]. Reads againstneo-agent-memory/neo-agent-sessions(collections NOT re-embedded by a KB re-embed) degrade only by daemon contention, never by incomplete data — so the QoS layer (Option 2) is warranted and sufficient for them.query_raw_memories/query_summariesare semanticcollection.querys (fully contention-degraded, fully recoverable);get_context_frontier/pre_brief_sessionare hybrids (graph step contention-immune, only thecollection.gethydration tail contended);search_nodesis SQLite (immune). ACs: (1) Option 2 is a shared Chroma QoS arbiter mediating all daemon-bound ops from bothChromaManagers (KB + Memory Core have separate managers, each with a private#chromaLock, no shared scheduler today), tagging each op with operation-class metadata; (2) it prioritizes Memory Core lightweight reads and makes a heavy batch-loop yield between batches when any is queued; (3)search_nodesneeds no arbiter path.[RESOLVED_TO_AC].ask_knowledge_base's degradation during a re-embed has two independent causes: daemon contention (the shared QoS arbiter restores this) and incomplete data (theknowledge-basecollection is mid-rebuild — the arbiter cannot materialize absent rows). The KB read path splits across the two sibling Discussions: Keep Memory Core lightweight ops alive during heavy Chroma operations #11676's shared QoS arbiter owns the contention aspect; completeness is #11677's domain (keeping the live collection un-gutted). ACs: (1) the shared QoS arbiter coversask_knowledge_base'scollection.queryfor daemon responsiveness; (2) Keep Memory Core lightweight ops alive during heavy Chroma operations #11676 explicitly scopes OQ1b's completeness aspect out — delegated to Avoid gutting the live KB collection during a full re-embed #11677, and Keep Memory Core lightweight ops alive during heavy Chroma operations #11676 does not block on Avoid gutting the live KB collection during a full re-embed #11677; (3) until Avoid gutting the live KB collection during a full re-embed #11677 ships, a re-embed leavesask_knowledge_baseresponsive-but-incomplete (with the arbiter) rather than slow-and-incomplete — the residual is documented, not silently degraded.[RESOLVED_TO_AC]. The durable pending record is the existingAGENT_MEMORYgraph node extended to carry the combined turn content inproperties, written synchronously before any Chroma call — no new table. ACs: (1)add_memorywrites theAGENT_MEMORYnode synchronously with the combined turn content +embeddingStatus: 'pending', returning without awaiting Chroma; (2) the drain queue is selected explicitly bylabel = 'AGENT_MEMORY' AND properties.embeddingStatus = 'pending'— NOTsemanticVectorId IS NULL(addMemorysets that non-null today;MESSAGEnodes carry none); (3) the pending record carries lease/retry/health fields modeled on the existingSummarizationJobstable (lease_token,expires_at,retry_count); (4) a background drain-worker — internal daemon modeled onLazyEdgeDrainer, no MCP surface — drains pending nodes → embed →collection.add()→ setembeddingStatus: 'embedded'+semanticVectorId; (5) the drainer is idempotent and crash-safe — an interrupted drain leaves the node re-claimable (stillpending/ lease expired) so no memory is dropped.[RESOLVED_TO_AC]. Verified againstdev: no read returns stale data — the only effect is a bounded visibility lag.query_raw_memories/query_summaries(semanticcollection.query) andget_session_memories(collection.getbysessionId) do not surface a pending memory until drain;search_nodesfinds it by name/description/id immediately but not by content (searchNodesjson_extracts only name/description/id);get_context_frontierreturns it topologically (summary hydration skipped by its livesemanticVectorIdguard);pre_brief_sessionis topology-only (getNeighborsomitssemanticVectorId— a pre-existing gap, separate ticket, not this scope). ACs: (1) the graduation ticket documents the visibility-lag semantics — graph-backed reads immediate, all Chroma-backed reads lag, no stale data on any path; (2)search_nodesgains a content field /descriptionsnippet, or explicitly accepts pending content as non-text-searchable until drain; (3) pending-aware summarization barrier —summarizeSession/ thesummarizeSessionssweep must NOT finalize a session that still hasembeddingStatus: 'pending'AGENT_MEMORYnodes (defer to the next cycle), sincesummarizeSessionreads session memories via Chromacollection.get({where:{sessionId}})and would otherwise finalize an incomplete summary.VectorService.embed's delete-then-rebuild-in-place gutting the live collection for hours? Tracked as a sibling friction (see Related); NOT in this Discussion's scope, but it shares the root event.Graduation Criteria
Ready to graduate when:
[RESOLVED_TO_AC](@neo-gpt convergence, 2026-05-20).[RESOLVED_TO_AC]resolutions (@neo-gpt convergence, 2026-05-20).[GRADUATION_APPROVED]plus the OQ2/OQ3[RESOLVED_TO_AC]convergence).summarizeSessionbarrier).Graduation target: an Epic — the convergent shape is the 3 + 2 hybrid (Option 3 write-decouple + Option 2 read-arbiter), two distinct sub-areas. All 4 internal graduation criteria are met; the only remaining gate is the §6 high-blast 3-signal cross-family consensus (Gemini's harness is down → operator-override path).
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