fix(agent-sessions): treat the GenAI memory operations as known ops - #1142
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📝 WalkthroughWalkthroughThe ingest gateway now stamps AI span facts and normalized usage. Session readers and ClickHouse indexes consume those stamps. The AI trace index adds tool-call identity and paused-call fields, with local schema version 26 and ClickHouse migration 0035. ChangesAI telemetry stamping and indexing
Priority: ➖ Normal Estimated code review effort: 4 (Complex) | ~60 minutes Change: Bug fix Sequence Diagram(s)sequenceDiagram
participant IngestGateway
participant TraceStorage
participant AiTraceIndexMv
participant SessionReaders
IngestGateway->>TraceStorage: Store spans with maple_ai.* stamps
TraceStorage->>AiTraceIndexMv: Provide span attributes for index projection
TraceStorage->>SessionReaders: Provide spans for session summaries and classification
Suggested reviewers: Merge Risk: 🟡 Moderate · up to Local CLI users would see AI trace index rows with no model, call or token data, because local ingest does not add the fields the new view reads. Fix this before merging. Two smaller issues also remain. Older memory spans can be counted as model calls in session summaries while the detail page shows them as agent work. The warehouse notes can also lead queries to subtract a child's tokens from a parent that no longer carries them, producing negative totals. Security Architecture ReviewSecurity architecture risk: 🔵 Low · up to The change centralizes how AI activity is classified and stored. The inspected paths do not add permissions or tool execution, but deployment-order and rollback compatibility remain unverified. Retained concerns Security review detailsSecurity Blast Radius
Trust Boundaries and Controls
Resilience and Maintainability Implications
Hardening Proposals
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Maple reviewConfidence 4/5 · likely safe to merge Adds the semconv memory-store operations to both operation vocabularies so a memory span is no longer read as an LLM or tool call, and restates Claude Code's cache-write tokens under
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| if (INFERENCE_OPS.has(operation) || RETRIEVAL_OPS.has(operation)) return "inference" | ||
| if (TOOL_OPS.has(operation)) return "tool" | ||
| if (AGENT_OPS.has(operation)) return "agent" | ||
| if (AGENT_OPS.has(operation) || MEMORY_OPS.has(operation)) return "agent" |
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🟡 Memory bookkeeping opens an extra turn
When a root memory span precedes an agent invocation, classifyAiSpan makes both eligible turn anchors. If they end over five seconds apart, findAnchors retains a phantom turn for bookkeeping.
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Agent-root anchors are AI spans classified as agent work with no AI ancestor. A root memory span now qualifies, although it does not start a user turn. The setup-merging rule only collapses workless anchors that end within five seconds of the next one buildSessionTurns. This makes memory operations produce extra turns when they are separate roots and more than five seconds apart.
Example: A search_memory span starts at second 0 and ends at second 1, followed by invoke_agent at second 10. Both are root AI spans. The session gets two turns instead of one.
Recommended fix: Keep memory operations classified as agent work for display, but exclude AI_MEMORY_OPERATIONS from the agent-root anchor selection in findAnchors. Add a test with a root memory span followed by an agent root beyond the setup window.
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Valid, fixed in f3f338e. findAnchors now skips spans whose operation is in AI_MEMORY_OPERATIONS when it picks agent roots. They still classify as agent for display. Added test does not open a turn at a root memory operation: search_memory at 0-1s, then invoke_agent at 10s, gives one agent-root turn that holds all three spans.
Maple reviewConfidence 2/5 · risky as written Adds the semconv memory operations to the shared operation vocabulary so a memory span reads as agent bookkeeping in both the classifier and the session SQL, and keeps a root memory span from opening its own turn. Safe to merge; the anchor rule and its test both need one more pass.
FindingsWarning · F1 · Memory span with no
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| (span) => | ||
| span.isAiSpan && | ||
| classifyAiSpan(span) === "agent" && | ||
| !MEMORY_OPS.has(span.genAi.operationName ?? "") && |
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Memory span with no gen_ai.operation.name still opens a turn
F1 · Warning · correctness
The anchor filter reads only the reported attribute, but classifyAiSpan falls back to the span name — and this file exists to serve the reporters that skip gen_ai.operation.name (GEN_AI_OPERATIONS, session-waterfall.tsx:758). A root span named create_memory with no model and no reported operation lands on session-turns.ts:91 as "agent", so MEMORY_OPS.has("") is false and it anchors a turn of its own: the session shows an extra turn whose only content is bookkeeping — exactly what f3f338e set out to prevent.
Derive the operation the same way `classifyAiSpan` does when the attribute is absent — the leading word of the span name when `GEN_AI_OPERATIONS` contains it — e.g. a small `spanOperation(span)` helper called from both places, and filter on its result here.
Prompt for an AI agent
In `packages/agent-sessions/src/session-turns.ts:425-426`: Memory span with no `gen_ai.operation.name` still opens a turn.
The anchor filter reads only the reported attribute, but `classifyAiSpan` falls back to the span name — and this file exists to serve the reporters that skip `gen_ai.operation.name` (`GEN_AI_OPERATIONS`, `session-waterfall.tsx:758`). A root span named `create_memory` with no model and no reported operation lands on `session-turns.ts:91` as `"agent"`, so `MEMORY_OPS.has("")` is false and it anchors a turn of its own: the session shows an extra turn whose only content is bookkeeping — exactly what f3f338e set out to prevent.
Suggested fix: Derive the operation the same way `classifyAiSpan` does when the attribute is absent — the leading word of the span name when `GEN_AI_OPERATIONS` contains it — e.g. a small `spanOperation(span)` helper called from both places, and filter on its result here.
Verify the problem exists at that location before changing it, and keep the fix to those lines.
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Leaving this as is. A memory operation is recognised by its operation everywhere: the ingest gateway (KNOWN_OPS against the reported operation, #1143) and classifyAiSpan. Reading it off a span name here only would make turn anchoring disagree with how the same span is classified.
…del-call rule A memory operation naming its embedding model is agent bookkeeping, not a model call; #1142 adds the same ops to the index's known-op list.
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Maple reviewConfidence 2/5 · risky as written The head teaches the agent-sessions classifier that GenAI memory operations are agent work, keeps them from opening a turn, and restates Claude Code cache tokens under the semconv
FindingsWarning · F3 · Memory ops read as
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…1143) * feat(ingest): stamp model-call usage as disjoint maple_ai.usage buckets The gateway now restates a model call's token usage as five disjoint buckets (uncached input, cache read, cache write, visible output, reasoning) plus cost under maple_ai.usage.*, leaving the customer's gen_ai.usage.* as sent. The convention is chosen by emitter, not by gen_ai.provider.name, so inclusive emitters labelled anthropic (OpenRouter Broadcast, OTel genai anthropic, Pydantic AI) no longer double count their cache. Only the span that is the model call carries buckets; agent, step and workflow wrappers get none. Guards: a prompt smaller than its cache is read cache-exclusive, and reasoning is clamped to the completion so a span's total matches the provider's total_tokens. * feat(ingest): mark every stamped span with maple_ai.llm_call The gateway already decides which span is the model call to own the usage buckets; it now says so on every stamped span: 1 on the model call (with or without usage, so a failed call still counts), 0 on the rest. The key's presence tells readers the gateway classified the span, so rows without it keep the op/name heuristics until they age out. An unknown dialect's server span (a proxy's POST /chat/completions) is never the call. Tests cover the heuristic false positives: Spring AI chat_client (op framework), LangSmith ChatPromptTemplate (op chain), DSPy ChatAdapter.__call__ (no op) and the LiteLLM proxy server span. * fix(ingest): treat the GenAI memory operations as known ops in the model-call rule A memory operation naming its embedding model is agent bookkeeping, not a model call; #1142 adds the same ops to the index's known-op list. * feat(agent-sessions): decide every aggregate/filter fact at ingest, the index projects the stamps (#1160) * feat(ingest): stamp every Agent Sessions aggregate and filter fact on the span The gateway now decides, per stamped span, whether it is a tool call, whether it failed, whether it is a tool call's paused copy, and its model, agent, tool, tool call id, response id, tool description and a failed tool call's result, and writes each as a maple_ai.* stamp beside the llm-call marker and usage buckets. One pass over the span's attributes feeds every fact, usage included, in place of a scan per key. OpenAI Agents' OpenInference instrumentor names an agent only in graph.node.id on its AGENT span; that id is the agent name where it equals the span name. * feat(agent-sessions): ai_trace_index_mv projects the gateway's maple_ai.* stamps Migration 0039 (local schema v26; both placeholders, renumbered at merge) recreates ai_trace_index_mv so Model, AgentName, ToolName, ResponseId, IsLlmCall, IsToolCall, IsError, the five token buckets, Tokens, Cost, ToolDescription and FailedToolCallResult each read the fact the ingest gateway stamped on the span. The operation lists, span-name needles, dialect key lists and per-provider usage conventions leave the view; what stays is generic: the environment, error.type, the status message and the failure fingerprint's redaction chain. * feat(agent-sessions): the detail page and /summary read the gateway's stamps On a span the ingest gateway stamped (maple_ai.llm_call present), classifyAiSpan, isLlmCall and spanFailed take its verdicts, spanTokenBuckets and the new spanCost its buckets and cost, and the /summary SQL its verdicts, names and buckets: the facts ai_trace_index sums, so the list and the page cannot disagree. Spans ingested before keep the op/name rules and usage conventions until the 30-day TTL. The materialization e2e seeds carry the stamps the gateway would have written. * chore(ingest): name the stamp key table's entry type, point the stamps at MAPLE_AI_STAMP_ATTRS * docs(agent-sessions): point comments at the gateway's stamps instead of the deleted SQL builders * fix(agent-sessions): number the gateway-stamps view migration 0035 Migration versions must be contiguous, and a BYO-ClickHouse instance at 0039 would skip a lower number landing later. The in-flight view changes rebase onto this one and drop their own migrations of the view. * fix(agent-sessions): the prompt-cache check counts the gateway's cache buckets * fix(agent-sessions): the detail page names the agent the gateway named The span mapper prefers maple_ai.agent.name over the decoded dialect keys, so every reader of genAi.agentName (header, turns, waterfall, filters) shows the agent the list and its facets show, OpenAI Agents' graph node included. * chore(agent-sessions): drop unread stamp keys, unexport in-file constants, fix stale comments * fix(agent-sessions): build the e2e gateway stamps without an open dictionary binding * test(agent-sessions): pin the stamp keys against the ingest gateway's sources * fix(ingest): read a text fact of any OTLP type, as the warehouse Map holds it An integer tool call id or response id, a structured tool call result and a non-string error.type counted when the view read the Map; the stamps now count them too, stringified the way the row encoder writes the Map. Only Google ADK writes the confirmation request, so only its tool results are searched for it. * fix(ingest): stamp a reported $0 cost, so a free call is not read as unpriced * fix(ingest): saturate the cache sum, so an absurd customer figure cannot overflow it * test(agent-sessions): hash the gateway's Rust sources into the stamp-key pin, match only their constants * test(agent-sessions): prove the gateway's failure verdict overrides a span's own error.type * chore(agent-sessions): cut process notes and a duplicate test, rewrap comments * feat(agent-sessions): project the tool call id and the paused-copy stamp onto ai_trace_index Migration 0035 and local schema v26 add ToolCallId (maple_ai.tool.call_id) and IsPausedToolCall (maple_ai.tool.paused) to ai_trace_index, so the list can count a call paused for approval and executed in a later trace once. Only the columns and their projection; the counting stays with the list. * test(agent-sessions): seed the ai-tools e2e spans with the gateway's stamps ai_trace_index_mv projects only the maple_ai.* stamps since migration 0035, so the ai-tools seeds, which carried none, would materialize as neither a call nor a tool. The stamp helper moves to clickhouse-e2e-support so both suites share it. * feat(agent-sessions): a tool call paused for approval is no call, by its framework's explicit mark Drops ToolCallId and IsPausedToolCall from migration 0035 and local schema v26, and the gateway's maple_ai.tool.call_id and maple_ai.tool.paused stamps. Instead the gateway stamps maple_ai.tool_call = 0 on the copy a call paused for a human's approval leaves, so list, summary and detail all count maple_ai.tool_call = 1; a call paused and then rejected counts none. Such a copy is no failure either, though some frameworks end it in error. A pause is read only from a framework's explicit mark, never from a missing result (content capture off, or a tool that returns nothing): - Google ADK: gcp.vertex.agent.tool_response carries the confirmation request (every ADK version writes the key; 2.6 writes no gen_ai.tool.call.result). - OpenAI Agents SDK up to 0.22.0: output.value is a ToolApprovalItem's repr. - pydantic-ai: pydantic_ai.tool.deferral.name = ApprovalRequired. - LlamaIndex's own tracer: the step's status message "Waiting for event". Strands, OpenAI Agents 0.22.1+ and a Mastra tool that suspends itself mark nothing on the paused copy, so it still counts. * fix(agent-sessions): the detail page counts and fails a stamped span by the gateway's verdict (folds #1141) The gateway stamps maple_ai.tool_call = 0 on the copy a call paused for a human's approval leaves, and no maple_ai.error on it even where its framework ends it in error. The read path follows: - isCountedToolCall: on a stamped span maple_ai.tool_call = 1. The detail count, the tool histogram, the checks' coverage and the repetition finding use it, so a paused copy is in none of them. The display kind (classifyAiSpan) still reads a paused copy as a tool: the waterfall, span kind and icons show it as one. - countedToolCalls: the result-based pause merge (drop a no-result copy when a later copy under the same call id carries a result) serves only pre-stamp spans until the 30-day TTL, so a stamped call that recorded no result is no longer dropped. - spanFailed and the totals read's failure count: on a stamped span the gateway's maple_ai.error alone, so a paused copy its framework ended in error (LlamaIndex, pydantic-ai before instrumentation v5) is no failure, as on the list.
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Inline comments:
Review comments at @apps/cli/src/server/schema/local-schema.sql:
- Around line 996-1020: Update the local POST /v1/traces ingest flow before
encodeTraces to apply the Rust gateway’s Maple AI stamping logic, or an
equivalent TypeScript implementation, to decoded spans missing required
maple_ai.* attributes. Preserve existing attributes and ensure the stamped
values are present in SpanAttributes before insertion so the v26 view can derive
model, call flags, and usage.
Review comments at
@packages/backend/src/services/warehouse/warehouse-catalog.ts:
- Line 39: Update the ai_trace_index catalog notes to describe Model, AgentName,
ToolName, Tokens, and ToolCallId as projections of maple_ai.* stamps. Restrict
child-token netting guidance to rows materialized before migration 0035, and
identify maple_ai.tool.call_id and maple_ai.tool.paused as the ToolCallId and
pause-status source keys.
Review comments at @packages/query-engine-integrations/src/ai/ai-sessions.ts:
- Around line 1644-1647: Update the unstamped-span fallback in the summary
query, identified by its `.notIn(...)` call, to also exclude
`AI_MEMORY_OPERATIONS`. Import `AI_MEMORY_OPERATIONS` from
`@maple/domain/gen-ai` and preserve the existing retrieval, tool, and agent
exclusions.
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apps/cli/src/server/local-schema-history.tsapps/cli/src/server/local-schema-version.tsapps/cli/src/server/local-store-migrations/steps.tsapps/cli/src/server/schema-identity.tsapps/cli/src/server/schema/local-inserts.jsonapps/cli/src/server/schema/local-schema-v26.sqlapps/cli/src/server/schema/local-schema.sqlapps/cli/test/local-store-migrations.test.tsapps/cli/test/native-local-store-migration.shapps/ingest/benches/ai_session_bench.rsapps/ingest/src/ai_session.rsapps/ingest/src/ai_session/claude_code.rsapps/ingest/src/ai_session/facts.rsapps/ingest/src/ai_session/usage.rsapps/ingest/src/clickhouse_insert_mappings.rsapps/ingest/src/telemetry.rsapps/web/src/components/agent-sessions/session-detail/span-expansion.tsxpackages/agent-sessions/src/session-checks.test.tspackages/agent-sessions/src/session-checks.tspackages/agent-sessions/src/session-summary.test.tspackages/agent-sessions/src/session-summary.tspackages/agent-sessions/src/session-turns.test.tspackages/agent-sessions/src/session-turns.tspackages/backend/src/services/warehouse/ai-trace-index-materialization.clickhouse.e2e.test.tspackages/backend/src/services/warehouse/warehouse-catalog.tspackages/domain/src/clickhouse/migrations/0035_ai_trace_index_gateway_stamps.tspackages/domain/src/clickhouse/migrations/index.test.tspackages/domain/src/clickhouse/migrations/index.tspackages/domain/src/gen-ai.test.tspackages/domain/src/gen-ai.tspackages/domain/src/tinybird/datasources.tspackages/domain/src/tinybird/gen-ai-columns.tspackages/domain/src/tinybird/materializations.tspackages/query-engine-integrations/src/__sql_baseline__/integrations.sqlpackages/query-engine-integrations/src/ai/ai-integrations.test.tspackages/query-engine-integrations/src/ai/ai-integrations.tspackages/query-engine-integrations/src/ai/ai-sessions.test.tspackages/query-engine-integrations/src/ai/ai-sessions.tspackages/query-engine-integrations/src/ai/ai-span-columns.test.tspackages/query-engine-integrations/src/ai/ai-span-columns.tspackages/query-engine-integrations/src/ai/ai-tools.tspackages/query-engine/src/ch/tables.tsturbo.json
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search_memory, create_memory, update_memory, upsert_memory, delete_memory, create_memory_store and delete_memory_store fell through to the span-name fallback, so a memory span naming a model counted as an LLM call and one naming a tool as a tool call. The ingest gateway already decides this for the spans it stamps (`KNOWN_OPS` in `ai_session/usage.rs`). The detail classifier now reads them as agent work for the spans ingested before the stamps.
Semconv renamed gen_ai.usage.cache_creation.input_tokens to gen_ai.usage.cache_write.input_tokens. Every reader accepts the new name: the detail decode aliases it, and ai_trace_index_mv and the session summary SQL coalesce both spellings.
A search_memory ahead of the agent run is agent work but not the start of a turn; as an agent-root anchor it opened a phantom turn whenever it ended more than the setup window before the run.
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Maple review🔴 Confidence 2/5 · risky as written Adds the seven semconv memory-store operations to the domain's known ops, so the detail classifier reads them as agent work and they stop opening a turn of their own, and restates Claude Code cache writes under the semconv
Still open from earlier reviews
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Maple review🟡 Confidence 3/5 · needs attention This head adds
Still open from earlier reviews
Fixed since the last review
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Based on
main(#1143 landed as 3688ee9); rebased so only this PR's commits remain. No migration and no warehouse SQL rule: #1143's ingest gateway already treats the memory ops as known (KNOWN_OPSinapps/ingest/src/ai_session/usage.rs, used bymaple_ai.llm_callandmaple_ai.tool_call), and the index only projects those stamps. The former migration 0035 / local schema v26, thegen-ai-columns.tsKNOWN_OPSchange and the session-summary SQL change are gone.1. Memory operations are known ops on the read path
The semconv memory-store operations (
search_memory,create_memory,update_memory,upsert_memory,delete_memory,create_memory_store,delete_memory_store) hit the span-name / model / tool-name fallback: a memory span naming a model counted as an LLM call, one naming a tool as a tool call.AI_MEMORY_OPERATIONSinpackages/domain/src/gen-ai.tssession-turns.ts): memory ops read asagentwork, never inference or tool. Stamped spans already get this from the gateway; this covers rows ingested before the stamps.findAnchors: a root memory operation does not open a turn of its own2. Claude Code restatement writes
gen_ai.usage.cache_write.input_tokensSemconv renamed
cache_creationtocache_write. Every reader already accepts the new key:usage.rsreads both spellings)GENAI_LEGACY_ALIASES.usageCacheCreationInputTokens(ai-integrations.ts)packages/ui/src/lib/gen-ai.ts): both listedDeploy notes
Tests (on
main)cargo test --lib ai_session(apps/ingest): 73 passpackages/agent-sessionssession-turns (53 pass; the anchor test fails with the memory filter removed),packages/domaingen-aiNeed help on this PR? Tag
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