fix(agent-sessions): decode tool-error payloads the way the session page does

apps/ai/src/mcp/tools/__tests__/agent-tools.test.ts

@@ -127,10 +127,10 @@
 
 const breakdownPairRows = [{ model: "claude-sonnet-4", service: "api", calls: 9 }]
 
-// Exactly what the read returns for a payload it cut: `AI_TOOL_ERROR_PAYLOAD_MAX`
-// characters, with the row reporting the true size the span carried.
-const LONG_ARGUMENTS = `{"query":"${"x".repeat(AI_TOOL_ERROR_PAYLOAD_MAX - 12)}"}`
+// Arguments longer than the read keeps: it cuts them to `AI_TOOL_ERROR_PAYLOAD_MAX`
+// characters and reports the true size the span carried.
 const LONG_ARGUMENTS_BYTES = 12_000
+const LONG_ARGUMENTS = `{"query":"${"x".repeat(LONG_ARGUMENTS_BYTES - 12)}"}`
 
 /** The payload rows below are joined to these by trace and span id. */
 const occurrence = (ids: [string, string], sessionId: string, timestamp: string, durationNs: number) => ({
@@ -153,20 +153,14 @@
 ]
 
 /** `statusCode` is Title case on the wire, like every other Maple span status. */
-const payload = (ids: [string, string], args: string, argumentsBytes: number) => ({
+const payload = (ids: [string, string], args: string, result = "TimeoutError: upstream timed out") => ({
 	traceId: ids[0].repeat(32),
 	spanId: ids[1].repeat(16),
 	statusCode: "Error",
-	arguments: args,
-	argumentsBytes,
-	result: "TimeoutError: upstream timed out",
-	resultBytes: 32,
+	spanAttributes: { "gen_ai.tool.call.arguments": args, "gen_ai.tool.call.result": result },
 })
 
-const payloadRows = [
-	payload(["a", "b"], LONG_ARGUMENTS, LONG_ARGUMENTS_BYTES),
-	payload(["c", "d"], `{"query":"short"}`, 17),
-]
+const payloadRows = [payload(["a", "b"], LONG_ARGUMENTS), payload(["c", "d"], `{"query":"short"}`)]
 
 /** The payload read, answering with rows of the test's own shape. */
 const payloadsAre = (rows: ReadonlyArray<unknown>): FixtureRule[] => [
@@ -424,7 +418,7 @@
 
 	it("renders sessions, variants, the breakdown and clipped sample payloads", async () => {
 		const rendered = await render(ERROR_DETAIL, { ...GROUP, payload_chars: 100 })
 		expect(rendered).toContain(`## Tool failure group ${FINGERPRINT}`)
 		expect(rowCells(rendered, "sess_a")).toEqual([
 			"sess_a",
 			"openai-agents",
@@ -453,7 +447,7 @@
 		// One row past the page is what tells the read there is a next page — on
 		// the samples statement, not the variants read's constant `LIMIT 20`.
 		expect(samplesSql().some((sql) => /\bLIMIT 2\b/.test(sql))).toBe(true)
 		expect(rendered).toContain("More samples exist past this page")
 
 		executedSql.length = 0
 		await call(ERROR_DETAIL, { ...GROUP, samples_limit: 999 })
@@ -462,7 +456,7 @@
 
 	it("clamps payload_chars to its default and its ceiling", async () => {
 		// The clip appends one ellipsis to the characters it kept.
 		expect(clippedArguments(await render(ERROR_DETAIL, GROUP))).toHaveLength(801)
 		// The ceiling is the read's own cap, and the payload the read already cut
 		// still renders with the ellipsis its byte total implies.
 		expect(
@@ -478,22 +472,18 @@
 	})
 
 	it("tells a payload the span left empty from one it never carried", async () => {
-		const rows = payloadRows.map((row) => ({ ...row, arguments: "", argumentsBytes: 0 }))
+		const rows = [payload(["a", "b"], ""), payload(["c", "d"], "")]
 		const rendered = await renderWith(payloadsAre(rows), ERROR_DETAIL, GROUP)
 		expect(rendered).toContain("(empty)")
 		expect(rendered).not.toContain("(not available: the span was not retained)")
 	})
 
 	it("fences a sample payload that carries a code fence of its own", async () => {
-		const rows = payloadRows.map((row) => ({
-			...row,
-			result: FENCED_RESULT,
-			resultBytes: FENCED_RESULT.length,
-		}))
+		const rows = [payload(["a", "b"], "{}", FENCED_RESULT), payload(["c", "d"], "{}", FENCED_RESULT)]
 		const rendered = await renderWith(payloadsAre(rows), ERROR_DETAIL, GROUP)
 		// One backtick longer than the longest run inside the payload, which is
 		// left intact.
 		expect(rendered).toContain(`\`\`\`\`\n${FENCED_RESULT}`)
 		expect(rendered).toContain("```js")
 	})
 

apps/api/src/routes/internal/ai-sessions.http.test.ts

@@ -1668,10 +1668,11 @@
 										traceId: occurrence.traceId,
 										spanId: occurrence.spanId,
 										statusCode: "Ok",
-										arguments: "{}",
-										argumentsBytes: 2,
-										result: occurrence.message,
-										resultBytes: 58,
+										spanAttributes: {
+											"maple_ai.vendor.id": "maple",
+											"gen_ai.tool.call.arguments": "{}",
+											"gen_ai.tool.call.result": occurrence.message,
+										},
 									},
 								],
 					)
@@ -1685,7 +1686,7 @@
 				tool: "run_tests",
 				fingerprint: FINGERPRINT,
 			})
 			expect(response.status).toBe(200)
 			expect(contexts).toEqual(["aiToolsErrorOccurrences", "aiToolsErrorPayloads"])
 			const [occurrencesSql, payloadSql] = seen
 			// One row past the default page, to know whether there is another.
@@ -1708,7 +1709,7 @@
 						arguments: "{}",
 						argumentsBytes: 2,
 						result: occurrence.message,
-						resultBytes: 58,
+						resultBytes: occurrence.message.length,
 					},
 				],
 			})

packages/backend/src/services/ai-sessions/ai-session-reads.ts

@@ -749,7 +749,11 @@ export const readAiToolErrorSamples = Effect.fn("aiSessions.toolErrorSamples")(f
 				),
 				{ profile: "list", context: "aiToolsErrorPayloads" },
 			)
-	const payloadBySpan = new Map(payloads.map((row) => [`${row.traceId}:${row.spanId}`, row] as const))
+	const payloadBySpan = new Map(
+		payloads.map(
+			(row) => [`${row.traceId}:${row.spanId}`, Integrations.aiToolErrorPayload(row)] as const,
+		),
+	)
 	return new AiToolErrorSamplesResponse({
 		...(nextCursor !== undefined && { nextCursor }),
 		occurrences: occurrences.map((row) => {

packages/backend/src/services/warehouse/ai-tools.clickhouse.e2e.test.ts

@@ -96,6 +96,9 @@ const TRACE_IDS_AT_1 = missingKey('["evidence"][1]["traceIds"]')
 const LOG_PATTERNS_AT_0 = missingKey('["evidence"][0]["logPatterns"]')
 /** A failure that says why in its status message alone. */
 const REFUSED = "sandbox refused the command"
+/** `flaky_tool`'s parameter schema. */
+const FLAKY_SCHEMA =
+	'{"properties": {"retries": {"type": "integer"}}, "required": ["retries"], "type": "object"}'
 
 interface SeedSpan {
 	readonly traceId: string
@@ -280,10 +283,17 @@ const SEED_SPANS: ReadonlyArray<SeedSpan> = [
 		durationNs: 8_000_000,
 		status: "Error",
 		statusMessage: "upstream returned 503",
+		// An OpenInference tool span whose GenAI dual-write copied the parameter
+		// schema into the arguments slot: the payload read shows `input.value`,
+		// as the session page does.
 		attrs: agentSpan({
+			[MAPLE_AI_VENDOR_ID_ATTR]: "openai_agents_sdk",
+			"openinference.span.kind": "TOOL",
 			"gen_ai.operation.name": "execute_tool",
 			"gen_ai.tool.name": "flaky_tool",
-			"gen_ai.tool.call.arguments": '{"retries":1}',
+			"tool.parameters": FLAKY_SCHEMA,
+			"gen_ai.tool.call.arguments": FLAKY_SCHEMA,
+			"input.value": '{"retries":1}',
 			"gen_ai.tool.call.result": '{"error":"503"}',
 			...aiGatewayStamps({
 				toolCall: true,
@@ -825,13 +835,15 @@ describe.skipIf(!clickhouseE2eEnabled)("agent tools reads", () => {
 		)
 		assert.isFalse(payloads.sql.includes(flakyWindow.startTime))
 		assert.deepStrictEqual(
-			Effect.runSync(payloads.decodeRows(await runJson(payloads.sql))).map((row) => ({
-				spanId: row.spanId,
-				statusCode: row.statusCode,
-				arguments: row.arguments,
-				argumentsBytes: row.argumentsBytes,
-				resultBytes: row.resultBytes,
-			})),
+			Effect.runSync(payloads.decodeRows(await runJson(payloads.sql)))
+				.map(Integrations.aiToolErrorPayload)
+				.map((row) => ({
+					spanId: row.spanId,
+					statusCode: row.statusCode,
+					arguments: row.arguments,
+					argumentsBytes: row.argumentsBytes,
+					resultBytes: row.resultBytes,
+				})),
 			[
 				{
 					spanId: "tools-flaky-1",
@@ -870,7 +882,9 @@ describe.skipIf(!clickhouseE2eEnabled)("agent tools reads", () => {
 			{ orgId: ORG_ID, ...slice },
 			{ rowSchema: Integrations.aiToolErrorPayloadsRowSchema },
 		)
-		const rows = Effect.runSync(payloads.decodeRows(await runJson(payloads.sql)))
+		const rows = Effect.runSync(payloads.decodeRows(await runJson(payloads.sql))).map(
+			Integrations.aiToolErrorPayload,
+		)
 		assert.deepStrictEqual(
 			[...rows]
 				.sort((a, b) => a.spanId.localeCompare(b.spanId))

packages/query-engine-integrations/src/__sql_baseline__/integrations.sql

@@ -1170,10 +1170,8 @@ SELECT
           TraceId AS traceId,
           SpanId AS spanId,
           StatusCode AS statusCode,
-          leftUTF8(coalesce(nullIf(SpanAttributes['gen_ai.tool.call.arguments'], ''), nullIf(SpanAttributes['ai.toolCall.args'], ''), ''), 4000) AS arguments,
-          length(coalesce(nullIf(SpanAttributes['gen_ai.tool.call.arguments'], ''), nullIf(SpanAttributes['ai.toolCall.args'], ''), '')) AS argumentsBytes,
-          leftUTF8(coalesce(nullIf(SpanAttributes['gen_ai.tool.call.result'], ''), nullIf(SpanAttributes['ai.toolCall.result'], ''), ''), 4000) AS result,
-          length(coalesce(nullIf(SpanAttributes['gen_ai.tool.call.result'], ''), nullIf(SpanAttributes['ai.toolCall.result'], ''), '')) AS resultBytes
+          mapApply((k, v) -> (k, leftUTF8(v, 16384)), mapFilter((k, v) -> (((k IN ('maple_ai.session.id', 'maple_ai.vendor.id', 'maple_ai.vendor.version', 'maple_ai.agent.name', 'gen_ai.operation.name', 'gen_ai.provider.name', 'gen_ai.system', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.request.choice.count', 'gen_ai.request.temperature', 'gen_ai.request.top_p', 'gen_ai.request.top_k', 'gen_ai.request.stop_sequences', 'gen_ai.request.frequency_penalty', 'gen_ai.request.presence_penalty', 'gen_ai.request.encoding_formats', 'gen_ai.request.seed', 'gen_ai.openai.request.seed', 'gen_ai.request.stream', 'gen_ai.request.reasoning.level', 'gen_ai.request.previous_response.id', 'gen_ai.request.stream_cursor', 'gen_ai.response.id', 'gen_ai.response.model', 'gen_ai.response.finish_reasons', 'gen_ai.response.finish_reason', 'gen_ai.response.status', 'gen_ai.response.time_to_first_chunk', 'gen_ai.output.type', 'gen_ai.usage.input_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.cache_read.input_tokens', 'gen_ai.usage.input_tokens.cached', 'gen_ai.usage.cache_creation.input_tokens', 'gen_ai.usage.cache_write.input_tokens', 'gen_ai.usage.output_tokens', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.reasoning.output_tokens', 'gen_ai.usage.output_tokens.reasoning', 'gen_ai.usage.cost', 'gen_ai.usage.total_cost', 'maple_ai.llm_call', 'maple_ai.tool_call', 'maple_ai.error', 'maple_ai.usage.input_tokens', 'maple_ai.usage.cache_read_tokens', 'maple_ai.usage.cache_write_tokens', 'maple_ai.usage.output_tokens', 'maple_ai.usage.reasoning_tokens', 'maple_ai.usage.cost', 'gen_ai.conversation.id', 'gen_ai.conversation.compacted', 'gen_ai.agent.id', 'gen_ai.agent.name', 'gen_ai.agent.description', 'gen_ai.agent.version', 'gen_ai.tool.name', 'gen_ai.tool.call.id', 'gen_ai.tool.description', 'gen_ai.tool.type', 'gen_ai.tool.call.arguments', 'gen_ai.tool.call.result', 'gen_ai.tool.definitions', 'gen_ai.system_instructions', 'gen_ai.input.messages', 'gen_ai.prompt', 'gen_ai.output.messages', 'gen_ai.completion', 'gen_ai.data_source.id', 'gen_ai.retrieval.query.text', 'gen_ai.retrieval.top_k', 'gen_ai.retrieval.documents', 'gen_ai.memory.store.id', 'gen_ai.memory.record.id', 'gen_ai.memory.record.count', 'gen_ai.memory.query.text', 'gen_ai.memory.records', 'gen_ai.embeddings.dimension.count', 'gen_ai.evaluation.name', 'gen_ai.evaluation.score.value', 'gen_ai.evaluation.score.label', 'gen_ai.evaluation.explanation', 'gen_ai.prompt.name', 'gen_ai.prompt.version', 'gen_ai.workflow.name', 'span.metadata.attempt_index', 'span.metadata.status_code', 'trace.metadata.openrouter.provider_name', 'error.type', 'server.address', 'server.port', 'ai.model.provider', 'ai.model.id', 'ai.response.id', 'ai.response.model', 'ai.response.finishReason', 'gen_ai.client.operation.time_to_first_chunk', 'ai.usage.inputTokens', 'ai.usage.promptTokens', 'ai.usage.cachedInputTokens', 'ai.usage.inputTokenDetails.cacheReadTokens', 'ai.usage.inputTokenDetails.cacheWriteTokens', 'ai.usage.outputTokens', 'ai.usage.completionTokens', 'ai.usage.reasoningTokens', 'ai.usage.outputTokenDetails.reasoningTokens', 'ai.telemetry.functionId', 'ai.toolCall.name', 'ai.toolCall.id', 'ai.toolCall.args', 'ai.toolCall.result', 'ai.prompt.tools', 'ai.prompt.messages', 'ai.prompt', 'llm.provider', 'llm.system', 'llm.model_name', 'llm.finish_reason', 'llm.token_count.prompt', 'llm.token_count.prompt_details.cache_read', 'llm.token_count.completion', 'llm.token_count.completion_details.reasoning', 'llm.cost.total', 'tool.name', 'tool.description', 'llm.tools', 'openinference.span.kind', 'tool.parameters', 'input.value', 'output.value', 'eve.turn.id', 'maple_ai.turn.id') OR k LIKE 'gen_ai.prompt.variable.%') OR k LIKE 'llm.input_messages.%') OR k LIKE 'llm.output_messages.%'), SpanAttributes)) AS spanAttributes,
+          mapApply((k, v) -> (k, length(v)), mapFilter((k, v) -> lengthUTF8(v) > 16384, mapFilter((k, v) -> (((k IN ('maple_ai.session.id', 'maple_ai.vendor.id', 'maple_ai.vendor.version', 'maple_ai.agent.name', 'gen_ai.operation.name', 'gen_ai.provider.name', 'gen_ai.system', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.request.choice.count', 'gen_ai.request.temperature', 'gen_ai.request.top_p', 'gen_ai.request.top_k', 'gen_ai.request.stop_sequences', 'gen_ai.request.frequency_penalty', 'gen_ai.request.presence_penalty', 'gen_ai.request.encoding_formats', 'gen_ai.request.seed', 'gen_ai.openai.request.seed', 'gen_ai.request.stream', 'gen_ai.request.reasoning.level', 'gen_ai.request.previous_response.id', 'gen_ai.request.stream_cursor', 'gen_ai.response.id', 'gen_ai.response.model', 'gen_ai.response.finish_reasons', 'gen_ai.response.finish_reason', 'gen_ai.response.status', 'gen_ai.response.time_to_first_chunk', 'gen_ai.output.type', 'gen_ai.usage.input_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.cache_read.input_tokens', 'gen_ai.usage.input_tokens.cached', 'gen_ai.usage.cache_creation.input_tokens', 'gen_ai.usage.cache_write.input_tokens', 'gen_ai.usage.output_tokens', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.reasoning.output_tokens', 'gen_ai.usage.output_tokens.reasoning', 'gen_ai.usage.cost', 'gen_ai.usage.total_cost', 'maple_ai.llm_call', 'maple_ai.tool_call', 'maple_ai.error', 'maple_ai.usage.input_tokens', 'maple_ai.usage.cache_read_tokens', 'maple_ai.usage.cache_write_tokens', 'maple_ai.usage.output_tokens', 'maple_ai.usage.reasoning_tokens', 'maple_ai.usage.cost', 'gen_ai.conversation.id', 'gen_ai.conversation.compacted', 'gen_ai.agent.id', 'gen_ai.agent.name', 'gen_ai.agent.description', 'gen_ai.agent.version', 'gen_ai.tool.name', 'gen_ai.tool.call.id', 'gen_ai.tool.description', 'gen_ai.tool.type', 'gen_ai.tool.call.arguments', 'gen_ai.tool.call.result', 'gen_ai.tool.definitions', 'gen_ai.system_instructions', 'gen_ai.input.messages', 'gen_ai.prompt', 'gen_ai.output.messages', 'gen_ai.completion', 'gen_ai.data_source.id', 'gen_ai.retrieval.query.text', 'gen_ai.retrieval.top_k', 'gen_ai.retrieval.documents', 'gen_ai.memory.store.id', 'gen_ai.memory.record.id', 'gen_ai.memory.record.count', 'gen_ai.memory.query.text', 'gen_ai.memory.records', 'gen_ai.embeddings.dimension.count', 'gen_ai.evaluation.name', 'gen_ai.evaluation.score.value', 'gen_ai.evaluation.score.label', 'gen_ai.evaluation.explanation', 'gen_ai.prompt.name', 'gen_ai.prompt.version', 'gen_ai.workflow.name', 'span.metadata.attempt_index', 'span.metadata.status_code', 'trace.metadata.openrouter.provider_name', 'error.type', 'server.address', 'server.port', 'ai.model.provider', 'ai.model.id', 'ai.response.id', 'ai.response.model', 'ai.response.finishReason', 'gen_ai.client.operation.time_to_first_chunk', 'ai.usage.inputTokens', 'ai.usage.promptTokens', 'ai.usage.cachedInputTokens', 'ai.usage.inputTokenDetails.cacheReadTokens', 'ai.usage.inputTokenDetails.cacheWriteTokens', 'ai.usage.outputTokens', 'ai.usage.completionTokens', 'ai.usage.reasoningTokens', 'ai.usage.outputTokenDetails.reasoningTokens', 'ai.telemetry.functionId', 'ai.toolCall.name', 'ai.toolCall.id', 'ai.toolCall.args', 'ai.toolCall.result', 'ai.prompt.tools', 'ai.prompt.messages', 'ai.prompt', 'llm.provider', 'llm.system', 'llm.model_name', 'llm.finish_reason', 'llm.token_count.prompt', 'llm.token_count.prompt_details.cache_read', 'llm.token_count.completion', 'llm.token_count.completion_details.reasoning', 'llm.cost.total', 'tool.name', 'tool.description', 'llm.tools', 'openinference.span.kind', 'tool.parameters', 'input.value', 'output.value', 'eve.turn.id', 'maple_ai.turn.id') OR k LIKE 'gen_ai.prompt.variable.%') OR k LIKE 'llm.input_messages.%') OR k LIKE 'llm.output_messages.%'), SpanAttributes))) AS cutAttributeBytes
         FROM trace_detail_spans
         WHERE OrgId = 'org_sql_catalog'
           AND Timestamp >= '2026-01-02 11:15:00.000000000'

packages/query-engine-integrations/src/ai/ai-integrations.ts

@@ -32,7 +32,6 @@ import { AI_VENDOR_INTEGRATIONS } from "./ai-vendors"
 import { isRecord, unwrapMessages, unwrapOutputMessages, unwrapToolMessage } from "./ai-messages"
 
 export interface AiRefineContext {
-	readonly row: AiSessionSpansOutput
 	/** The span's own attributes — the map the source key lists read. */
 	readonly attributes: Record<string, string>
 	/** One attribute decoded the way the mapper decodes `field`; `undefined`
@@ -348,16 +347,13 @@ export const AI_NON_SIGNAL_FIELDS: ReadonlySet<AiGenAiField> = new Set([...AI_CO
 const hasAiSignal = (values: MutableAiGenAiValues): boolean =>
 	Object.keys(values).some((field) => !AI_NON_SIGNAL_FIELDS.has(field as AiGenAiField))
 
-export const mapAiSpan = (row: AiSessionSpansOutput): AiAgentSpan => {
-	// Span attributes only, envelope and source keys alike. The gateway strips
-	// `maple_ai.*` from span attributes before stamping its own verdict, so a
-	// span-level value is authoritative — and it does not touch resource
-	// attributes, where one forged `gen_ai.*` or `maple_ai.*` key would mark
-	// every span in the service as an AI span.
-	const attributes = row.spanAttributes
-	const vendorId = readAttribute(attributes, MAPLE_AI_VENDOR_ID_ATTR)
+/** Every catalog field of one span, through the integration its vendor stamp
+ *  selects: the source keys in order, then the refine hooks. */
+const decodeGenAi = (
+	attributes: Record<string, string>,
+	vendorId: string | undefined,
+): MutableAiGenAiValues => {
 	const integration = resolveAiIntegration(vendorId)
-
 	// SAFETY: the catalog correlates each field with its value type, but a loop
 	// over the field union cannot carry that correlation. `decodeAttribute` is
 	// driven by the same catalog entry as the field it is written under, so the
@@ -377,11 +373,38 @@ export const mapAiSpan = (row: AiSessionSpansOutput): AiAgentSpan => {
 			break
 		}
 	}
-	integration.refine?.(genAi, { row, attributes, read })
+	integration.refine?.(genAi, { attributes, read })
 	// The agent the ingest gateway named, which the list and its facets show: it
 	// reads names no dialect key carries (OpenAI Agents' graph node).
 	const stampedAgent = readAttribute(attributes, MAPLE_AI_STAMP_ATTRS.agentName)
 	if (stampedAgent !== undefined) genAi.agentName = stampedAgent
+	return genAi
+}
+
+/**
+ * What a tool call was called with and what came back, decoded exactly as the
+ * session page decodes the span — so a view that reads one tool span on its
+ * own shows the payload the transcript shows: an OpenInference span's real
+ * `input.value` rather than the parameter schema its GenAI dual-write copied
+ * into `gen_ai.tool.call.arguments`, a LangChain `ToolMessage` unwrapped to
+ * its content. `undefined` where the span captured none.
+ */
+export const aiToolCallPayload = (
+	attributes: Record<string, string>,
+): { readonly arguments: unknown; readonly result: unknown } => {
+	const genAi = decodeGenAi(attributes, readAttribute(attributes, MAPLE_AI_VENDOR_ID_ATTR))
+	return { arguments: genAi.toolCallArguments, result: genAi.toolCallResult }
+}
+
+export const mapAiSpan = (row: AiSessionSpansOutput): AiAgentSpan => {
+	// Span attributes only, envelope and source keys alike. The gateway strips
+	// `maple_ai.*` from span attributes before stamping its own verdict, so a
+	// span-level value is authoritative — and it does not touch resource
+	// attributes, where one forged `gen_ai.*` or `maple_ai.*` key would mark
+	// every span in the service as an AI span.
+	const attributes = row.spanAttributes
+	const vendorId = readAttribute(attributes, MAPLE_AI_VENDOR_ID_ATTR)
+	const genAi = decodeGenAi(attributes, vendorId)
 
 	const promptVariables = collectPromptVariables(attributes)
 	const sessionId = readAttribute(attributes, MAPLE_AI_SESSION_ID_ATTR)