{
  "version": 3,
  "sources": ["../../src/app/ai/agents/evals2/harness/categoryStatistics.ts", "../../src/app/ai/agents/evals2/harness/reportSchemas.ts", "../../src/app/ai/agents/evals2/harness/tokenUsage.ts", "../../src/app/ai/agents/evals2/harness/jsonReport.ts", "../../src/app/ai/agents/evals2/harness/helpers.ts", "../../src/app/ai/agents/evals2/harness/passedAssertionCapture.ts", "../../src/app/ai/agents/evals2/harness/report.ts", "../../src/app/ai/agents/evals2/harness/scoring.ts", "../../src/app/ai/agents/evals2/harness/transcriptInput.ts", "../../src/app/ai/agents/evals2/harness/runner.ts", "../../src/app/ai/agents/evals2/harness/transcriptData.ts", "../../src/app/ai/agents/evals2/harness/uiAdapter.ts", "../../src/app/ai/agents/evals2/harness/browserRunner.ts", "../../src/app/ai/agents/evals2/harness/evalGlobals.ts", "../../src/app/ai/agents/evals2/harness/browserEvalGlobals.ts", "agent-evals-browser-manifest:/Users/alex/Projects/FramerStudio/src/app/vekter/src/app/ai/agents/evals2/harness/bundledEvalFiles.ts", "../../src/app/ai/agents/evals2/harness/definitionFilter.ts", "../../src/app/ai/agents/evals2/harness/importEvalDefinitions.ts", "../../src/app/ai/agents/evals2/harness/modelConfig.ts", "../../src/document/components/chrome/evaluations/evalDefinitions.ts", "../../src/document/components/chrome/evaluations/evalRunState.ts", "../../src/document/components/chrome/evaluations/evalRunner.ts"],
  "sourcesContent": ["import type { AgentEvalCategoryStatisticsByCategory } from \"./reportTypes.ts\"\n\ntype AgentEvalCategory = keyof AgentEvalCategoryStatisticsByCategory\n\nconst categories: Record<AgentEvalCategory, true> = {\n\tcorrectness: true,\n\taccuracy: true,\n\tefficiency: true,\n\tfunctionality: true,\n\tdesign: true,\n}\n\nexport const agentEvalCategories = Object.keys(categories) as readonly AgentEvalCategory[]\n\nexport function createEmptyAgentEvalCategoryStatistics(): AgentEvalCategoryStatisticsByCategory {\n\treturn {\n\t\tcorrectness: { passed: 0, failed: 0, total: 0 },\n\t\taccuracy: { passed: 0, failed: 0, total: 0 },\n\t\tefficiency: { passed: 0, failed: 0, total: 0 },\n\t\tfunctionality: { passed: 0, failed: 0, total: 0 },\n\t\tdesign: { passed: 0, failed: 0, total: 0 },\n\t}\n}\n", "import { isLanguageModel } from \"app/ai/languageModels.ts\"\nimport type { LanguageModel } from \"app/ai/languageModels.ts\"\nimport { isAgentReasoningEffort, type AgentReasoningEffort } from \"app/ai/models.ts\"\nimport { z } from \"zod\"\n\nconst agentEvalCheckCategories = [\"correctness\", \"accuracy\", \"efficiency\", \"functionality\", \"design\"] as const\nexport const agentEvalCheckCategorySchema = z.enum(agentEvalCheckCategories)\nexport const agentEvalCheckKindSchema = z.enum([\"required\", \"forbidden\", \"scored\", \"diagnostic\"])\n\nconst agentEvalCategoryStatisticsSchema = z.object({\n\tpassed: z.number(),\n\tfailed: z.number(),\n\ttotal: z.number(),\n})\n\nexport const agentEvalCategoryStatisticsByCategorySchema = z.record(\n\tagentEvalCheckCategorySchema,\n\tagentEvalCategoryStatisticsSchema,\n)\n\nexport const agentEvalCallbackStatisticsSchema = z.object({\n\texecutedWithoutThrow: z.number(),\n\texecuted: z.number(),\n\tthrew: z.number(),\n\tpassed: z.number(),\n\tfailed: z.number(),\n\ttotal: z.number(),\n})\n\nexport const agentEvalCheckResultSchema = z.object({\n\tid: z.string(),\n\tcategory: agentEvalCheckCategorySchema,\n\tkind: agentEvalCheckKindSchema.optional(),\n\tname: z.string(),\n\tgroup: z.string().optional(),\n\titem: z.string().optional(),\n\tpassed: z.boolean(),\n\tscore: z.number().min(0).max(1).optional(),\n\tmessage: z.string().optional(),\n\tassertion: z.string().optional(),\n\tachievedStep: z.number().optional(),\n\terror: z.string().optional(),\n\texpected: z.string().optional(),\n\treceived: z.string().optional(),\n\tmatcher: z.string().optional(),\n\terrorStack: z.string().optional(),\n\tdurationMs: z.number(),\n})\n\nconst agentEvalRunStatusSchema = z.enum([\"passed\", \"failed\", \"error\", \"stopped\"])\n\nexport const agentEvalRunStatisticsSchema = z.object({\n\tdurationMs: z.number(),\n\ttotalToolSteps: z.number(),\n\tearlyStopped: z.boolean(),\n\tstopStep: z.number().optional(),\n\tcategories: agentEvalCategoryStatisticsByCategorySchema,\n\tcallbacks: agentEvalCallbackStatisticsSchema,\n})\n\nexport const agentEvalTokenUsageSchema = z.object({\n\tinputTokens: z.number().optional(),\n\toutputTokens: z.number().optional(),\n\ttotalTokens: z.number().optional(),\n\treasoningTokens: z.number().optional(),\n})\n\nexport const agentEvalRunResultSchema = z.object({\n\tevalId: z.string(),\n\tfixtureId: z.string(),\n\tname: z.string(),\n\tsourceFile: z.string(),\n\tmodel: z.custom<LanguageModel>(isLanguageModel),\n\treasoningEffort: z.custom<AgentReasoningEffort>(isAgentReasoningEffort).optional(),\n\trunNumber: z.number(),\n\tstatus: agentEvalRunStatusSchema,\n\tscore: z.number().min(0).max(1).optional(),\n\tdurationMs: z.number(),\n\tcost: z.number(),\n\ttokenUsage: agentEvalTokenUsageSchema.optional(),\n\ttotalToolSteps: z.number(),\n\ttoolStepNames: z.array(z.string()).optional(),\n\tstatistics: agentEvalRunStatisticsSchema,\n\tchecks: z.array(agentEvalCheckResultSchema),\n\terror: z.string().optional(),\n\ttranscriptPath: z.string().optional(),\n\terrorStack: z.string().optional(),\n})\n\nconst agentEvalReportSummarySchema = z.object({\n\ttotalRuns: z.number(),\n\tpassedRuns: z.number(),\n\tfailedRuns: z.number(),\n\terrorRuns: z.number(),\n\tstoppedRuns: z.number().default(0),\n\tscore: z.number().min(0).max(1).default(0),\n\tdurationMs: z.number(),\n\tcost: z.number(),\n\ttokenUsage: agentEvalTokenUsageSchema.optional(),\n\ttotalToolSteps: z.number(),\n\ttotalChecks: z.number(),\n\tpassedChecks: z.number(),\n\tfailedChecks: z.number(),\n\tcategories: agentEvalCategoryStatisticsByCategorySchema,\n\tcallbacks: agentEvalCallbackStatisticsSchema,\n})\n\nexport const agentEvalJsonReportSchema = z.object({\n\tschemaVersion: z.literal(1),\n\tgeneratedAt: z.string(),\n\tevaluatedSha: z.string().optional(),\n\tsummary: agentEvalReportSummarySchema,\n\tresults: z.array(agentEvalRunResultSchema),\n})\n", "import type { LanguageModelUsage } from \"ai\"\nimport type { z } from \"zod\"\nimport type { agentEvalTokenUsageSchema } from \"./reportSchemas.ts\"\n\nexport type AgentEvalTokenUsage = z.infer<typeof agentEvalTokenUsageSchema>\n\nexport function toAgentEvalTokenUsage(usage: LanguageModelUsage | undefined): AgentEvalTokenUsage | undefined {\n\tif (usage === undefined) return undefined\n\n\tconst { inputTokens, outputTokens, totalTokens, outputTokenDetails, reasoningTokens } = usage\n\n\tconst tokenUsage: AgentEvalTokenUsage = {\n\t\tinputTokens,\n\t\toutputTokens,\n\t\ttotalTokens,\n\t\treasoningTokens: reasoningTokens ?? outputTokenDetails?.reasoningTokens,\n\t}\n\n\treturn tokenUsage\n}\n\nexport function aggregateAgentEvalTokenUsage(\n\tleft: AgentEvalTokenUsage | undefined,\n\tright: AgentEvalTokenUsage | undefined,\n): AgentEvalTokenUsage | undefined {\n\tif (left === undefined && right === undefined) return undefined\n\n\treturn {\n\t\tinputTokens: sumOptionalTokenCount(left?.inputTokens, right?.inputTokens),\n\t\toutputTokens: sumOptionalTokenCount(left?.outputTokens, right?.outputTokens),\n\t\ttotalTokens: sumOptionalTokenCount(left?.totalTokens, right?.totalTokens),\n\t\treasoningTokens: sumOptionalTokenCount(left?.reasoningTokens, right?.reasoningTokens),\n\t}\n}\n\nfunction sumOptionalTokenCount(left: number | undefined, right: number | undefined): number | undefined {\n\tif (left === undefined && right === undefined) return undefined\n\treturn (left ?? 0) + (right ?? 0)\n}\n\nfunction formatTokenCount(count: number): string {\n\tif (count >= 1_000_000) return `${(count / 1_000_000).toFixed(1)}M`\n\tif (count >= 10_000) return `${Math.round(count / 1_000)}k`\n\tif (count >= 1_000) return `${(count / 1_000).toFixed(1)}k`\n\treturn count.toLocaleString(\"en-US\")\n}\n\nexport function formatTokenUsage(usage: AgentEvalTokenUsage | undefined): string {\n\tif (usage === undefined) return \"-\"\n\n\tconst parts: string[] = []\n\tif (usage.inputTokens !== undefined) parts.push(`${formatTokenCount(usage.inputTokens)} in`)\n\tif (usage.outputTokens !== undefined) parts.push(`${formatTokenCount(usage.outputTokens)} out`)\n\tif (parts.length > 0) {\n\t\tif (usage.reasoningTokens !== undefined && usage.reasoningTokens > 0) {\n\t\t\tparts.push(`${formatTokenCount(usage.reasoningTokens)} reasoning`)\n\t\t}\n\t\treturn parts.join(\" / \")\n\t}\n\n\tif (usage.totalTokens !== undefined) return `${formatTokenCount(usage.totalTokens)} tokens`\n\treturn \"-\"\n}\n", "import { z } from \"zod\"\nimport { agentEvalCategories, createEmptyAgentEvalCategoryStatistics } from \"./categoryStatistics.ts\"\nimport type { AgentEvalJsonReport } from \"./jsonReportTypes.ts\"\nimport { agentEvalJsonReportSchema } from \"./reportSchemas.ts\"\nimport type { AgentEvalCallbackStatistics } from \"./reportTypes.ts\"\nimport { aggregateAgentEvalTokenUsage } from \"./tokenUsage.ts\"\nimport type { AgentEvalTokenUsage } from \"./tokenUsage.ts\"\nimport type { AgentEvalRunResult } from \"./types.ts\"\n\ninterface AgentEvalJsonReportOptions {\n\tevaluatedSha?: string\n}\n\nfunction createEmptyCallbackStatistics(): AgentEvalCallbackStatistics {\n\treturn {\n\t\texecutedWithoutThrow: 0,\n\t\texecuted: 0,\n\t\tthrew: 0,\n\t\tpassed: 0,\n\t\tfailed: 0,\n\t\ttotal: 0,\n\t}\n}\n\nexport function createAgentEvalJsonReport(\n\tresults: readonly AgentEvalRunResult[],\n\toptions: AgentEvalJsonReportOptions = {},\n): AgentEvalJsonReport {\n\tconst categoryStatistics = createEmptyAgentEvalCategoryStatistics()\n\tconst callbacks = createEmptyCallbackStatistics()\n\tlet durationMs = 0\n\tlet cost = 0\n\tlet tokenUsage: AgentEvalTokenUsage | undefined\n\tlet totalToolSteps = 0\n\tlet totalChecks = 0\n\tlet passedChecks = 0\n\tlet failedChecks = 0\n\tlet passedRuns = 0\n\tlet failedRuns = 0\n\tlet errorRuns = 0\n\tlet stoppedRuns = 0\n\tlet score = 0\n\n\tfor (const result of results) {\n\t\tdurationMs += result.statistics.durationMs\n\t\tcost += result.cost\n\t\ttokenUsage = aggregateAgentEvalTokenUsage(tokenUsage, result.tokenUsage)\n\t\ttotalToolSteps += result.statistics.totalToolSteps\n\t\tscore += result.score ?? 0\n\t\ttotalChecks += result.statistics.callbacks.total\n\t\tpassedChecks += result.statistics.callbacks.passed\n\t\tfailedChecks += result.statistics.callbacks.failed\n\t\tif (result.status === \"passed\") passedRuns++\n\t\tif (result.status === \"failed\") failedRuns++\n\t\tif (result.status === \"error\") errorRuns++\n\t\tif (result.status === \"stopped\") stoppedRuns++\n\n\t\tfor (const category of agentEvalCategories) {\n\t\t\tcategoryStatistics[category].passed += result.statistics.categories[category].passed\n\t\t\tcategoryStatistics[category].failed += result.statistics.categories[category].failed\n\t\t\tcategoryStatistics[category].total += result.statistics.categories[category].total\n\t\t}\n\n\t\tcallbacks.executedWithoutThrow += result.statistics.callbacks.executedWithoutThrow\n\t\tcallbacks.executed += result.statistics.callbacks.executed\n\t\tcallbacks.threw += result.statistics.callbacks.threw\n\t\tcallbacks.passed += result.statistics.callbacks.passed\n\t\tcallbacks.failed += result.statistics.callbacks.failed\n\t\tcallbacks.total += result.statistics.callbacks.total\n\t}\n\n\tconst report: AgentEvalJsonReport = {\n\t\tschemaVersion: 1,\n\t\tgeneratedAt: new Date().toISOString(),\n\t\tsummary: {\n\t\t\ttotalRuns: results.length,\n\t\t\tpassedRuns,\n\t\t\tfailedRuns,\n\t\t\terrorRuns,\n\t\t\tstoppedRuns,\n\t\t\tscore: results.length === 0 ? 0 : score / results.length,\n\t\t\tdurationMs,\n\t\t\tcost,\n\t\t\ttokenUsage,\n\t\t\ttotalToolSteps,\n\t\t\ttotalChecks,\n\t\t\tpassedChecks,\n\t\t\tfailedChecks,\n\t\t\tcategories: categoryStatistics,\n\t\t\tcallbacks,\n\t\t},\n\t\tresults: [...results],\n\t\tevaluatedSha: options.evaluatedSha,\n\t}\n\treturn report\n}\n\nexport function parseAgentEvalJsonReport(raw: string, filePath: string): AgentEvalJsonReport {\n\tconst parsed: unknown = JSON.parse(raw)\n\tconst report = agentEvalJsonReportSchema.safeParse(parsed)\n\tif (report.success) return report.data\n\tthrow new Error(`Unsupported agent eval JSON report: ${filePath}\\n${z.prettifyError(report.error)}`)\n}\n", "import { assert } from \"@framerjs/shared\"\nimport type { Agent } from \"app/ai/agents/Agent.ts\"\nimport { type CommandType, isCommand, type Command } from \"app/ai/agents/dsl.ts\"\nimport { isAssistantToolCallPart, isCommandError, isDesignPlan } from \"app/ai/agents/messages.ts\"\nimport type { CommandError, ToolStep } from \"app/ai/agents/messages.ts\"\nimport type { ClarificationQuestion } from \"app/ai/agents/tools/askClarification.ts\"\nimport type { ReadProjectQuery } from \"app/ai/agents/tools/readProject.ts\"\nimport { isReviewChangesToolResponseValue, type ReviewChangesResponse } from \"app/ai/agents/tools/reviewChanges.ts\"\nimport type { AgentScriptRecordedCall } from \"app/ai/agents/tools/script/bridge.ts\"\nimport {\n\tASK_CLARIFICATION_TOOL_NAME,\n\tREAD_PROJECT_TOOL_NAME,\n\tREVIEW_CHANGES_TOOL_NAME,\n\tSCRIPT_TOOL_NAME,\n} from \"app/ai/agents/tools/toolNames.ts\"\nimport type { AgentTypedToolCall, AgentTypedToolResult } from \"app/ai/agents/tools/toolSet.ts\"\nimport type { AgentRequest } from \"app/ai/agents/types.ts\"\nimport type { NodeID } from \"document/models/CanvasTree/nodes/NodeID.ts\"\nimport { isObject } from \"utils/typeChecks.ts\"\nimport type { AgentEvalReport } from \"./reportTypes.ts\"\n\nconst PROJECT_MUTATION_SCRIPT_PATTERN = /\\bapi\\.updateProject\\s*\\(/u\n\nexport type AgentEvalStepPart = ToolStep[\"content\"][number]\n\nexport interface AgentEvalPartPosition {\n\tstepIndex: number\n\tpartIndex: number\n}\n\nexport interface AgentEvalPositionedPart {\n\tposition: AgentEvalPartPosition\n\tpart: AgentEvalStepPart\n}\n\nexport type AgentEvalToolCallName = AgentTypedToolCall[\"toolName\"]\nexport type AgentEvalToolCallForName<TName extends AgentEvalToolCallName> = Extract<\n\tAgentTypedToolCall,\n\t{ toolName: TName }\n>\ntype AgentEvalToolInputForName<TName extends AgentEvalToolCallName> =\n\tAgentEvalToolCallForName<TName> extends {\n\t\tinput: infer TInput\n\t}\n\t\t? TInput\n\t\t: never\n\nexport type AgentEvalToolResult = AgentTypedToolResult & {\n\tstepIndex: number\n}\n\nexport type AgentEvalToolResultName = AgentTypedToolResult[\"toolName\"]\nexport type AgentEvalToolResultForName<TName extends AgentEvalToolResultName> = Extract<\n\tAgentTypedToolResult,\n\t{ toolName: TName }\n> & {\n\tstepIndex: number\n}\nexport type AgentEvalScriptCallMethod = AgentScriptRecordedCall[\"method\"]\nexport type AgentEvalScriptCallForMethod<TMethod extends AgentEvalScriptCallMethod> = Extract<\n\tAgentScriptRecordedCall,\n\t{ method: TMethod }\n>\nexport type AgentEvalPositionedScriptCall = AgentScriptRecordedCall & {\n\tposition: AgentEvalPartPosition\n\t/** entire script in which the call occurred */\n\tscript: string\n}\nexport type AgentEvalPositionedScriptCallForMethod<TMethod extends AgentEvalScriptCallMethod> =\n\tAgentEvalScriptCallForMethod<TMethod> & {\n\t\tposition: AgentEvalPartPosition\n\t\t/** entire script in which the call occurred */\n\t\tscript: string\n\t}\n\nexport interface AgentEvalScriptRunInstrumentation {\n\tcallCount: number\n}\n\nexport interface AgentEvalScriptInstrumentationState {\n\tcalls: AgentScriptRecordedCall[]\n}\n\nexport interface AgentEvalClarificationQuestionGroup {\n\tstepIndex: number\n\tquestions: readonly ClarificationQuestion[]\n}\n\n/**\n * Generic transcript queries for an eval run.\n *\n * Keep this layer about the agent transcript itself: ordered step parts, tool-call positions, and\n * command/script mutation boundaries. Fixture-specific document assertions should live in scenario\n * helpers instead of growing the harness API.\n */\nexport interface AgentEvalStepsHelper {\n\tall(): readonly ToolStep[]\n\tlast(): ToolStep | undefined\n\tparts(): readonly AgentEvalPositionedPart[]\n\tdesignPlans(): readonly string[]\n\tfirstDesignPlanPosition(): AgentEvalPartPosition | undefined\n\treadProjectQueries(predicate?: (query: ReadProjectQuery) => boolean): readonly ReadProjectQuery[]\n\tfirstPartPosition(\n\t\tpredicate: (part: AgentEvalStepPart, position: AgentEvalPartPosition) => boolean,\n\t): AgentEvalPartPosition | undefined\n\tfirstToolCallPosition<TName extends AgentEvalToolCallName>(\n\t\tname: TName,\n\t\tpredicate?: (call: AgentEvalToolCallForName<TName>, position: AgentEvalPartPosition) => boolean,\n\t): AgentEvalPartPosition | undefined\n\tfirstReadProjectQueryPosition(predicate: (query: ReadProjectQuery) => boolean): AgentEvalPartPosition | undefined\n\tfirstScriptPosition(predicate: (script: string) => boolean): AgentEvalPartPosition | undefined\n\tfirstProjectMutationPosition(): AgentEvalPartPosition | undefined\n\thasPartAtOrBefore(\n\t\tposition: AgentEvalPartPosition,\n\t\tpredicate: (part: AgentEvalStepPart, position: AgentEvalPartPosition) => boolean,\n\t): boolean\n\thasReadProjectQueryAtOrBefore(\n\t\tposition: AgentEvalPartPosition,\n\t\tpredicate: (query: ReadProjectQuery) => boolean,\n\t): boolean\n\tcomparePositions(left: AgentEvalPartPosition, right: AgentEvalPartPosition): number\n\texpectBefore(left: AgentEvalPartPosition | undefined, right: AgentEvalPartPosition | undefined): void\n\texpectNoReviewBeforeMutation(): void\n}\n\n/**\n * Generic tool transcript queries for an eval run.\n *\n * The low-level methods (`calls`, `results`, `inputs`, `firstCall`) work for every agent tool. The\n * named conveniences below cover high-frequency eval assertions while still staying transcript-only.\n */\nexport interface AgentEvalToolsHelper {\n\tcalls(): readonly AgentTypedToolCall[]\n\tcalls<TName extends AgentEvalToolCallName>(name: TName): readonly AgentEvalToolCallForName<TName>[]\n\tresults(): readonly AgentEvalToolResult[]\n\tresults<TName extends AgentEvalToolResultName>(name: TName): readonly AgentEvalToolResultForName<TName>[]\n\tinputs<TName extends AgentEvalToolCallName>(name: TName): readonly AgentEvalToolInputForName<TName>[]\n\tfirstCall<TName extends AgentEvalToolCallName>(\n\t\tname: TName,\n\t\tpredicate?: (call: AgentEvalToolCallForName<TName>) => boolean,\n\t): AgentEvalToolCallForName<TName> | undefined\n\thasCall<TName extends AgentEvalToolCallName>(\n\t\tname: TName,\n\t\tpredicate?: (call: AgentEvalToolCallForName<TName>) => boolean,\n\t): boolean\n\tfirstResult<TName extends AgentEvalToolResultName>(\n\t\tname: TName,\n\t\tpredicate?: (result: AgentEvalToolResultForName<TName>) => boolean,\n\t): AgentEvalToolResultForName<TName> | undefined\n\thasResult<TName extends AgentEvalToolResultName>(\n\t\tname: TName,\n\t\tpredicate?: (result: AgentEvalToolResultForName<TName>) => boolean,\n\t): boolean\n\treadProjectQueries(predicate?: (query: ReadProjectQuery) => boolean): readonly ReadProjectQuery[]\n\treadProjectResults(\n\t\tpredicate?: (query: ReadProjectQuery) => boolean,\n\t): readonly AgentEvalToolResultForName<typeof READ_PROJECT_TOOL_NAME>[]\n\tfirstReadProjectResult(\n\t\tpredicate?: (query: ReadProjectQuery) => boolean,\n\t): AgentEvalToolResultForName<typeof READ_PROJECT_TOOL_NAME> | undefined\n\thasReadProjectQuery(predicate: (query: ReadProjectQuery) => boolean): boolean\n\tscriptInputs(predicate?: (script: string) => boolean): readonly string[]\n\tscriptCalls(): readonly AgentEvalPositionedScriptCall[]\n\tscriptCalls<TMethod extends AgentEvalScriptCallMethod>(\n\t\tmethod: TMethod,\n\t\tpredicate?: (call: AgentEvalPositionedScriptCallForMethod<TMethod>) => boolean,\n\t): readonly AgentEvalPositionedScriptCallForMethod<TMethod>[]\n\thasScriptCall<TMethod extends AgentEvalScriptCallMethod>(\n\t\tmethod: TMethod,\n\t\tpredicate?: (call: AgentEvalPositionedScriptCallForMethod<TMethod>) => boolean,\n\t): boolean\n\tnodeLookups(idOrPredicate: NodeID | ((id: NodeID) => boolean)): readonly AgentEvalPositionedScriptCall[]\n\tfirstNodeLookup(idOrPredicate: NodeID | ((id: NodeID) => boolean)): AgentEvalPositionedScriptCall | undefined\n\thasNodeLookup(idOrPredicate: NodeID | ((id: NodeID) => boolean)): boolean\n\tclarificationQuestions(): readonly AgentEvalClarificationQuestionGroup[]\n\tclarificationQuestionText(): string\n\tcommandErrors(): readonly CommandError[]\n\treviewChangesResults(): readonly ReviewChangesResponse[]\n\treportNoReadProject(report: AgentEvalReport): void\n\treportNoReviewBeforeMutation(report: AgentEvalReport): void\n\treportReplayContinued(report: AgentEvalReport, options: AgentEvalReplayContinuedOptions): void\n\treportReplayChecks(report: AgentEvalReport, options?: AgentEvalReplayChecksOptions): void\n}\n\nexport interface AgentEvalCommandsHelper {\n\tall(): readonly Command[]\n\tfirst(): Command | undefined\n\tbyType<T extends CommandType>(type: T): readonly Extract<Command, { type: T }>[]\n}\n\ninterface AgentEvalHelpers {\n\tsteps: AgentEvalStepsHelper\n\ttools: AgentEvalToolsHelper\n\tcommands: AgentEvalCommandsHelper\n}\n\ninterface AgentEvalHelperSource {\n\tagent: Pick<Agent, \"chatMessages\">\n\tcurrent?: {\n\t\trequest: AgentRequest\n\t}\n\trequestStartIndex?: number\n\tscriptInstrumentationState?: AgentEvalScriptInstrumentationState\n}\n\nexport interface AgentEvalReplayChecksOptions {\n\trequestId?: string\n\tstepIndex?: number\n\tforbidReadProject?: boolean\n}\n\nexport interface AgentEvalReplayContinuedOptions {\n\trequestId?: string\n\tstepIndex?: number\n}\n\nfunction getLatestRequest(source: AgentEvalHelperSource): AgentRequest | undefined {\n\treturn source.current?.request ?? source.agent.chatMessages.at(-1)\n}\n\nfunction getHelperRequests(source: AgentEvalHelperSource): readonly AgentRequest[] {\n\tconst requestStartIndex = source.requestStartIndex\n\tif (requestStartIndex === undefined) {\n\t\tconst request = getLatestRequest(source)\n\t\treturn request === undefined ? [] : [request]\n\t}\n\n\tconst requests = source.agent.chatMessages.slice(requestStartIndex)\n\tconst currentRequest = source.current?.request\n\tif (currentRequest === undefined || requests.includes(currentRequest)) return requests\n\treturn [...requests, currentRequest]\n}\n\nfunction isClarificationQuestion(value: unknown): value is ClarificationQuestion {\n\tif (!isObject(value)) return false\n\tif (typeof value.question !== \"string\") return false\n\tif (!Array.isArray(value.suggestedAnswers)) return false\n\treturn value.suggestedAnswers.every(answer => {\n\t\treturn (\n\t\t\ttypeof answer === \"string\" ||\n\t\t\t(isObject(answer) && typeof answer.answer === \"string\" && typeof answer.description === \"string\")\n\t\t)\n\t})\n}\n\nfunction formatClarificationQuestionText(questions: readonly ClarificationQuestion[]): string {\n\treturn questions\n\t\t.map(question => question.question)\n\t\t.join(\" \")\n\t\t.toLowerCase()\n}\n\nfunction getClarificationQuestionsFromInput(input: unknown): readonly ClarificationQuestion[] {\n\tif (!isObject(input) || !Array.isArray(input.questions)) return []\n\treturn input.questions.filter(isClarificationQuestion)\n}\n\nfunction collectClarificationQuestions(steps: readonly ToolStep[]): readonly AgentEvalClarificationQuestionGroup[] {\n\tconst clarificationQuestions: AgentEvalClarificationQuestionGroup[] = []\n\tfor (const { part, position } of getPositionedParts(steps)) {\n\t\tif (!isAssistantToolCallPart(part) || !isToolCallForName(part.content, ASK_CLARIFICATION_TOOL_NAME)) continue\n\t\tclarificationQuestions.push({\n\t\t\tstepIndex: position.stepIndex,\n\t\t\tquestions: getClarificationQuestionsFromInput(part.content.input),\n\t\t})\n\t}\n\treturn clarificationQuestions\n}\n\nfunction getReadProjectQueries(input: unknown): readonly ReadProjectQuery[] {\n\tif (!isObject(input) || !Array.isArray(input.queries)) return []\n\treturn input.queries.filter((query): query is ReadProjectQuery => isObject(query) && typeof query.type === \"string\")\n}\n\nfunction getPositionedParts(steps: readonly ToolStep[]): readonly AgentEvalPositionedPart[] {\n\tconst positionedParts: AgentEvalPositionedPart[] = []\n\tfor (let stepIndex = 0; stepIndex < steps.length; stepIndex++) {\n\t\tconst step = steps[stepIndex]\n\t\tassert(step !== undefined, `Expected eval step ${stepIndex} to exist.`)\n\t\tfor (let partIndex = 0; partIndex < step.content.length; partIndex++) {\n\t\t\tconst part = step.content[partIndex]\n\t\t\tassert(part !== undefined, `Expected eval step part ${stepIndex}:${partIndex} to exist.`)\n\t\t\tpositionedParts.push({ position: { stepIndex, partIndex }, part })\n\t\t}\n\t}\n\treturn positionedParts\n}\n\nfunction comparePartPositions(left: AgentEvalPartPosition, right: AgentEvalPartPosition): number {\n\treturn left.stepIndex - right.stepIndex || left.partIndex - right.partIndex\n}\n\nfunction getReadProjectQueriesFromPart(part: AgentEvalStepPart): readonly ReadProjectQuery[] {\n\tif (!isAssistantToolCallPart(part) || part.content.toolName !== READ_PROJECT_TOOL_NAME) return []\n\treturn getReadProjectQueries(part.content.input)\n}\n\nfunction getScriptInput(part: AgentEvalStepPart): string | undefined {\n\tif (!isAssistantToolCallPart(part) || part.content.toolName !== SCRIPT_TOOL_NAME) return undefined\n\treturn part.content.input.script\n}\n\nfunction isProjectMutationPart(part: AgentEvalStepPart): boolean {\n\tconst script = getScriptInput(part)\n\treturn Array.isArray(part) || (script !== undefined && PROJECT_MUTATION_SCRIPT_PATTERN.test(script))\n}\n\nfunction collectReadProjectQueriesFromSteps(\n\tsteps: readonly ToolStep[],\n\tpredicate: (query: ReadProjectQuery) => boolean = () => true,\n): readonly ReadProjectQuery[] {\n\tconst queries: ReadProjectQuery[] = []\n\tfor (const step of steps) {\n\t\tfor (const part of step.content) {\n\t\t\tfor (const query of getReadProjectQueriesFromPart(part)) {\n\t\t\t\tif (predicate(query)) queries.push(query)\n\t\t\t}\n\t\t}\n\t}\n\treturn queries\n}\n\nfunction collectCommandParts(steps: readonly ToolStep[]): {\n\tcommands: readonly Command[]\n\terrors: readonly CommandError[]\n} {\n\tconst commands: Command[] = []\n\tconst errors: CommandError[] = []\n\tfor (const step of steps) {\n\t\tfor (const part of step.content) {\n\t\t\tif (!Array.isArray(part)) continue\n\t\t\tfor (const line of part) {\n\t\t\t\tif (isCommand(line)) commands.push(line)\n\t\t\t\tif (isCommandError(line)) errors.push(line)\n\t\t\t}\n\t\t}\n\t}\n\treturn { commands, errors }\n}\n\nfunction isToolCallForName<TName extends AgentEvalToolCallName>(\n\tcall: AgentTypedToolCall,\n\tname: TName,\n): call is AgentEvalToolCallForName<TName> {\n\treturn call.toolName === name\n}\n\nfunction isToolResultForName<TName extends AgentEvalToolResultName>(\n\tresult: AgentTypedToolResult,\n\tname: TName,\n): result is Extract<AgentTypedToolResult, { toolName: TName }> {\n\treturn result.toolName === name\n}\n\nfunction addStepIndex<TToolResult extends AgentTypedToolResult>(\n\tresult: TToolResult,\n\tstepIndex: number,\n): TToolResult & { stepIndex: number } {\n\treturn { ...result, stepIndex }\n}\n\nfunction collectToolCalls(steps: readonly ToolStep[]): readonly AgentTypedToolCall[]\nfunction collectToolCalls<TName extends AgentEvalToolCallName>(\n\tsteps: readonly ToolStep[],\n\tname: TName,\n): readonly AgentEvalToolCallForName<TName>[]\nfunction collectToolCalls<TName extends AgentEvalToolCallName>(\n\tsteps: readonly ToolStep[],\n\tname?: TName,\n): readonly AgentTypedToolCall[] | readonly AgentEvalToolCallForName<TName>[] {\n\tconst calls: AgentTypedToolCall[] = []\n\tfor (const step of steps) {\n\t\tfor (const part of step.content) {\n\t\t\tif (!isAssistantToolCallPart(part)) continue\n\t\t\tif (name !== undefined && !isToolCallForName(part.content, name)) continue\n\t\t\tcalls.push(part.content)\n\t\t}\n\t}\n\treturn calls\n}\n\nfunction collectToolResults(steps: readonly ToolStep[]): readonly AgentEvalToolResult[]\nfunction collectToolResults<TName extends AgentEvalToolResultName>(\n\tsteps: readonly ToolStep[],\n\tname: TName,\n): readonly AgentEvalToolResultForName<TName>[]\nfunction collectToolResults<TName extends AgentEvalToolResultName>(\n\tsteps: readonly ToolStep[],\n\tname?: TName,\n): readonly AgentEvalToolResult[] | readonly AgentEvalToolResultForName<TName>[] {\n\tif (name === undefined) {\n\t\tconst results: AgentEvalToolResult[] = []\n\t\tfor (let stepIndex = 0; stepIndex < steps.length; stepIndex++) {\n\t\t\tconst step = steps[stepIndex]\n\t\t\tassert(step !== undefined, `Expected eval step ${stepIndex} to exist.`)\n\t\t\tfor (const result of step.toolResults) {\n\t\t\t\tresults.push(addStepIndex(result, stepIndex))\n\t\t\t}\n\t\t}\n\t\treturn results\n\t}\n\n\tconst results: AgentEvalToolResultForName<TName>[] = []\n\tfor (let stepIndex = 0; stepIndex < steps.length; stepIndex++) {\n\t\tconst step = steps[stepIndex]\n\t\tassert(step !== undefined, `Expected eval step ${stepIndex} to exist.`)\n\t\tfor (const result of step.toolResults) {\n\t\t\tif (!isToolResultForName(result, name)) continue\n\t\t\tresults.push(addStepIndex(result, stepIndex))\n\t\t}\n\t}\n\treturn results\n}\n\nfunction createToolCallsHelper(getSteps: () => readonly ToolStep[]): AgentEvalToolsHelper[\"calls\"] {\n\tfunction calls(): readonly AgentTypedToolCall[]\n\tfunction calls<TName extends AgentEvalToolCallName>(name: TName): readonly AgentEvalToolCallForName<TName>[]\n\tfunction calls<TName extends AgentEvalToolCallName>(\n\t\tname?: TName,\n\t): readonly AgentTypedToolCall[] | readonly AgentEvalToolCallForName<TName>[] {\n\t\tif (name === undefined) return collectToolCalls(getSteps())\n\t\treturn collectToolCalls(getSteps(), name)\n\t}\n\treturn calls\n}\n\nfunction createToolResultsHelper(getSteps: () => readonly ToolStep[]): AgentEvalToolsHelper[\"results\"] {\n\tfunction results(): readonly AgentEvalToolResult[]\n\tfunction results<TName extends AgentEvalToolResultName>(name: TName): readonly AgentEvalToolResultForName<TName>[]\n\tfunction results<TName extends AgentEvalToolResultName>(\n\t\tname?: TName,\n\t): readonly AgentEvalToolResult[] | readonly AgentEvalToolResultForName<TName>[] {\n\t\tif (name === undefined) return collectToolResults(getSteps())\n\t\treturn collectToolResults(getSteps(), name)\n\t}\n\treturn results\n}\n\nfunction createToolInputsHelper(getSteps: () => readonly ToolStep[]): AgentEvalToolsHelper[\"inputs\"] {\n\treturn function inputs<TName extends AgentEvalToolCallName>(\n\t\tname: TName,\n\t): readonly AgentEvalToolInputForName<TName>[] {\n\t\tconst toolInputs: AgentEvalToolInputForName<TName>[] = []\n\t\tfor (const call of collectToolCalls(getSteps(), name)) {\n\t\t\t// collectToolCalls filters by the same name, but TypeScript cannot keep that\n\t\t\t// relationship through the generic union of all typed tool inputs.\n\t\t\ttoolInputs.push(call.input as AgentEvalToolInputForName<TName>)\n\t\t}\n\t\treturn toolInputs\n\t}\n}\n\nfunction createFirstToolCallHelper(getSteps: () => readonly ToolStep[]): AgentEvalToolsHelper[\"firstCall\"] {\n\treturn function firstCall<TName extends AgentEvalToolCallName>(\n\t\tname: TName,\n\t\tpredicate: (call: AgentEvalToolCallForName<TName>) => boolean = () => true,\n\t): AgentEvalToolCallForName<TName> | undefined {\n\t\treturn collectToolCalls(getSteps(), name).find(predicate)\n\t}\n}\n\nfunction createFirstToolResultHelper(getSteps: () => readonly ToolStep[]): AgentEvalToolsHelper[\"firstResult\"] {\n\treturn function firstResult<TName extends AgentEvalToolResultName>(\n\t\tname: TName,\n\t\tpredicate: (result: AgentEvalToolResultForName<TName>) => boolean = () => true,\n\t): AgentEvalToolResultForName<TName> | undefined {\n\t\treturn collectToolResults(getSteps(), name).find(predicate)\n\t}\n}\n\nfunction createScriptCallsHelper(\n\toptions: AgentEvalHelpersOptions,\n\tgetScriptInstrumentationState: () => AgentEvalScriptInstrumentationState | undefined,\n\tgetSteps: () => readonly ToolStep[],\n): AgentEvalToolsHelper[\"scriptCalls\"] {\n\tfunction scriptCalls(): readonly AgentEvalPositionedScriptCall[]\n\tfunction scriptCalls<TMethod extends AgentEvalScriptCallMethod>(\n\t\tmethod: TMethod,\n\t\tpredicate?: (call: AgentEvalPositionedScriptCallForMethod<TMethod>) => boolean,\n\t): readonly AgentEvalPositionedScriptCallForMethod<TMethod>[]\n\tfunction scriptCalls<TMethod extends AgentEvalScriptCallMethod>(\n\t\tmethod?: TMethod,\n\t\tpredicate?: (call: AgentEvalPositionedScriptCallForMethod<TMethod>) => boolean,\n\t): readonly AgentEvalPositionedScriptCall[] | readonly AgentEvalPositionedScriptCallForMethod<TMethod>[] {\n\t\tconst calls = collectPositionedScriptCalls(\n\t\t\toptions.initialStepIndex ?? 0,\n\t\t\tgetSteps(),\n\t\t\tgetScriptInstrumentationState(),\n\t\t)\n\t\tif (method === undefined) return calls\n\t\treturn calls.filter(\n\t\t\t(call): call is AgentEvalPositionedScriptCallForMethod<TMethod> =>\n\t\t\t\tisScriptCallForMethod(call, method) && (predicate?.(call) ?? true),\n\t\t)\n\t}\n\treturn scriptCalls\n}\n\nfunction isScriptCallForMethod<TMethod extends AgentEvalScriptCallMethod>(\n\tcall: AgentEvalPositionedScriptCall,\n\tmethod: TMethod,\n): call is AgentEvalPositionedScriptCallForMethod<TMethod> {\n\treturn call.method === method\n}\n\nfunction collectPositionedScriptCalls(\n\tinitialStepIndex: number,\n\tsteps: readonly ToolStep[],\n\tstate: AgentEvalScriptInstrumentationState | undefined,\n): readonly AgentEvalPositionedScriptCall[] {\n\tif (!state || state.calls.length === 0) return []\n\tconst positionedCalls: AgentEvalPositionedScriptCall[] = []\n\tlet scriptCallIndex = 0\n\n\tfor (\n\t\tlet stepIndex = initialStepIndex;\n\t\tstepIndex < steps.length && scriptCallIndex < state.calls.length;\n\t\tstepIndex++\n\t) {\n\t\tconst step = steps[stepIndex]\n\t\tassert(step !== undefined, `Expected eval step ${stepIndex} to exist.`)\n\t\tfor (let partIndex = 0; partIndex < step.content.length && scriptCallIndex < state.calls.length; partIndex++) {\n\t\t\tconst part = step.content[partIndex]\n\t\t\tassert(part !== undefined, `Expected eval step part ${stepIndex}:${partIndex} to exist.`)\n\t\t\tif (!isAssistantToolCallPart(part) || part.content.toolName !== SCRIPT_TOOL_NAME) continue\n\n\t\t\tlet lastSearchedIndex = 0\n\t\t\tfor (; scriptCallIndex < state.calls.length; scriptCallIndex++) {\n\t\t\t\tconst scriptCall = state.calls[scriptCallIndex]\n\t\t\t\tif (!scriptCall) continue\n\n\t\t\t\tconst searchString = `${scriptCall.method}(`\n\t\t\t\tconst searchIndex = part.content.input.script.indexOf(searchString, lastSearchedIndex)\n\t\t\t\tif (searchIndex === -1) break\n\n\t\t\t\tlastSearchedIndex = searchIndex + searchString.length\n\n\t\t\t\tconst position = { stepIndex, partIndex }\n\t\t\t\tpositionedCalls.push({ ...scriptCall, position, script: part.content.input.script })\n\t\t\t}\n\t\t}\n\t}\n\n\treturn positionedCalls\n}\n\nfunction createAgentEvalHelpersFromSteps(\n\toptions: AgentEvalHelpersOptions,\n\tgetSteps: () => readonly ToolStep[],\n\tgetRequests?: () => readonly AgentRequest[],\n\tgetScriptInstrumentationState?: () => AgentEvalScriptInstrumentationState | undefined,\n): AgentEvalHelpers {\n\tconst steps: AgentEvalStepsHelper = {\n\t\tall: getSteps,\n\t\tlast: () => getSteps().at(-1),\n\t\tparts: () => getPositionedParts(getSteps()),\n\t\tdesignPlans: () => {\n\t\t\tconst designPlans: string[] = []\n\t\t\tfor (const { part } of steps.parts()) {\n\t\t\t\tif (isDesignPlan(part)) designPlans.push(part.content)\n\t\t\t}\n\t\t\treturn designPlans\n\t\t},\n\t\tfirstDesignPlanPosition: () => steps.firstPartPosition(isDesignPlan),\n\t\treadProjectQueries: predicate => collectReadProjectQueriesFromSteps(getSteps(), predicate),\n\t\tfirstPartPosition: predicate => {\n\t\t\treturn steps.parts().find(({ part, position }) => predicate(part, position))?.position\n\t\t},\n\t\tfirstToolCallPosition: (name, predicate) => {\n\t\t\treturn steps.firstPartPosition((part, position) => {\n\t\t\t\tif (!isAssistantToolCallPart(part) || !isToolCallForName(part.content, name)) return false\n\t\t\t\treturn predicate?.(part.content, position) ?? true\n\t\t\t})\n\t\t},\n\t\tfirstReadProjectQueryPosition: predicate => {\n\t\t\treturn steps.firstPartPosition(part => getReadProjectQueriesFromPart(part).some(predicate))\n\t\t},\n\t\tfirstScriptPosition: predicate => {\n\t\t\treturn steps.firstPartPosition(part => {\n\t\t\t\tconst script = getScriptInput(part)\n\t\t\t\treturn script !== undefined && predicate(script)\n\t\t\t})\n\t\t},\n\t\tfirstProjectMutationPosition: () => steps.firstPartPosition(isProjectMutationPart),\n\t\thasPartAtOrBefore: (position, predicate) => {\n\t\t\treturn steps.parts().some(({ part, position: partPosition }) => {\n\t\t\t\treturn comparePartPositions(partPosition, position) <= 0 && predicate(part, partPosition)\n\t\t\t})\n\t\t},\n\t\thasReadProjectQueryAtOrBefore: (position, predicate) => {\n\t\t\treturn steps.hasPartAtOrBefore(position, part => getReadProjectQueriesFromPart(part).some(predicate))\n\t\t},\n\t\tcomparePositions: comparePartPositions,\n\t\texpectBefore: (left, right) => {\n\t\t\texpect(left).toBeDefined()\n\t\t\texpect(right).toBeDefined()\n\t\t\tif (left === undefined || right === undefined) return\n\t\t\texpect(comparePartPositions(left, right)).toBeLessThan(0)\n\t\t},\n\t\texpectNoReviewBeforeMutation: () => {\n\t\t\tconst firstReviewPosition = steps.firstToolCallPosition(REVIEW_CHANGES_TOOL_NAME)\n\t\t\tif (firstReviewPosition === undefined) return\n\t\t\tsteps.expectBefore(steps.firstProjectMutationPosition(), firstReviewPosition)\n\t\t},\n\t}\n\n\tconst tools: AgentEvalToolsHelper = {\n\t\tcalls: createToolCallsHelper(getSteps),\n\t\tresults: createToolResultsHelper(getSteps),\n\t\tinputs: createToolInputsHelper(getSteps),\n\t\tfirstCall: createFirstToolCallHelper(getSteps),\n\t\thasCall: (name, predicate) => tools.firstCall(name, predicate) !== undefined,\n\t\tfirstResult: createFirstToolResultHelper(getSteps),\n\t\thasResult: (name, predicate) => tools.firstResult(name, predicate) !== undefined,\n\t\treadProjectQueries: predicate => {\n\t\t\tconst queries = tools.calls(READ_PROJECT_TOOL_NAME).flatMap(call => call.input.queries)\n\t\t\treturn predicate === undefined ? queries : queries.filter(predicate)\n\t\t},\n\t\treadProjectResults: predicate => {\n\t\t\tconst results = tools.results(READ_PROJECT_TOOL_NAME)\n\t\t\tif (predicate === undefined) return results\n\t\t\treturn results.filter(result => getReadProjectQueries(result.input).some(predicate))\n\t\t},\n\t\tfirstReadProjectResult: predicate => tools.readProjectResults(predicate).at(0),\n\t\thasReadProjectQuery: predicate => tools.readProjectQueries(predicate).length > 0,\n\t\tscriptInputs: predicate =>\n\t\t\ttools\n\t\t\t\t.calls(SCRIPT_TOOL_NAME)\n\t\t\t\t.map(call => call.input.script)\n\t\t\t\t.filter(script => predicate?.(script) ?? true),\n\t\tscriptCalls: createScriptCallsHelper(options, () => getScriptInstrumentationState?.(), getSteps),\n\t\thasScriptCall: (method, predicate) => tools.scriptCalls(method).some(call => predicate?.(call) ?? true),\n\t\tnodeLookups: idOrPredicate => {\n\t\t\tconst predicate = typeof idOrPredicate === \"function\" ? idOrPredicate : (id: NodeID) => id === idOrPredicate\n\t\t\treturn tools.scriptCalls().filter(call => {\n\t\t\t\tif (call.method === \"getNode\" || call.method === \"serialize\") return predicate(call.input.id)\n\t\t\t\tif (call.method === \"getNodes\" || call.method === \"serializeNodes\") return call.input.ids.some(predicate)\n\t\t\t\treturn false\n\t\t\t})\n\t\t},\n\t\tfirstNodeLookup: idOrPredicate => {\n\t\t\treturn tools.nodeLookups(idOrPredicate).at(0)\n\t\t},\n\t\thasNodeLookup: idOrPredicate => tools.nodeLookups(idOrPredicate).length > 0,\n\t\tclarificationQuestions: () => collectClarificationQuestions(getSteps()),\n\t\tclarificationQuestionText: () =>\n\t\t\tformatClarificationQuestionText(tools.clarificationQuestions()[0]?.questions ?? []),\n\t\tcommandErrors: () => collectCommandParts(getSteps()).errors,\n\t\treviewChangesResults: () => {\n\t\t\tconst results: ReviewChangesResponse[] = []\n\t\t\tfor (const result of tools.results(REVIEW_CHANGES_TOOL_NAME)) {\n\t\t\t\tif (isReviewChangesToolResponseValue(result.output)) results.push(result.output)\n\t\t\t}\n\t\t\treturn results\n\t\t},\n\t\treportNoReadProject: report => {\n\t\t\treport.efficiency.scored(\"does not call read_project\", () => {\n\t\t\t\texpect(tools.calls(READ_PROJECT_TOOL_NAME)).toHaveLength(0)\n\t\t\t})\n\t\t},\n\t\treportNoReviewBeforeMutation: report => {\n\t\t\treport.efficiency.scored(\"does not review changes before project update\", () => {\n\t\t\t\tsteps.expectNoReviewBeforeMutation()\n\t\t\t})\n\t\t},\n\t\treportReplayContinued: (report, options) => {\n\t\t\tconst requests = getRequests?.() ?? []\n\t\t\tconst replayStepCount = options.stepIndex ?? 0\n\n\t\t\tif (options.requestId !== undefined) {\n\t\t\t\treport.correctness.required(\"continues captured request\", () => {\n\t\t\t\t\texpect(requests.some(request => request.id === options.requestId)).toBe(true)\n\t\t\t\t})\n\t\t\t}\n\t\t\treport.correctness.required(\"runs after replayed checkpoint\", () => {\n\t\t\t\texpect(steps.all().length).toBeGreaterThan(replayStepCount)\n\t\t\t})\n\t\t},\n\t\treportReplayChecks: (report, options = {}) => {\n\t\t\tconst requests = getRequests?.() ?? []\n\t\t\tconst replayStepCount = options.stepIndex ?? 0\n\n\t\t\tif (options.requestId !== undefined) {\n\t\t\t\treport.correctness.required(\"continues captured request\", () => {\n\t\t\t\t\texpect(requests.some(request => request.id === options.requestId)).toBe(true)\n\t\t\t\t})\n\t\t\t}\n\t\t\treport.correctness.scored(\"no command errors\", () => {\n\t\t\t\texpect(tools.commandErrors()).toHaveLength(0)\n\t\t\t})\n\t\t\treport.correctness.required(\"runs after initial replay checkpoint\", () => {\n\t\t\t\texpect(steps.all().length).toBeGreaterThan(replayStepCount)\n\t\t\t})\n\t\t\tif (options.forbidReadProject === true) tools.reportNoReadProject(report)\n\t\t\treport.efficiency.diagnostic(\"does not ask for clarification\", () => {\n\t\t\t\texpect(tools.calls(ASK_CLARIFICATION_TOOL_NAME)).toHaveLength(0)\n\t\t\t})\n\t\t\ttools.reportNoReviewBeforeMutation(report)\n\t\t},\n\t}\n\n\tconst commands: AgentEvalCommandsHelper = {\n\t\tall: () => collectCommandParts(getSteps()).commands,\n\t\tfirst: () => commands.all().at(0),\n\t\tbyType: <T extends CommandType>(type: T) =>\n\t\t\tcommands.all().filter((command): command is Extract<Command, { type: T }> => command.type === type),\n\t}\n\n\treturn { steps, tools, commands }\n}\n\ntype AgentEvalHelpersOptions = { initialStepIndex?: number }\nexport function createAgentEvalHelpers(\n\tsource: AgentEvalHelperSource,\n\toptions: AgentEvalHelpersOptions = {},\n): AgentEvalHelpers {\n\treturn createAgentEvalHelpersFromSteps(\n\t\toptions,\n\t\t() => getHelperRequests(source).flatMap(request => request.steps),\n\t\t() => getHelperRequests(source),\n\t\t() => source.scriptInstrumentationState,\n\t)\n}\n\nexport function createAgentEvalHelpersForSteps(\n\tsteps: readonly ToolStep[],\n\tscriptInstrumentationState?: AgentEvalScriptInstrumentationState,\n\toptions: AgentEvalHelpersOptions = {},\n): AgentEvalHelpers {\n\treturn createAgentEvalHelpersFromSteps(\n\t\toptions,\n\t\t() => steps,\n\t\tundefined,\n\t\t() => scriptInstrumentationState,\n\t)\n}\n", "/**\n * Side-channel for surfacing the message of a passing assertion.\n *\n * Matchers (see browserEvalGlobals) only throw on failure, so a passing\n * `expect(...)` normally records nothing. To show the asserted condition on\n * passed checks too, the matcher stashes its last passing assertion here and the\n * report recorder consumes it immediately after running each check.\n */\nexport interface PassedAssertion {\n\tmessage: string\n\texpected?: string\n\treceived?: string\n\tmatcher?: string\n}\n\nlet lastPassedAssertion: PassedAssertion | undefined\n\nexport function recordPassedAssertion(assertion: PassedAssertion): void {\n\tlastPassedAssertion = assertion\n}\n\n/** Clears any captured assertion so a check never inherits a previous check's result. */\nexport function resetPassedAssertionCapture(): void {\n\tlastPassedAssertion = undefined\n}\n\n/** Returns the assertion captured since the last reset and clears it. */\nexport function consumePassedAssertion(): PassedAssertion | undefined {\n\tconst assertion = lastPassedAssertion\n\tlastPassedAssertion = undefined\n\treturn assertion\n}\n", "import { assert } from \"@framerjs/shared/src/assert.ts\"\nimport { isBoolean, isFunction, isObject, isString } from \"utils/typeChecks.ts\"\nimport { consumePassedAssertion, resetPassedAssertionCapture } from \"./passedAssertionCapture.ts\"\nimport type {\n\tAgentEvalCheck,\n\tAgentEvalCheckCategory,\n\tAgentEvalCheckKind,\n\tAgentEvalCheckResult,\n\tAgentEvalReportCategory,\n\tAgentEvalReportCategoryEachArgs,\n\tAgentEvalReportCategoryMultiCard,\n\tAgentEvalReportCategoryMultiLabels,\n\tAgentEvalReportController,\n} from \"./reportTypes.ts\"\n\ninterface PendingCheckResult {\n\tpassed: boolean\n\tscore?: number\n\tassertion?: string\n\terror?: string\n\texpected?: string\n\treceived?: string\n\tmatcher?: string\n\terrorStack?: string\n}\n\ninterface CheckMetadata {\n\tkind?: AgentEvalCheckKind\n\tgroup?: string\n\titem?: string\n\titemIndex?: number\n\tinvocationKey?: number\n}\n\nfunction getCheckId(category: AgentEvalCheckCategory, name: string, metadata: CheckMetadata = {}): string {\n\tif (metadata.group !== undefined && metadata.invocationKey !== undefined && metadata.itemIndex !== undefined) {\n\t\treturn `${category}:${metadata.group}:${metadata.invocationKey}:${metadata.itemIndex}:${name}`\n\t}\n\n\treturn `${category}:${name}`\n}\n\nfunction getErrorMessage(error: unknown): string {\n\tif (error instanceof Error) return error.message\n\treturn String(error)\n}\n\nfunction getErrorStack(error: unknown): string | undefined {\n\tif (error instanceof Error && isString(error.stack)) return error.stack\n\treturn undefined\n}\n\nfunction createMultiCard<T extends AgentEvalReportCategoryMultiLabels>(\n\tkeys: readonly Extract<keyof T, string>[],\n): AgentEvalReportCategoryMultiCard<T> {\n\tconst entries = keys.map(key => [key, false] as const)\n\treturn Object.fromEntries(entries) as AgentEvalReportCategoryMultiCard<T>\n}\n\nfunction isPartialMultiCard<T extends AgentEvalReportCategoryMultiLabels>(\n\tkeys: readonly Extract<keyof T, string>[],\n\tresult: unknown,\n): result is Partial<AgentEvalReportCategoryMultiCard<T>> {\n\tif (!isObject(result)) return false\n\n\tconst validKeys = new Set<string>(keys)\n\tfor (const [key, value] of Object.entries(result)) {\n\t\tif (!validKeys.has(key)) return false\n\t\tif (!isBoolean(value)) return false\n\t}\n\treturn true\n}\n\nfunction getStringProperty(value: unknown, property: string): string | undefined {\n\tif (value === null || typeof value !== \"object\") return undefined\n\tconst propertyValue = Reflect.get(value, property)\n\treturn isString(propertyValue) ? propertyValue : undefined\n}\n\nfunction getAssertionDetail(error: unknown, property: string): string | undefined {\n\tif (error === null || typeof error !== \"object\") return undefined\n\tconst assertion = Reflect.get(error, \"assertion\")\n\treturn getStringProperty(assertion, property)\n}\n\nfunction normalizeScore(score: number): number {\n\tif (!Number.isFinite(score) || score < 0 || score > 1) {\n\t\tthrow new Error(`Expected scored eval check to return a number between 0 and 1, received ${score}.`)\n\t}\n\treturn score\n}\n\nfunction getPendingCheckResult(result: unknown, metadata: CheckMetadata): PendingCheckResult {\n\tconst passed = result === undefined ? true : result === true\n\tif (metadata.kind !== \"scored\") return { passed, received: passed ? undefined : String(result) }\n\n\tconst score = typeof result === \"number\" ? normalizeScore(result) : passed ? 1 : 0\n\treturn {\n\t\tpassed: score === 1,\n\t\tscore,\n\t\treceived: score === 1 ? undefined : String(score),\n\t}\n}\n\nexport function createAgentEvalReport(): AgentEvalReportController {\n\tconst checksById = new Map<string, AgentEvalCheckResult>()\n\tlet currentStep: number | undefined\n\tlet eachInvocationKey = 0\n\n\tfunction record(\n\t\tcategory: AgentEvalCheckCategory,\n\t\tname: string,\n\t\tresult: PendingCheckResult,\n\t\tdurationMs: number,\n\t\tmetadata: CheckMetadata = {},\n\t): void {\n\t\tconst id = getCheckId(category, name, metadata)\n\t\tconst existing = checksById.get(id)\n\t\tconst achievedStep =\n\t\t\texisting?.achievedStep ?? (result.passed && currentStep !== undefined ? currentStep : undefined)\n\t\tconst next: AgentEvalCheckResult = {\n\t\t\tid,\n\t\t\tcategory,\n\t\t\tname,\n\t\t\tpassed: result.passed,\n\t\t\tdurationMs,\n\t\t\tgroup: metadata.group,\n\t\t\titem: metadata.item,\n\t\t\tmessage: existing?.message,\n\t\t\tassertion: result.assertion,\n\t\t\tachievedStep,\n\t\t\terror: result.error,\n\t\t\texpected: result.expected,\n\t\t\treceived: result.received,\n\t\t\tmatcher: result.matcher,\n\t\t\terrorStack: result.errorStack,\n\t\t}\n\t\tif (metadata.kind !== undefined) next.kind = metadata.kind\n\t\tif (result.score !== undefined) next.score = result.score\n\t\tchecksById.set(id, next)\n\t}\n\n\tfunction runCheck(\n\t\tcategory: AgentEvalCheckCategory,\n\t\tname: string,\n\t\tcheck: AgentEvalCheck,\n\t\tmessage?: string,\n\t\tmetadata: CheckMetadata = {},\n\t) {\n\t\tconst startedAt = performance.now()\n\t\tconst recordError = (error: unknown) => {\n\t\t\trecord(\n\t\t\t\tcategory,\n\t\t\t\tname,\n\t\t\t\t{\n\t\t\t\t\tpassed: false,\n\t\t\t\t\tscore: metadata.kind === \"scored\" ? 0 : undefined,\n\t\t\t\t\terror: getErrorMessage(error),\n\t\t\t\t\texpected: getAssertionDetail(error, \"expected\"),\n\t\t\t\t\treceived: getAssertionDetail(error, \"received\"),\n\t\t\t\t\tmatcher: getAssertionDetail(error, \"matcher\"),\n\t\t\t\t\terrorStack: getErrorStack(error),\n\t\t\t\t},\n\t\t\t\tMath.round(performance.now() - startedAt),\n\t\t\t\tmetadata,\n\t\t\t)\n\t\t}\n\n\t\ttry {\n\t\t\tresetPassedAssertionCapture()\n\t\t\tconst result = isFunction(check) ? check() : check\n\t\t\tconst pendingResult = getPendingCheckResult(result, metadata)\n\t\t\tif (pendingResult.passed) {\n\t\t\t\tconst passedAssertion = consumePassedAssertion()\n\t\t\t\tif (passedAssertion) {\n\t\t\t\t\tpendingResult.assertion = passedAssertion.message\n\t\t\t\t\tpendingResult.expected = passedAssertion.expected\n\t\t\t\t\tpendingResult.received = passedAssertion.received\n\t\t\t\t\tpendingResult.matcher = passedAssertion.matcher\n\t\t\t\t}\n\t\t\t}\n\t\t\trecord(category, name, pendingResult, Math.round(performance.now() - startedAt), metadata)\n\t\t\tconst latest = checksById.get(getCheckId(category, name, metadata))\n\t\t\tif (latest && message !== undefined) checksById.set(latest.id, { ...latest, message })\n\t\t} catch (error) {\n\t\t\trecordError(error)\n\t\t}\n\t}\n\n\tfunction recordMulti<T extends AgentEvalReportCategoryMultiLabels>(\n\t\tcategory: AgentEvalCheckCategory,\n\t\tlabels: T,\n\t\tkeys: readonly Extract<keyof T, string>[],\n\t\tcard: AgentEvalReportCategoryMultiCard<T>,\n\t\tdurationMs: number,\n\t\terror?: unknown,\n\t): void {\n\t\tfor (const key of keys) {\n\t\t\tconst label = labels[key]\n\t\t\tassert(label !== undefined, `Missing multi check label for \"${key}\".`)\n\t\t\tconst passed = card[key]\n\t\t\trecord(\n\t\t\t\tcategory,\n\t\t\t\tlabel,\n\t\t\t\t{\n\t\t\t\t\tpassed,\n\t\t\t\t\terror: passed || error === undefined ? undefined : getErrorMessage(error),\n\t\t\t\t\terrorStack: passed || error === undefined ? undefined : getErrorStack(error),\n\t\t\t\t\treceived: passed ? undefined : String(passed),\n\t\t\t\t},\n\t\t\t\tdurationMs,\n\t\t\t)\n\t\t}\n\t}\n\n\t/**\n\t * Runs one callback that can report several checks by mutating a shared result card.\n\t * The callback may return the card, a partial card, or nothing; when it completes, the\n\t * card's current state is used as the result unless `true` or an invalid value is returned.\n\t */\n\tfunction runMultiCheck<T extends AgentEvalReportCategoryMultiLabels>(\n\t\tcategory: AgentEvalCheckCategory,\n\t\tlabels: T,\n\t\tcheck: (card: AgentEvalReportCategoryMultiCard<T>) => unknown,\n\t): void {\n\t\tconst startedAt = performance.now()\n\t\tconst keys = Object.keys(labels) as Extract<keyof T, string>[]\n\t\tconst card = createMultiCard<T>(keys)\n\n\t\ttry {\n\t\t\tconst result = check(card)\n\t\t\tconst durationMs = Math.round(performance.now() - startedAt)\n\n\t\t\tif (result === true) {\n\t\t\t\tfor (const key of keys) {\n\t\t\t\t\tconst label = labels[key]\n\t\t\t\t\tassert(label !== undefined, `Missing multi check label for \"${key}\".`)\n\t\t\t\t\trecord(category, label, { passed: true }, durationMs)\n\t\t\t\t}\n\t\t\t\treturn\n\t\t\t}\n\n\t\t\tif (isPartialMultiCard(keys, result)) {\n\t\t\t\tfor (const key of keys) {\n\t\t\t\t\tcard[key] = result[key] ?? card[key]\n\t\t\t\t}\n\t\t\t\trecordMulti(category, labels, keys, card, durationMs)\n\t\t\t\treturn\n\t\t\t}\n\n\t\t\tif (result === undefined) {\n\t\t\t\trecordMulti(category, labels, keys, card, durationMs)\n\t\t\t\treturn\n\t\t\t}\n\n\t\t\trecordMulti(category, labels, keys, createMultiCard<T>(keys), durationMs)\n\t\t} catch (error) {\n\t\t\trecordMulti(category, labels, keys, card, Math.round(performance.now() - startedAt), error)\n\t\t}\n\t}\n\n\tfunction createCategory(category: AgentEvalCheckCategory): AgentEvalReportCategory {\n\t\tconst reportCategory = {} as AgentEvalReportCategory\n\t\treportCategory.required = (name, check, message) => runCheck(category, name, check, message, { kind: \"required\" })\n\t\treportCategory.forbidden = (name, check, message) => runCheck(category, name, check, message, { kind: \"forbidden\" })\n\t\treportCategory.scored = (name, check, message) => runCheck(category, name, check, message, { kind: \"scored\" })\n\t\treportCategory.diagnostic = (name, check, message) =>\n\t\t\trunCheck(category, name, check, message, { kind: \"diagnostic\" })\n\t\treportCategory.each = <T>(...args: AgentEvalReportCategoryEachArgs<T>) => {\n\t\t\tconst [group, items, check] = args\n\t\t\tconst invocationKey = eachInvocationKey\n\n\t\t\tlet index = 0\n\t\t\tfor (const item of items) {\n\t\t\t\trunCheck(category, String(item), () => check(item, index), undefined, {\n\t\t\t\t\tkind: \"scored\",\n\t\t\t\t\tgroup,\n\t\t\t\t\titem: String(item),\n\t\t\t\t\titemIndex: index,\n\t\t\t\t\tinvocationKey,\n\t\t\t\t})\n\t\t\t\tindex++\n\t\t\t}\n\t\t\teachInvocationKey++\n\t\t}\n\t\treportCategory.multi = (...args) => {\n\t\t\tconst [labels, check] = args\n\t\t\trunMultiCheck(category, labels, check)\n\t\t}\n\t\treturn reportCategory\n\t}\n\n\treturn {\n\t\tcorrectness: createCategory(\"correctness\"),\n\t\taccuracy: createCategory(\"accuracy\"),\n\t\tefficiency: createCategory(\"efficiency\"),\n\t\tfunctionality: createCategory(\"functionality\"),\n\t\tdesign: createCategory(\"design\"),\n\t\tgetChecks: () => Array.from(checksById.values()),\n\t\tsetCurrentStep: stepIndex => {\n\t\t\tcurrentStep = stepIndex\n\t\t\teachInvocationKey = 0\n\t\t},\n\t}\n}\n", "import { agentEvalCategories } from \"./categoryStatistics.ts\"\nimport type { AgentEvalCheckCategory, AgentEvalCheckResult } from \"./reportTypes.ts\"\n\nconst defaultAgentEvalCategoryWeights = {\n\tcorrectness: 0.7,\n\taccuracy: 0.2,\n\tefficiency: 0.1,\n\tfunctionality: 1,\n\tdesign: 1,\n} satisfies Record<AgentEvalCheckCategory, number>\n\ninterface AgentEvalCategoryScore {\n\tearned: number\n\tpossible: number\n\tscore: number\n}\n\ntype AgentEvalCategoryScores = Record<AgentEvalCheckCategory, AgentEvalCategoryScore>\n\nfunction getEmptyCategoryScore(): AgentEvalCategoryScore {\n\treturn { earned: 0, possible: 0, score: 0 }\n}\n\nfunction createEmptyCategoryScores(): AgentEvalCategoryScores {\n\treturn {\n\t\tcorrectness: getEmptyCategoryScore(),\n\t\taccuracy: getEmptyCategoryScore(),\n\t\tefficiency: getEmptyCategoryScore(),\n\t\tfunctionality: getEmptyCategoryScore(),\n\t\tdesign: getEmptyCategoryScore(),\n\t}\n}\n\nexport function hasFailedGatingCheck(checks: readonly AgentEvalCheckResult[]): boolean {\n\treturn checks.some(check => (check.kind === \"required\" || check.kind === \"forbidden\") && !check.passed)\n}\n\nfunction isScoredCheck(check: AgentEvalCheckResult): boolean {\n\treturn check.kind === \"scored\" || check.kind === undefined\n}\n\nexport function createCategoryScores(checks: readonly AgentEvalCheckResult[]): AgentEvalCategoryScores {\n\tconst scores = createEmptyCategoryScores()\n\n\tfor (const check of checks) {\n\t\tif (!isScoredCheck(check)) continue\n\t\tconst category = scores[check.category]\n\t\tcategory.earned += check.score ?? (check.passed ? 1 : 0)\n\t\tcategory.possible += 1\n\t}\n\n\tfor (const category of agentEvalCategories) {\n\t\tconst score = scores[category]\n\t\tscore.score = score.possible === 0 ? 0 : score.earned / score.possible\n\t}\n\n\treturn scores\n}\n\nexport function getWeightedScore(checks: readonly AgentEvalCheckResult[]): number {\n\tif (hasFailedGatingCheck(checks)) return 0\n\n\tconst scores = createCategoryScores(checks)\n\tlet earned = 0\n\tlet possible = 0\n\n\tfor (const category of agentEvalCategories) {\n\t\tconst categoryScore = scores[category]\n\t\tif (categoryScore.possible === 0) continue\n\t\tconst weight = defaultAgentEvalCategoryWeights[category]\n\t\tearned += categoryScore.score * weight\n\t\tpossible += weight\n\t}\n\n\treturn possible === 0 ? 1 : earned / possible\n}\n\nexport function getScorePercent(score: number): number {\n\tif (score >= 1) return 100\n\treturn Math.floor(score * 100)\n}\n", "import type { ModelMessage } from \"ai\"\nimport { segmentsToTextContent } from \"app/agent/editor/utils/input.ts\"\nimport type { AgentRequest } from \"app/ai/agents/types.ts\"\nimport type { CanvasTree } from \"document/models/CanvasTree/CanvasTree.ts\"\n\ninterface TextModelMessageContent {\n\ttype: \"text\"\n\ttext: string\n}\n\nfunction createTextContent(text: string): TextModelMessageContent {\n\treturn { type: \"text\", text }\n}\n\nexport function createAgentEvalInputMessage(request: AgentRequest, tree: CanvasTree): ModelMessage {\n\treturn {\n\t\trole: \"user\",\n\t\tcontent: [\n\t\t\t...request.contextMessages.map(createTextContent),\n\t\t\tcreateTextContent(segmentsToTextContent(tree, request.parts).trim()),\n\t\t],\n\t}\n}\n", "import { assert } from \"@framerjs/shared\"\nimport type { LanguageModelUsage } from \"ai\"\nimport type { AgentInputSegment } from \"app/agent/editor/agentInputSchema.ts\"\nimport type { AgentLifeCycleHooks, AgentTurnOptions } from \"app/ai/agents/Agent.ts\"\nimport { isAssistantToolCallPart, type ToolStep } from \"app/ai/agents/messages.ts\"\nimport type { ClarificationAnswerProvider } from \"app/ai/agents/tools/askClarification.ts\"\nimport { ASK_CLARIFICATION_TOOL_NAME, READ_PROJECT_TOOL_NAME, SCRIPT_TOOL_NAME } from \"app/ai/agents/tools/toolNames.ts\"\nimport type { AgentRequest } from \"app/ai/agents/types.ts\"\nimport type { LanguageModel } from \"app/ai/languageModels.ts\"\nimport type { AgentReasoningEffort } from \"app/ai/models.ts\"\nimport { resolveAgentTurnUsdCost } from \"app/ai/utils/languageModelUsdEstimate.ts\"\nimport { getOpenRouterCostFromMetadata } from \"app/ai/utils/openRouterUsage.ts\"\nimport type { VekterEngine } from \"document/VekterEngine.ts\"\nimport { createEmptyAgentEvalCategoryStatistics } from \"./categoryStatistics.ts\"\nimport type { AgentEvalDefinition } from \"./definition.ts\"\nimport { createAgentEvalHelpers } from \"./helpers.ts\"\nimport type { AgentEvalScriptInstrumentationState } from \"./helpers.ts\"\nimport type { AgentEvalModelConfig } from \"./modelConfig.ts\"\nimport { createAgentEvalReport } from \"./report.ts\"\nimport type { AgentEvalCategoryStatisticsByCategory, AgentEvalCheckResult } from \"./reportTypes.ts\"\nimport { getWeightedScore, hasFailedGatingCheck } from \"./scoring.ts\"\nimport { toAgentEvalTokenUsage } from \"./tokenUsage.ts\"\nimport type { AgentEvalTranscriptInputMessages } from \"./transcriptData.ts\"\nimport { createAgentEvalInputMessage } from \"./transcriptInput.ts\"\nimport type {\n\tAgentEvalCurrentStep,\n\tAgentEvalProgressLogger,\n\tAgentEvalRequestInput,\n\tAgentEvalRunContext,\n\tAgentEvalRunResult,\n\tAgentEvalRunStatistics,\n\tAgentEvalRuntime,\n} from \"./types.ts\"\n\nexport type AgentEvalTranscriptWriter = (context: {\n\tresult: AgentEvalRunResult\n\tchatMessages: readonly AgentRequest[]\n\ttree: VekterEngine[\"tree\"]\n\tinputMessages: AgentEvalTranscriptInputMessages\n}) => Promise<string>\n\ninterface AgentEvalRunnerOptions {\n\tmodelConfigs: readonly AgentEvalModelConfig[]\n\truns: number\n\tsignal?: AbortSignal\n\tshouldRun?: (context: AgentEvalRunSelectionContext) => boolean\n\tsend?: (context: AgentEvalSendContext) => Promise<void>\n\tonRunStart?: (context: AgentEvalRunStartContext) => void | Promise<void>\n\tonRunProgressMessage?: (context: AgentEvalRunProgressMessageContext) => void\n\tonRunProgress?: (context: AgentEvalRunProgressContext) => void | Promise<void>\n\tonRunComplete?: (result: AgentEvalRunResult) => void | Promise<void>\n\tonRunUpdate?: (update: AgentEvalRunUpdate) => void | Promise<void>\n\tonProgress?: AgentEvalProgressLogger\n\ttranscript?: boolean\n\twriteTranscript?: AgentEvalTranscriptWriter\n}\n\nexport interface AgentEvalRunStartContext {\n\tdefinition: AgentEvalDefinition\n\tmodelConfig: AgentEvalModelConfig\n\trunNumber: number\n\ttotalRuns: number\n\trunInvocationId?: string\n}\n\nexport interface AgentEvalRunSelectionContext extends AgentEvalRunStartContext {\n\tdefinitionIndex: number\n\tmodelConfigIndex: number\n\t/** Flattened eval x model x run ordinal used for balanced CI sharding. */\n\trunIndex: number\n}\n\ninterface AgentEvalRunProgressContext extends AgentEvalRunStartContext {\n\tchecks: readonly AgentEvalCheckResult[]\n}\n\nexport interface AgentEvalRunProgressMessageContext extends AgentEvalRunStartContext {\n\tmessage: string\n}\n\nexport interface AgentEvalRunUpdate {\n\tdefinition: AgentEvalDefinition\n\trunInvocationId?: string\n\tmodel: LanguageModel\n\treasoningEffort?: AgentReasoningEffort\n\trunNumber: number\n\truntime: AgentEvalRuntime\n\ttranscriptInputMessages: AgentEvalTranscriptInputMessages\n}\n\ninterface AgentEvalSendContext extends AgentEvalRunContext {\n\tdefinition: AgentEvalDefinition\n\truntime: AgentEvalRuntime\n\tsignal?: AbortSignal\n}\n\ninterface AgentEvalDefinitionRunOptions extends Pick<AgentEvalRunnerOptions, \"send\" | \"onProgress\" | \"signal\"> {\n\treasoningEffort?: AgentReasoningEffort\n\tonRunProgressMessage?: AgentEvalProgressLogger\n\tonRunProgress?: (checks: readonly AgentEvalCheckResult[]) => void | Promise<void>\n\ttranscript?: boolean\n\twriteTranscript?: AgentEvalTranscriptWriter\n\tonRunUpdate?: (update: AgentEvalRunUpdate) => void | Promise<void>\n}\n\nfunction shouldEvaluateOnStepFinish(definition: AgentEvalDefinition): boolean {\n\tif (definition.options.runOnStepFinish === true) return true\n\treturn definition.options.stopWhenPassed === true\n}\n\nfunction getPrompt(definition: AgentEvalDefinition): readonly AgentInputSegment[] {\n\treturn [definition.name]\n}\n\nfunction getReplayRequestInput(request: AgentRequest): AgentEvalRequestInput {\n\treturn {\n\t\tparts: request.parts,\n\t\timplicitSelection: request.selection ?? [],\n\t\timages: request.images,\n\t\tfiles: request.files ?? [],\n\t}\n}\n\nfunction getAgentEvalRequestInput(context: AgentEvalSendContext): AgentEvalRequestInput {\n\tconst request = context.agent.chatMessages.at(-1)\n\tif (request) return getReplayRequestInput(request)\n\n\treturn {\n\t\tparts: context.runtime.prompt === undefined ? getPrompt(context.definition) : [context.runtime.prompt],\n\t\timplicitSelection: context.runtime.implicitSelection ?? [],\n\t\timages: context.runtime.images ?? [],\n\t\tfiles: context.runtime.files ?? [],\n\t}\n}\n\nconst defaultAgentSendTimeoutMs = 600_000\n/** Minimum budget per allowed tool step while `agent.send()` runs (model rounds + tool execution). */\nconst agentEvalSendTimeoutMsPerStep = 60_000\n\nfunction getAgentEvalProcessEnv(): NodeJS.ProcessEnv | undefined {\n\treturn typeof process === \"undefined\" ? undefined : process.env\n}\n\nfunction getAgentEvalSendTimeoutMs(\n\tenv: NodeJS.ProcessEnv | undefined = getAgentEvalProcessEnv(),\n\tevalSendTimeoutMs?: number,\n\tmaxSteps?: number,\n): number {\n\tconst configuredTimeout = env?.AGENT_EVAL_SEND_TIMEOUT_MS\n\tif (configuredTimeout !== undefined) {\n\t\tconst parsedTimeout = Number(configuredTimeout)\n\t\tif (Number.isInteger(parsedTimeout) && parsedTimeout > 0) return parsedTimeout\n\t}\n\n\tlet timeout = defaultAgentSendTimeoutMs\n\tif (evalSendTimeoutMs !== undefined && Number.isInteger(evalSendTimeoutMs) && evalSendTimeoutMs > 0) {\n\t\ttimeout = evalSendTimeoutMs\n\t}\n\n\tconst stepBudget = (maxSteps ?? 1) * agentEvalSendTimeoutMsPerStep\n\treturn Math.max(timeout, stepBudget)\n}\n\nfunction getAgentEvalTurnOptions(\n\tmaxSteps: number | undefined,\n\twaitForUserAnswers?: AgentTurnOptions[\"waitForUserAnswers\"],\n): AgentTurnOptions {\n\tconst options: AgentTurnOptions = {\n\t\tpropagateErrors: true,\n\t\t// TODO: If we ever want to eval title generation in the future we should make this configurable.\n\t\tskipTitleGeneration: true,\n\t\t// CLI eval assertions read the live engine state after command execution; committing the turn\n\t\t// into browser history only adds undo/timeline side effects. TODO: make this configurable once\n\t\t// we add evals that assert history, undo, or persisted timeline behavior.\n\t\tskipHistoryCommit: true,\n\t\t// Summary generation is post-turn memory maintenance and an extra model side effect; current\n\t\t// evals score the completed turn directly.\n\t\tskipSummaryGeneration: true,\n\t\t// Eval runs should not emit Raindrop events or SDK trace telemetry; this keeps CLI harness runs\n\t\t// deterministic and prevents telemetry failures from affecting model-turn diagnostics.\n\t\tdisableRaindropTelemetry: true,\n\t}\n\tif (maxSteps !== undefined) options.maxSteps = maxSteps\n\tif (waitForUserAnswers !== undefined) options.waitForUserAnswers = waitForUserAnswers\n\treturn options\n}\n\nexport const testing = {\n\tcreateEvalClarificationAnswerProvider,\n\tgetAgentEvalRequestInput,\n\tgetAgentEvalProcessEnv,\n\tgetAgentEvalSendTimeoutMs,\n\tgetAgentEvalTurnOptions,\n}\n\nfunction getRunRequests(runtime: AgentEvalRuntime | undefined): readonly AgentRequest[] {\n\tif (runtime === undefined) return []\n\tconst requestStartIndex = runtime.replayRequestStartIndex\n\tif (requestStartIndex === undefined) {\n\t\tconst request = runtime.agent.chatMessages.at(-1)\n\t\treturn request === undefined ? [] : [request]\n\t}\n\treturn runtime.agent.chatMessages.slice(requestStartIndex)\n}\n\nfunction getRequestStepOffset(runtime: AgentEvalRuntime, request: AgentRequest): number {\n\tlet offset = 0\n\tfor (const runRequest of getRunRequests(runtime)) {\n\t\tif (runRequest === request) return offset\n\t\toffset += runRequest.steps.length\n\t}\n\treturn 0\n}\n\nfunction shouldDeferFinalEvaluation(runtime: AgentEvalRuntime): boolean {\n\tconst followUpCount = runtime.followUpRequests?.length ?? 0\n\tif (followUpCount === 0) return false\n\tconst requestStartIndex = runtime.replayRequestStartIndex\n\tif (requestStartIndex === undefined) return false\n\treturn runtime.agent.chatMessages.length < requestStartIndex + 1 + followUpCount\n}\n\nfunction getTotalToolSteps(runtime: AgentEvalRuntime | undefined): number {\n\treturn getRunRequests(runtime).reduce((total, request) => total + request.steps.length, 0)\n}\n\nfunction getStringField(obj: Record<string, unknown>, key: string): string | undefined {\n\tconst value = obj[key]\n\treturn typeof value === \"string\" ? value : undefined\n}\n\nfunction formatReadProjectQueryLabel(query: Record<string, unknown>): string {\n\tconst type = getStringField(query, \"type\") ?? \"unknown\"\n\tconst identifier = getStringField(query, \"name\") ?? getStringField(query, \"id\")\n\treturn identifier ? `${type} > ${identifier}` : type\n}\n\nfunction formatReadProjectInput(input: unknown): string | undefined {\n\tif (!input || typeof input !== \"object\") return undefined\n\tif (!(\"queries\" in input)) return undefined\n\tconst { queries } = input\n\tif (!Array.isArray(queries)) return undefined\n\treturn queries\n\t\t.filter((query): query is object => typeof query === \"object\" && query !== null)\n\t\t.map(formatReadProjectQueryLabel)\n\t\t.join(\", \")\n}\n\nfunction formatScriptInput(input: unknown): string | undefined {\n\tif (!input || typeof input !== \"object\") return undefined\n\tif (!(\"script\" in input)) return undefined\n\tconst { script } = input\n\tif (typeof script !== \"string\") return undefined\n\tconst oneLine = script.replaceAll(\"\\n\", \" \").trim()\n\tconst maxLength = 120\n\treturn oneLine.length > maxLength ? `\"${oneLine.slice(0, maxLength)}...\"` : `\"${oneLine}\"`\n}\n\nfunction formatToolCallDetail(toolName: string, input: unknown): string {\n\tswitch (toolName) {\n\t\tcase READ_PROJECT_TOOL_NAME: {\n\t\t\tconst label = formatReadProjectInput(input)\n\t\t\treturn label ? `${toolName} > ${label}` : toolName\n\t\t}\n\t\tcase SCRIPT_TOOL_NAME: {\n\t\t\tconst label = formatScriptInput(input)\n\t\t\treturn label ? `${toolName} > ${label}` : toolName\n\t\t}\n\t\tdefault:\n\t\t\treturn toolName\n\t}\n}\n\nfunction formatToolStepName(step: ToolStep): string {\n\tconst toolCallParts = step.content.filter(isAssistantToolCallPart)\n\n\treturn step.toolResults\n\t\t.map(result => {\n\t\t\tconst toolCall = toolCallParts.find(part => part.content.toolCallId === result.toolCallId)\n\t\t\treturn formatToolCallDetail(result.toolName, toolCall?.content.input)\n\t\t})\n\t\t.join(\", \")\n}\n\nfunction getToolStepNames(runtime: AgentEvalRuntime | undefined): string[] {\n\treturn getRunRequests(runtime).flatMap(request => request.steps.map(formatToolStepName))\n}\n\nfunction normalizeStepUsage(\n\tusage: AgentRequest[\"steps\"][number][\"metadata\"][\"usage\"] | undefined,\n): LanguageModelUsage | undefined {\n\tif (usage === undefined) return undefined\n\treturn {\n\t\tinputTokens: usage.inputTokens,\n\t\tinputTokenDetails: {\n\t\t\tnoCacheTokens: usage.inputTokenDetails?.noCacheTokens,\n\t\t\tcacheReadTokens: usage.inputTokenDetails?.cacheReadTokens,\n\t\t\tcacheWriteTokens: usage.inputTokenDetails?.cacheWriteTokens,\n\t\t},\n\t\toutputTokens: usage.outputTokens,\n\t\toutputTokenDetails: {\n\t\t\ttextTokens: usage.outputTokenDetails?.textTokens,\n\t\t\treasoningTokens: usage.outputTokenDetails?.reasoningTokens,\n\t\t},\n\t\ttotalTokens: usage.totalTokens,\n\t\treasoningTokens: usage.reasoningTokens,\n\t\tcachedInputTokens: usage.cachedInputTokens,\n\t\traw: usage.raw,\n\t}\n}\n\nfunction sumOptionalUsageValue(left: number | undefined, right: number | undefined): number | undefined {\n\tif (left === undefined && right === undefined) return undefined\n\treturn (left ?? 0) + (right ?? 0)\n}\n\nfunction aggregateLanguageModelUsage(\n\tleft: LanguageModelUsage | undefined,\n\tright: LanguageModelUsage,\n): LanguageModelUsage {\n\treturn {\n\t\tinputTokens: sumOptionalUsageValue(left?.inputTokens, right.inputTokens),\n\t\tinputTokenDetails: {\n\t\t\tnoCacheTokens: sumOptionalUsageValue(\n\t\t\t\tleft?.inputTokenDetails?.noCacheTokens,\n\t\t\t\tright.inputTokenDetails?.noCacheTokens,\n\t\t\t),\n\t\t\tcacheReadTokens: sumOptionalUsageValue(\n\t\t\t\tleft?.inputTokenDetails?.cacheReadTokens,\n\t\t\t\tright.inputTokenDetails?.cacheReadTokens,\n\t\t\t),\n\t\t\tcacheWriteTokens: sumOptionalUsageValue(\n\t\t\t\tleft?.inputTokenDetails?.cacheWriteTokens,\n\t\t\t\tright.inputTokenDetails?.cacheWriteTokens,\n\t\t\t),\n\t\t},\n\t\toutputTokens: sumOptionalUsageValue(left?.outputTokens, right.outputTokens),\n\t\toutputTokenDetails: {\n\t\t\ttextTokens: sumOptionalUsageValue(left?.outputTokenDetails?.textTokens, right.outputTokenDetails?.textTokens),\n\t\t\treasoningTokens: sumOptionalUsageValue(\n\t\t\t\tleft?.outputTokenDetails?.reasoningTokens,\n\t\t\t\tright.outputTokenDetails?.reasoningTokens,\n\t\t\t),\n\t\t},\n\t\ttotalTokens: sumOptionalUsageValue(left?.totalTokens, right.totalTokens),\n\t\treasoningTokens: sumOptionalUsageValue(left?.reasoningTokens, right.reasoningTokens),\n\t\tcachedInputTokens: sumOptionalUsageValue(left?.cachedInputTokens, right.cachedInputTokens),\n\t}\n}\n\nfunction getRunUsage(request: AgentRequest): LanguageModelUsage | undefined {\n\tif (request.usage !== undefined) return request.usage\n\n\tlet aggregatedUsage: LanguageModelUsage | undefined\n\tfor (const step of request.steps) {\n\t\tconst usage = normalizeStepUsage(step.metadata.usage)\n\t\tif (usage === undefined) continue\n\t\taggregatedUsage = aggregateLanguageModelUsage(aggregatedUsage, usage)\n\t}\n\treturn aggregatedUsage\n}\n\nfunction getRunRequestsUsage(requests: readonly AgentRequest[]): LanguageModelUsage | undefined {\n\tlet aggregatedUsage: LanguageModelUsage | undefined\n\tfor (const request of requests) {\n\t\tconst usage = getRunUsage(request)\n\t\tif (usage === undefined) continue\n\t\taggregatedUsage = aggregateLanguageModelUsage(aggregatedUsage, usage)\n\t}\n\treturn aggregatedUsage\n}\n\nfunction getRunProviderReportedCost(request: AgentRequest): number {\n\tlet cost = 0\n\tfor (const step of request.steps) {\n\t\tcost += getOpenRouterCostFromMetadata(step.metadata.providerMetadata)\n\t}\n\treturn cost\n}\n\nfunction getRunCost(runtime: AgentEvalRuntime | undefined, model: LanguageModel): number {\n\tlet cost = 0\n\tfor (const request of getRunRequests(runtime)) {\n\t\tcost += request.cost ?? resolveAgentTurnUsdCost(getRunProviderReportedCost(request), 0, model, getRunUsage(request))\n\t}\n\treturn cost\n}\n\nfunction getRunStatus(checks: AgentEvalRunResult[\"checks\"], error: string | undefined): AgentEvalRunResult[\"status\"] {\n\tif (error) return \"error\"\n\tif (hasFailedGatingCheck(checks)) return \"failed\"\n\treturn haveAllChecksPassed(checks) ? \"passed\" : \"failed\"\n}\n\nfunction getFinalRunStatus(\n\tchecks: AgentEvalRunResult[\"checks\"],\n\terror: string | undefined,\n\tstopped: boolean,\n): AgentEvalRunResult[\"status\"] {\n\tif (stopped) return \"stopped\"\n\treturn getRunStatus(checks, error)\n}\n\nfunction hasClarificationToolCall(step: ToolStep): boolean {\n\treturn step.toolResults.some(result => result.toolName === ASK_CLARIFICATION_TOOL_NAME)\n}\n\nfunction createEvalClarificationAnswerProvider(autoAnswerClarifications = false): ClarificationAnswerProvider {\n\tif (autoAnswerClarifications) {\n\t\treturn async questions =>\n\t\t\tquestions.map((question, questionIndex) => {\n\t\t\t\tconst answer = question.suggestedAnswers[0]\n\t\t\t\tassert(answer !== undefined, \"Clarification question must have at least one suggested answer.\")\n\t\t\t\treturn { questionIndex, answer }\n\t\t\t})\n\t}\n\treturn async () => []\n}\n\nfunction getRunErrorMessage(error: unknown): string {\n\treturn error instanceof Error ? error.message : String(error)\n}\n\nfunction getRunErrorStack(error: unknown): string | undefined {\n\treturn error instanceof Error && typeof error.stack === \"string\" ? error.stack : undefined\n}\n\nfunction haveAllChecksPassed(checks: readonly AgentEvalCheckResult[]): boolean {\n\tconst nonDiagnosticChecks = checks.filter(check => check.kind !== \"diagnostic\")\n\tif (nonDiagnosticChecks.length === 0) return checks.length > 0 && checks.every(check => check.passed)\n\treturn nonDiagnosticChecks.every(check => check.passed)\n}\n\nfunction isRunStopped(signal: AbortSignal | undefined, runtime: AgentEvalRuntime | undefined): boolean {\n\tif (signal?.aborted) return true\n\treturn runtime?.agent.chatMessages.at(-1)?.aborted?.reason === \"user-stopped\"\n}\n\nfunction createRunProgressLogger(\n\toptions: Pick<AgentEvalDefinitionRunOptions, \"onProgress\" | \"onRunProgressMessage\">,\n): AgentEvalProgressLogger | undefined {\n\tif (!options.onProgress && !options.onRunProgressMessage) return\n\treturn message => {\n\t\toptions.onProgress?.(message)\n\t\toptions.onRunProgressMessage?.(message)\n\t}\n}\n\nfunction isDiagnosticCheck(check: AgentEvalCheckResult): boolean {\n\treturn check.kind === \"diagnostic\"\n}\n\nfunction createCategoryStatistics(checks: readonly AgentEvalCheckResult[]): AgentEvalCategoryStatisticsByCategory {\n\tconst categories = createEmptyAgentEvalCategoryStatistics()\n\n\tfor (const check of checks) {\n\t\tif (isDiagnosticCheck(check)) continue\n\t\tconst category = categories[check.category]\n\t\tcategory.total++\n\t\tif (check.passed) {\n\t\t\tcategory.passed++\n\t\t} else {\n\t\t\tcategory.failed++\n\t\t}\n\t}\n\n\treturn categories\n}\n\nfunction createRunStatistics(\n\tchecks: readonly AgentEvalCheckResult[],\n\tdurationMs: number,\n\ttotalToolSteps: number,\n\tearlyStop: AgentEvalCurrentStep | undefined,\n): AgentEvalRunStatistics {\n\tconst scoringChecks = checks.filter(check => !isDiagnosticCheck(check))\n\tconst threw = scoringChecks.filter(check => check.error !== undefined).length\n\tconst passed = scoringChecks.filter(check => check.passed).length\n\tconst failed = scoringChecks.length - passed\n\n\treturn {\n\t\tdurationMs,\n\t\ttotalToolSteps,\n\t\tearlyStopped: earlyStop !== undefined,\n\t\tstopStep: earlyStop?.stepIndex,\n\t\tcategories: createCategoryStatistics(checks),\n\t\tcallbacks: {\n\t\t\texecutedWithoutThrow: scoringChecks.length - threw,\n\t\t\texecuted: scoringChecks.length,\n\t\t\tthrew,\n\t\t\tpassed,\n\t\t\tfailed,\n\t\t\ttotal: scoringChecks.length,\n\t\t},\n\t}\n}\n\nfunction commitPendingTreeChanges(engine: VekterEngine): void {\n\tif (!engine.tree.hasUncommittedChanges()) return\n\n\tconst inEventHandlingBefore = engine.scheduler.inEventHandling\n\n\t// Force `processFrame` to commit by pretending to be a top-level handler\n\tengine.scheduler.inEventHandling = 0\n\ttry {\n\t\tengine.testing.processFrame(() => undefined, \"nonUserEvent\")\n\t} finally {\n\t\tengine.scheduler.inEventHandling = inEventHandlingBefore\n\t}\n\tassert(!engine.tree.hasUncommittedChanges(), \"Eval callback requires a committed tree.\")\n}\n\nasync function defaultSendAgentTurn(context: AgentEvalSendContext): Promise<void> {\n\tconst agentSendTimeoutMs = getAgentEvalSendTimeoutMs(\n\t\tundefined,\n\t\tcontext.definition.options.sendTimeoutMs,\n\t\tcontext.definition.options.maxSteps,\n\t)\n\tconst turnOptions = getAgentEvalTurnOptions(\n\t\tcontext.definition.options.maxSteps,\n\t\tcreateEvalClarificationAnswerProvider(context.definition.options.autoAnswerClarifications === true),\n\t)\n\tObject.assign(turnOptions, context.runtime.turnOptions)\n\tconst scriptInstrumentationState = context.scriptInstrumentationState\n\tif (scriptInstrumentationState !== undefined) {\n\t\tconst existingInstrumentation = turnOptions.scriptEvalInstrumentation\n\t\tturnOptions.scriptEvalInstrumentation = {\n\t\t\trecordCall: call => {\n\t\t\t\tscriptInstrumentationState.calls.push(call)\n\t\t\t\texistingInstrumentation?.recordCall(call)\n\t\t\t},\n\t\t}\n\t}\n\tconst requestInput = getAgentEvalRequestInput(context)\n\tawait sendAgentEvalTurnWithTimeout(\n\t\tcontext,\n\t\t() =>\n\t\t\tcontext.runtime.replayTarget !== undefined\n\t\t\t\t? context.agent.resumeLastRequest({\n\t\t\t\t\t\t...turnOptions,\n\t\t\t\t\t\tforce: true,\n\t\t\t\t\t\tmodel: context.model,\n\t\t\t\t\t\treasoningEffort: context.reasoningEffort,\n\t\t\t\t\t})\n\t\t\t\t: context.agent.send(\n\t\t\t\t\t\trequestInput.parts,\n\t\t\t\t\t\trequestInput.implicitSelection,\n\t\t\t\t\t\tcontext.model,\n\t\t\t\t\t\tcontext.reasoningEffort,\n\t\t\t\t\t\trequestInput.images,\n\t\t\t\t\t\trequestInput.files,\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t...turnOptions,\n\t\t\t\t\t\t},\n\t\t\t\t\t),\n\t\tagentSendTimeoutMs,\n\t)\n\n\tfor (const followUpRequest of context.runtime.followUpRequests ?? []) {\n\t\tawait sendAgentEvalTurnWithTimeout(\n\t\t\tcontext,\n\t\t\t() =>\n\t\t\t\tcontext.agent.send(\n\t\t\t\t\tfollowUpRequest.parts,\n\t\t\t\t\tfollowUpRequest.implicitSelection,\n\t\t\t\t\tcontext.model,\n\t\t\t\t\tcontext.reasoningEffort,\n\t\t\t\t\tfollowUpRequest.images,\n\t\t\t\t\tfollowUpRequest.files,\n\t\t\t\t\t{\n\t\t\t\t\t\t...turnOptions,\n\t\t\t\t\t},\n\t\t\t\t),\n\t\t\tagentSendTimeoutMs,\n\t\t)\n\t}\n}\n\nasync function sendAgentEvalTurnWithTimeout(\n\tcontext: AgentEvalSendContext,\n\tcreateSendPromise: () => Promise<unknown>,\n\tagentSendTimeoutMs: number,\n): Promise<void> {\n\tif (context.signal?.aborted) {\n\t\tawait context.agent.stop()\n\t\tthrow new Error(\"Agent eval run stopped.\")\n\t}\n\n\tconst sendPromise = createSendPromise()\n\tlet timeout: ReturnType<typeof setTimeout> | undefined\n\tconst timeoutPromise = new Promise<never>((_, reject) => {\n\t\ttimeout = setTimeout(() => {\n\t\t\tvoid context.agent.stop()\n\t\t\treject(\n\t\t\t\tnew Error(\n\t\t\t\t\t`Agent send timed out after ${agentSendTimeoutMs}ms (full turn: model rounds + tool execution). Raise sendTimeoutMs on the eval, maxSteps budget (~${agentEvalSendTimeoutMsPerStep}ms/step), or AGENT_EVAL_SEND_TIMEOUT_MS.`,\n\t\t\t\t),\n\t\t\t)\n\t\t}, agentSendTimeoutMs)\n\t})\n\tlet removeAbortListener = (): void => undefined\n\tconst abortPromise = new Promise<never>((_, reject) => {\n\t\tconst signal = context.signal\n\t\tif (signal === undefined) return\n\n\t\tconst handleAbort = () => {\n\t\t\tvoid context.agent.stop()\n\t\t\treject(new Error(\"Agent eval run stopped.\"))\n\t\t}\n\t\tsignal.addEventListener(\"abort\", handleAbort, { once: true })\n\t\tremoveAbortListener = () => signal.removeEventListener(\"abort\", handleAbort)\n\t})\n\tsendPromise.catch(() => undefined)\n\ttry {\n\t\tawait Promise.race([sendPromise, timeoutPromise, abortPromise])\n\t} finally {\n\t\tif (timeout !== undefined) clearTimeout(timeout)\n\t\tremoveAbortListener()\n\t}\n}\n\nexport async function runAgentEvalDefinition(\n\tdefinition: AgentEvalDefinition,\n\tmodel: LanguageModel,\n\trunNumber: number,\n\toptions: AgentEvalDefinitionRunOptions = {},\n): Promise<AgentEvalRunResult> {\n\tconst report = createAgentEvalReport()\n\tconst startedAt = performance.now()\n\tlet runtime: AgentEvalRuntime | undefined\n\tlet error: string | undefined\n\tlet errorStack: string | undefined\n\tlet earlyStop: AgentEvalCurrentStep | undefined\n\tlet stopped = false\n\tlet state: unknown\n\tconst transcriptInputMessages = new Map<AgentRequest[\"id\"], ReturnType<typeof createAgentEvalInputMessage>>()\n\tconst scriptInstrumentationState: AgentEvalScriptInstrumentationState = { calls: [] }\n\tconst send = options.send ?? defaultSendAgentTurn\n\tconst progress = createRunProgressLogger(options)\n\tprogress?.(`run start: ${definition.name} ${model} #${runNumber}`)\n\n\tconst evaluate = async (\n\t\tcontext: Omit<AgentEvalRunContext, \"report\" | \"steps\" | \"tools\" | \"commands\" | \"model\" | \"runNumber\" | \"state\">,\n\t): Promise<void> => {\n\t\tif (earlyStop !== undefined) return\n\t\tcommitPendingTreeChanges(context.engine)\n\t\tconst currentStep = context.current?.kind === \"step\" ? context.current : undefined\n\t\treport.setCurrentStep(currentStep?.stepIndex)\n\t\ttry {\n\t\t\tawait definition.evaluate({\n\t\t\t\t...context,\n\t\t\t\treport,\n\t\t\t\tstate,\n\t\t\t\t...createAgentEvalHelpers(\n\t\t\t\t\t{\n\t\t\t\t\t\t...context,\n\t\t\t\t\t\trequestStartIndex: runtime?.replayRequestStartIndex,\n\t\t\t\t\t},\n\t\t\t\t\t{ initialStepIndex: definition.options.stepIndex },\n\t\t\t\t),\n\t\t\t\tmodel,\n\t\t\t\treasoningEffort: options.reasoningEffort,\n\t\t\t\trunNumber,\n\t\t\t})\n\t\t\tif (currentStep !== undefined) await options.onRunProgress?.([...report.getChecks()])\n\t\t\tif (\n\t\t\t\tcurrentStep !== undefined &&\n\t\t\t\thasClarificationToolCall(currentStep.step) &&\n\t\t\t\tdefinition.options.autoAnswerClarifications !== true\n\t\t\t) {\n\t\t\t\tif (earlyStop === undefined) earlyStop = currentStep\n\t\t\t\tvoid context.agent.stop()\n\t\t\t\treturn\n\t\t\t}\n\t\t\tif (definition.options.stopWhenPassed === false) return\n\t\t\tif (currentStep === undefined) return\n\t\t\tif (!haveAllChecksPassed(report.getChecks())) return\n\t\t\tif (earlyStop !== undefined) return\n\n\t\t\tearlyStop = currentStep\n\t\t\tvoid context.agent.stop()\n\t\t} finally {\n\t\t\treport.setCurrentStep(undefined)\n\t\t}\n\t}\n\n\tconst runnableDefinition: AgentEvalDefinition = {\n\t\t...definition,\n\t\tevaluate: context =>\n\t\t\tevaluate({\n\t\t\t\tengine: context.engine,\n\t\t\t\tagent: context.agent,\n\t\t\t\tcurrent: context.current,\n\t\t\t\tscriptInstrumentationState,\n\t\t\t}),\n\t}\n\n\tconst lifecycleHooks: AgentLifeCycleHooks = {\n\t\tonTurnStart: () => {\n\t\t\tprogress?.(`agent turn start: ${definition.name}`)\n\t\t},\n\t\tonFirstToken: () => {\n\t\t\tprogress?.(`model first token: ${definition.name}`)\n\t\t},\n\t\tonInputEstimate: estimatedTokens => {\n\t\t\tprogress?.(`model input estimate: ${definition.name} ${estimatedTokens} tokens`)\n\t\t},\n\t\tonPrepareStep: () => {\n\t\t\tassert(runtime, \"Eval runtime must be loaded before prepare-step hooks run.\")\n\t\t\tconst request = runtime.agent.chatMessages.at(-1)\n\t\t\tif (request !== undefined && !transcriptInputMessages.has(request.id)) {\n\t\t\t\ttranscriptInputMessages.set(request.id, createAgentEvalInputMessage(request, runtime.engine.tree))\n\t\t\t}\n\t\t\treturn undefined\n\t\t},\n\t\tonStepFinish: async () => {\n\t\t\tassert(runtime, \"Eval runtime must be loaded before step hooks run.\")\n\t\t\tconst request = runtime.agent.chatMessages.at(-1)\n\t\t\tassert(request, \"Step eval hook requires a completed request.\")\n\t\t\tconst step = request.steps.at(-1)\n\t\t\tassert(step, \"Step eval hook requires a current tool step.\")\n\t\t\tconst stepIndex = getRequestStepOffset(runtime, request) + request.steps.length - 1\n\n\t\t\tif (shouldEvaluateOnStepFinish(definition)) {\n\t\t\t\tprogress?.(`step hook: ${definition.name} step ${stepIndex}`)\n\t\t\t\tawait evaluate({\n\t\t\t\t\tengine: runtime.engine,\n\t\t\t\t\tagent: runtime.agent,\n\t\t\t\t\tscriptInstrumentationState,\n\t\t\t\t\tcurrent: {\n\t\t\t\t\t\tkind: \"step\",\n\t\t\t\t\t\tstepIndex,\n\t\t\t\t\t\tstep,\n\t\t\t\t\t\trequest,\n\t\t\t\t\t},\n\t\t\t\t})\n\t\t\t\tprogress?.(`step hook complete: ${definition.name} step ${stepIndex}`)\n\t\t\t}\n\t\t\tawait options.onRunUpdate?.({\n\t\t\t\tdefinition,\n\t\t\t\tmodel,\n\t\t\t\treasoningEffort: options.reasoningEffort,\n\t\t\t\trunNumber,\n\t\t\t\truntime,\n\t\t\t\ttranscriptInputMessages: new Map(transcriptInputMessages),\n\t\t\t})\n\t\t},\n\t\tonTurnEnd: async agent => {\n\t\t\tassert(runtime, \"Eval runtime must be loaded before final hooks run.\")\n\t\t\tconst request = agent.chatMessages.at(-1)\n\t\t\tassert(request, \"Final eval hook requires a completed request.\")\n\t\t\tif (request.aborted) {\n\t\t\t\tprogress?.(`agent turn end: ${definition.name}`)\n\t\t\t\treturn\n\t\t\t}\n\t\t\tif (shouldDeferFinalEvaluation(runtime)) {\n\t\t\t\tprogress?.(`final hook deferred: ${definition.name}`)\n\t\t\t\tawait options.onRunUpdate?.({\n\t\t\t\t\tdefinition,\n\t\t\t\t\tmodel,\n\t\t\t\t\treasoningEffort: options.reasoningEffort,\n\t\t\t\t\trunNumber,\n\t\t\t\t\truntime,\n\t\t\t\t\ttranscriptInputMessages: new Map(transcriptInputMessages),\n\t\t\t\t})\n\t\t\t\tprogress?.(`agent turn end: ${definition.name}`)\n\t\t\t\treturn\n\t\t\t}\n\n\t\t\tprogress?.(`final hook: ${definition.name}`)\n\t\t\tconst lastToolStep = request.steps.at(-1)\n\t\t\tawait evaluate({\n\t\t\t\tengine: runtime.engine,\n\t\t\t\tagent: runtime.agent,\n\t\t\t\tscriptInstrumentationState,\n\t\t\t\tcurrent: {\n\t\t\t\t\tkind: \"final\",\n\t\t\t\t\trequest,\n\t\t\t\t\tlastToolStep,\n\t\t\t\t},\n\t\t\t})\n\t\t\tprogress?.(`final hook complete: ${definition.name}`)\n\t\t\tawait options.onRunUpdate?.({\n\t\t\t\tdefinition,\n\t\t\t\tmodel,\n\t\t\t\treasoningEffort: options.reasoningEffort,\n\t\t\t\trunNumber,\n\t\t\t\truntime,\n\t\t\t\ttranscriptInputMessages: new Map(transcriptInputMessages),\n\t\t\t})\n\t\t\tprogress?.(`agent turn end: ${definition.name}`)\n\t\t},\n\t}\n\n\ttry {\n\t\tprogress?.(`fixture load start: ${definition.fixture.id}`)\n\t\truntime = await definition.fixture.load({ definition, lifecycleHooks, onProgress: progress })\n\t\tprogress?.(`fixture load complete: ${definition.fixture.id}`)\n\t\tstate = await definition.options.prepareState?.(runtime.engine)\n\t\tawait options.onRunUpdate?.({\n\t\t\tdefinition,\n\t\t\tmodel,\n\t\t\treasoningEffort: options.reasoningEffort,\n\t\t\trunNumber,\n\t\t\truntime,\n\t\t\ttranscriptInputMessages: new Map(transcriptInputMessages),\n\t\t})\n\t\tprogress?.(`agent send start: ${definition.name} ${model}`)\n\t\tawait send({\n\t\t\tengine: runtime.engine,\n\t\t\tagent: runtime.agent,\n\t\t\treport,\n\t\t\tstate,\n\t\t\t...createAgentEvalHelpers(\n\t\t\t\t{\n\t\t\t\t\tagent: runtime.agent,\n\t\t\t\t\trequestStartIndex: runtime.replayRequestStartIndex,\n\t\t\t\t\tscriptInstrumentationState,\n\t\t\t\t},\n\t\t\t\t{ initialStepIndex: definition.options.stepIndex },\n\t\t\t),\n\t\t\tmodel,\n\t\t\treasoningEffort: options.reasoningEffort,\n\t\t\trunNumber,\n\t\t\tdefinition: runnableDefinition,\n\t\t\truntime,\n\t\t\tsignal: options.signal,\n\t\t\tscriptInstrumentationState,\n\t\t})\n\t\tstopped = earlyStop === undefined && isRunStopped(options.signal, runtime)\n\t\tprogress?.(`${stopped ? \"agent send stopped\" : \"agent send complete\"}: ${definition.name} ${model}`)\n\t} catch (runError) {\n\t\tstopped = earlyStop === undefined && isRunStopped(options.signal, runtime)\n\t\tif (stopped) {\n\t\t\tprogress?.(`run stopped: ${definition.name}`)\n\t\t} else {\n\t\t\terror = getRunErrorMessage(runError)\n\t\t\terrorStack = getRunErrorStack(runError)\n\t\t\tprogress?.(`run error: ${definition.name}: ${error}`)\n\t\t}\n\t} finally {\n\t\tprogress?.(`runtime dispose start: ${definition.name}`)\n\t\tawait runtime?.dispose?.()\n\t\tprogress?.(`runtime dispose complete: ${definition.name}`)\n\t}\n\n\tprogress?.(`result aggregation start: ${definition.name}`)\n\tconst checks = [...report.getChecks()]\n\tconst durationMs = Math.round(performance.now() - startedAt)\n\tconst runRequests = getRunRequests(runtime)\n\tconst tokenUsage = toAgentEvalTokenUsage(getRunRequestsUsage(runRequests))\n\tconst cost = getRunCost(runtime, model)\n\tconst totalToolSteps = getTotalToolSteps(runtime)\n\tconst toolStepNames = getToolStepNames(runtime)\n\tconst statistics = createRunStatistics(checks, durationMs, totalToolSteps, earlyStop)\n\tconst score = statistics.callbacks.total === 0 ? 0 : getWeightedScore(checks)\n\tconst result: AgentEvalRunResult = {\n\t\tevalId: definition.id,\n\t\tfixtureId: definition.fixture.id,\n\t\tname: definition.name,\n\t\tsourceFile: definition.sourceFile,\n\t\tmodel,\n\t\treasoningEffort: options.reasoningEffort,\n\t\trunNumber,\n\t\tstatus: getFinalRunStatus(checks, error, stopped),\n\t\tscore,\n\t\tdurationMs,\n\t\tcost,\n\t\ttokenUsage,\n\t\ttotalToolSteps,\n\t\ttoolStepNames: toolStepNames.length > 0 ? toolStepNames : undefined,\n\t\tstatistics,\n\t\tchecks,\n\t}\n\tprogress?.(`result aggregation complete: ${definition.name}`)\n\tlet finalResult: AgentEvalRunResult = error ? { ...result, error } : result\n\tif (options.transcript === true && runtime !== undefined) {\n\t\tprogress?.(`transcript write start: ${definition.name}`)\n\t\tconst writeTranscript = options.writeTranscript\n\t\tassert(writeTranscript !== undefined, \"Transcript writing is enabled but no transcript writer was provided.\")\n\t\tconst transcriptPath = await writeTranscript({\n\t\t\tresult: finalResult,\n\t\t\tchatMessages: runtime.agent.chatMessages,\n\t\t\ttree: runtime.engine.tree,\n\t\t\tinputMessages: transcriptInputMessages,\n\t\t})\n\t\tfinalResult = { ...finalResult, transcriptPath }\n\t\tprogress?.(`transcript write complete: ${definition.name}`)\n\t}\n\tprogress?.(`run complete: ${definition.name} ${finalResult.status}`)\n\treturn errorStack ? { ...finalResult, errorStack } : finalResult\n}\n\nexport async function runAgentEvalDefinitions(\n\tdefinitions: readonly AgentEvalDefinition[],\n\toptions: AgentEvalRunnerOptions,\n): Promise<readonly AgentEvalRunResult[]> {\n\tconst results: AgentEvalRunResult[] = []\n\toptions.onProgress?.(\n\t\t`run queue: ${definitions.length} evals x ${options.modelConfigs.length} model configs x ${options.runs} runs`,\n\t)\n\tlet runIndex = 0\n\tfor (let definitionIndex = 0; definitionIndex < definitions.length; definitionIndex++) {\n\t\tconst definition = definitions[definitionIndex]\n\t\tif (definition === undefined) continue\n\t\tfor (let modelConfigIndex = 0; modelConfigIndex < options.modelConfigs.length; modelConfigIndex++) {\n\t\t\tconst modelConfig = options.modelConfigs[modelConfigIndex]\n\t\t\tif (modelConfig === undefined) continue\n\t\t\tfor (let runNumber = 1; runNumber <= options.runs; runNumber++) {\n\t\t\t\tif (options.signal?.aborted) return results\n\t\t\t\tconst selectionContext: AgentEvalRunSelectionContext = {\n\t\t\t\t\tdefinition,\n\t\t\t\t\tmodelConfig,\n\t\t\t\t\trunNumber,\n\t\t\t\t\ttotalRuns: options.runs,\n\t\t\t\t\tdefinitionIndex,\n\t\t\t\t\tmodelConfigIndex,\n\t\t\t\t\trunIndex,\n\t\t\t\t}\n\t\t\t\trunIndex++\n\t\t\t\tif (options.shouldRun !== undefined && !options.shouldRun(selectionContext)) continue\n\t\t\t\tawait options.onRunStart?.(selectionContext)\n\t\t\t\tconst result = await runAgentEvalDefinition(definition, modelConfig.model, runNumber, {\n\t\t\t\t\treasoningEffort: modelConfig.reasoningEffort,\n\t\t\t\t\tsignal: options.signal,\n\t\t\t\t\tsend: options.send,\n\t\t\t\t\tonProgress: options.onProgress,\n\t\t\t\t\tonRunProgressMessage: message =>\n\t\t\t\t\t\toptions.onRunProgressMessage?.({\n\t\t\t\t\t\t\tdefinition,\n\t\t\t\t\t\t\tmodelConfig,\n\t\t\t\t\t\t\trunNumber,\n\t\t\t\t\t\t\ttotalRuns: options.runs,\n\t\t\t\t\t\t\tmessage,\n\t\t\t\t\t\t}),\n\t\t\t\t\tonRunProgress: checks =>\n\t\t\t\t\t\toptions.onRunProgress?.({\n\t\t\t\t\t\t\tdefinition,\n\t\t\t\t\t\t\tmodelConfig,\n\t\t\t\t\t\t\trunNumber,\n\t\t\t\t\t\t\ttotalRuns: options.runs,\n\t\t\t\t\t\t\tchecks,\n\t\t\t\t\t\t}),\n\t\t\t\t\ttranscript: options.transcript,\n\t\t\t\t\twriteTranscript: options.writeTranscript,\n\t\t\t\t\tonRunUpdate: options.onRunUpdate,\n\t\t\t\t})\n\t\t\t\tresults.push(result)\n\t\t\t\tawait options.onRunComplete?.(result)\n\t\t\t}\n\t\t}\n\t}\n\treturn results\n}\n", "import type { ModelMessage } from \"ai\"\nimport { isCommand } from \"app/ai/agents/dsl.ts\"\nimport { getRequestModelMessages, isCommandError } from \"app/ai/agents/messages.ts\"\nimport { commandToDSL } from \"app/ai/agents/nodeToDSLCommands.ts\"\nimport type { AgentRequest } from \"app/ai/agents/types.ts\"\nimport type { CanvasTree } from \"document/models/CanvasTree/CanvasTree.ts\"\nimport { createAgentEvalInputMessage } from \"./transcriptInput.ts\"\nimport type { AgentEvalRunResult } from \"./types.ts\"\n\nexport type AgentEvalTranscriptInputMessages = ReadonlyMap<string, ModelMessage>\n\nexport interface AgentEvalTranscript {\n\tschemaVersion: 1\n\tgeneratedAt: string\n\tresult: AgentEvalRunResult\n\tdslCommands: readonly string[]\n\tinputMessages: readonly ModelMessage[]\n\tresponseMessages: readonly ModelMessage[]\n}\n\nfunction collectDSLCommands(chatMessages: readonly AgentRequest[]): readonly string[] {\n\treturn chatMessages\n\t\t.flatMap(request => request.steps ?? [])\n\t\t.flatMap(step => step.content)\n\t\t.flatMap(part => (Array.isArray(part) ? part : []))\n\t\t.flatMap(line => {\n\t\t\tif (isCommand(line)) return [commandToDSL(line)]\n\t\t\tif (isCommandError(line)) return [line.raw]\n\t\t\treturn []\n\t\t})\n}\n\nexport function createAgentEvalTranscriptData(\n\tresult: AgentEvalRunResult,\n\tchatMessages: readonly AgentRequest[],\n\ttree: CanvasTree,\n\tinputMessages?: AgentEvalTranscriptInputMessages,\n): AgentEvalTranscript {\n\treturn {\n\t\tschemaVersion: 1,\n\t\tgeneratedAt: new Date().toISOString(),\n\t\tresult,\n\t\tdslCommands: collectDSLCommands(chatMessages),\n\t\tinputMessages: chatMessages.map(\n\t\t\trequest => inputMessages?.get(request.id) ?? createAgentEvalInputMessage(request, tree),\n\t\t),\n\t\tresponseMessages: chatMessages.flatMap(getRequestModelMessages),\n\t}\n}\n", "import { assertNever } from \"@framerjs/shared\"\nimport { formatAgentModelConfig } from \"app/ai/agentModelConfig.ts\"\nimport { agentEvalCategories } from \"./categoryStatistics.ts\"\nimport type { AgentEvalJsonReport } from \"./jsonReportTypes.ts\"\nimport type { AgentEvalCheckCategory, AgentEvalCheckResult } from \"./reportTypes.ts\"\nimport type { AgentEvalTokenUsage } from \"./tokenUsage.ts\"\nimport type { AgentEvalRunResult } from \"./types.ts\"\n\nexport type AgentEvalPanelRunStatus = \"passed\" | \"failed\" | \"error\" | \"stopped\"\n\nexport function createAgentEvalUiRunId(\n\trunInvocationId: string | undefined,\n\tevalId: string,\n\tmodel: AgentEvalRunResult[\"model\"],\n\treasoningEffort: AgentEvalRunResult[\"reasoningEffort\"],\n\trunNumber: number,\n): string {\n\tconst runConfigId = formatAgentModelConfig({ model, reasoningEffort })\n\tif (runInvocationId === undefined) return `${evalId}:${runConfigId}:${runNumber}`\n\treturn `${runInvocationId}:${evalId}:${runConfigId}:${runNumber}`\n}\n\nexport interface AgentEvalUiCheck {\n\tid: string\n\tcategory: AgentEvalCheckCategory\n\tname: string\n\tsourceFile: string\n\tgroup?: string\n\titem?: string\n\tstatus: \"passed\" | \"failed\"\n\tfailureTitle?: string\n\tmessage?: string\n\tassertion?: string\n\tachievedStep?: number\n\terror?: string\n\terrorStack?: string\n\texpected?: string\n\treceived?: string\n\tmatcher?: string\n\tdurationMs: number\n}\n\nexport interface AgentEvalUiFailedCheck extends AgentEvalUiCheck {\n\tstatus: \"failed\"\n\tfailureTitle: string\n}\n\nexport interface AgentEvalUiCategory {\n\tcategory: AgentEvalCheckCategory\n\tpassed: number\n\tfailed: number\n\ttotal: number\n\tlabel: string\n}\n\nexport interface AgentEvalUiFailedCheckGroup {\n\tid: string\n\tlabel: string\n\tchecks: readonly AgentEvalUiFailedCheck[]\n}\n\nexport interface AgentEvalUiRun {\n\tid: string\n\trunInvocationId?: string\n\tevalId: string\n\tfixtureId: string\n\tname: string\n\tsourceFile: string\n\tmodel: AgentEvalRunResult[\"model\"]\n\treasoningEffort?: AgentEvalRunResult[\"reasoningEffort\"]\n\trunNumber: number\n\tstatus: AgentEvalRunResult[\"status\"]\n\tdurationMs: number\n\tcost: number\n\ttokenUsage?: AgentEvalTokenUsage\n\ttotalToolSteps: number\n\terror?: string\n\terrorStack?: string\n\tpanelStatus: AgentEvalPanelRunStatus\n\tstatusLabel: string\n\ttotalChecks: number\n\tpassedChecks: number\n\tfailedCheckCount: number\n\tcategorySummaries: readonly string[]\n\tfailedChecks: readonly AgentEvalUiFailedCheck[]\n\tfailedCheckGroups: readonly AgentEvalUiFailedCheckGroup[]\n\tcategories: readonly AgentEvalUiCategory[]\n\tchecks: readonly AgentEvalUiCheck[]\n\trawResult: AgentEvalRunResult\n}\n\nexport interface AgentEvalUiReport {\n\tgeneratedAt: string\n\tsummary: AgentEvalJsonReport[\"summary\"]\n\truns: readonly AgentEvalUiRun[]\n}\n\nexport function mapAgentEvalRunStatusToPanelStatus(status: AgentEvalRunResult[\"status\"]): AgentEvalPanelRunStatus {\n\tswitch (status) {\n\t\tcase \"passed\":\n\t\t\treturn \"passed\"\n\t\tcase \"failed\":\n\t\t\treturn \"failed\"\n\t\tcase \"error\":\n\t\t\treturn \"error\"\n\t\tcase \"stopped\":\n\t\t\treturn \"stopped\"\n\t\tdefault:\n\t\t\tassertNever(status)\n\t}\n}\n\nfunction getStatusLabel(status: AgentEvalPanelRunStatus): string {\n\tswitch (status) {\n\t\tcase \"passed\":\n\t\t\treturn \"Passed\"\n\t\tcase \"failed\":\n\t\t\treturn \"Failed\"\n\t\tcase \"error\":\n\t\t\treturn \"Error\"\n\t\tcase \"stopped\":\n\t\t\treturn \"Stopped\"\n\t\tdefault:\n\t\t\tassertNever(status)\n\t}\n}\n\nfunction formatAgentEvalCheckCategory(category: AgentEvalCheckCategory): string {\n\treturn `${category.slice(0, 1).toUpperCase()}${category.slice(1)}`\n}\n\nfunction getFailedCheckTitle(check: AgentEvalCheckResult): string {\n\tconst parts = [formatAgentEvalCheckCategory(check.category), check.group, check.item]\n\tif (check.item !== check.name) parts.push(check.name)\n\treturn parts.filter(part => part !== undefined).join(\" \u203A \")\n}\n\nfunction adaptCheck(check: AgentEvalCheckResult, sourceFile: string): AgentEvalUiCheck {\n\tconst status: AgentEvalUiCheck[\"status\"] = check.passed ? \"passed\" : \"failed\"\n\tconst uiCheck = {\n\t\t...check,\n\t\tsourceFile,\n\t\tstatus,\n\t}\n\treturn status === \"failed\" ? { ...uiCheck, failureTitle: getFailedCheckTitle(check) } : uiCheck\n}\n\nfunction isFailedCheck(check: AgentEvalUiCheck): check is AgentEvalUiFailedCheck {\n\treturn check.status === \"failed\"\n}\n\nfunction getFailedCheckGroup(check: AgentEvalUiFailedCheck): AgentEvalUiFailedCheckGroup {\n\tconst categoryLabel = formatAgentEvalCheckCategory(check.category)\n\tif (check.group === undefined) return { id: check.category, label: categoryLabel, checks: [check] }\n\treturn {\n\t\tid: `${check.category}:${check.group}`,\n\t\tlabel: `${categoryLabel} \u203A ${check.group}`,\n\t\tchecks: [check],\n\t}\n}\n\nfunction groupFailedChecks(checks: readonly AgentEvalUiFailedCheck[]): readonly AgentEvalUiFailedCheckGroup[] {\n\tconst groups = new Map<string, AgentEvalUiFailedCheckGroup>()\n\n\tfor (const check of checks) {\n\t\tconst group = getFailedCheckGroup(check)\n\t\tconst existing = groups.get(group.id)\n\t\tif (existing) {\n\t\t\tgroups.set(group.id, { ...existing, checks: [...existing.checks, check] })\n\t\t} else {\n\t\t\tgroups.set(group.id, group)\n\t\t}\n\t}\n\n\treturn Array.from(groups.values())\n}\n\nexport function adaptAgentEvalRunResultToUiRun(result: AgentEvalRunResult, runInvocationId?: string): AgentEvalUiRun {\n\tconst panelStatus = mapAgentEvalRunStatusToPanelStatus(result.status)\n\tconst adaptedCategories = agentEvalCategories.map(category => {\n\t\tconst statistics = result.statistics.categories[category]\n\t\treturn Object.assign({ category }, statistics, {\n\t\t\tlabel: `${category} ${statistics.passed}/${statistics.total}`,\n\t\t})\n\t})\n\tconst checks = result.checks.map(check => adaptCheck(check, result.sourceFile))\n\tconst failedChecks = checks.filter(isFailedCheck)\n\treturn {\n\t\t...result,\n\t\tid: createAgentEvalUiRunId(runInvocationId, result.evalId, result.model, result.reasoningEffort, result.runNumber),\n\t\trunInvocationId,\n\t\tpanelStatus,\n\t\tstatusLabel: getStatusLabel(panelStatus),\n\t\ttotalChecks: result.statistics.callbacks.total,\n\t\tpassedChecks: result.statistics.callbacks.passed,\n\t\tfailedCheckCount: result.statistics.callbacks.failed,\n\t\tcategorySummaries: adaptedCategories.map(category => category.label),\n\t\tfailedChecks,\n\t\tfailedCheckGroups: groupFailedChecks(failedChecks),\n\t\tcategories: adaptedCategories,\n\t\tchecks,\n\t\trawResult: result,\n\t}\n}\n\nexport function adaptAgentEvalJsonReportToUiReport(\n\treport: AgentEvalJsonReport,\n\trunInvocationId?: string,\n): AgentEvalUiReport {\n\treturn {\n\t\t...report,\n\t\truns: report.results.map(result => adaptAgentEvalRunResultToUiRun(result, runInvocationId)),\n\t}\n}\n", "import type { AgentEvalDefinition } from \"./definition.ts\"\nimport { createAgentEvalJsonReport } from \"./jsonReport.ts\"\nimport type { AgentEvalJsonReport } from \"./jsonReportTypes.ts\"\nimport type { AgentEvalModelConfig } from \"./modelConfig.ts\"\nimport { runAgentEvalDefinitions } from \"./runner.ts\"\nimport type {\n\tAgentEvalRunProgressMessageContext,\n\tAgentEvalRunSelectionContext,\n\tAgentEvalRunStartContext,\n\tAgentEvalRunUpdate,\n\tAgentEvalTranscriptWriter,\n} from \"./runner.ts\"\nimport { createAgentEvalTranscriptData, type AgentEvalTranscript } from \"./transcriptData.ts\"\nimport type { AgentEvalRunResult, AgentEvalProgressLogger } from \"./types.ts\"\nimport {\n\tadaptAgentEvalJsonReportToUiReport,\n\tadaptAgentEvalRunResultToUiRun,\n\tcreateAgentEvalUiRunId,\n} from \"./uiAdapter.ts\"\nimport type { AgentEvalUiReport, AgentEvalUiRun } from \"./uiAdapter.ts\"\n\nlet nextBrowserRunInvocationIndex = 0\n\nexport interface AgentEvalBrowserRunnerOptions {\n\tmodelConfigs: readonly AgentEvalModelConfig[]\n\truns: number\n\tsignal?: AbortSignal\n\ttranscript?: boolean\n\tonProgress?: AgentEvalProgressLogger\n\tshouldRun?: (context: AgentEvalRunSelectionContext) => boolean\n\tonRunQueued?: (context: AgentEvalRunStartContext) => void | Promise<void>\n\tonRunStart?: (context: AgentEvalRunStartContext) => void | Promise<void>\n\tonRunProgressMessage?: (context: AgentEvalRunProgressMessageContext) => void\n\tonRunStopped?: (context: AgentEvalRunStartContext) => void | Promise<void>\n\tonRun?: (run: AgentEvalUiRun) => void | Promise<void>\n\tonRunUpdate?: (update: AgentEvalRunUpdate) => void | Promise<void>\n}\n\nexport interface AgentEvalBrowserRunnerResult {\n\tresults: readonly AgentEvalRunResult[]\n\treport: AgentEvalJsonReport\n\tuiReport: AgentEvalUiReport\n\ttranscripts: readonly AgentEvalBrowserTranscript[]\n}\n\nexport interface AgentEvalBrowserTranscript {\n\tpath: string\n\tdata: AgentEvalTranscript\n}\n\nfunction sanitizeFileNameSegment(value: string): string {\n\treturn value\n\t\t.replaceAll(/[^\\w.-]+/gu, \"-\")\n\t\t.replaceAll(/^-+|-+$/gu, \"\")\n\t\t.slice(0, 80)\n}\n\nfunction createBrowserTranscriptFileName(result: AgentEvalRunResult): string {\n\tconst sourceFileName = result.sourceFile.split(\"/\").at(-1) ?? result.sourceFile\n\tconst modelConfig = result.reasoningEffort === undefined ? result.model : `${result.model}=${result.reasoningEffort}`\n\tconst stem = [sourceFileName, result.evalId, modelConfig, `run-${result.runNumber}`]\n\t\t.map(sanitizeFileNameSegment)\n\t\t.join(\"__\")\n\treturn `${stem}.transcript.json`\n}\n\nfunction createBrowserTranscriptWriter(transcripts: AgentEvalBrowserTranscript[]): AgentEvalTranscriptWriter {\n\treturn async ({ result, chatMessages, tree, inputMessages }) => {\n\t\tconst transcriptPath = `agent-eval-transcripts/${createBrowserTranscriptFileName(result)}`\n\t\ttranscripts.push({\n\t\t\tpath: transcriptPath,\n\t\t\tdata: createAgentEvalTranscriptData(result, chatMessages, tree, inputMessages),\n\t\t})\n\t\treturn transcriptPath\n\t}\n}\n\nexport async function runAgentEvalDefinitionsForBrowser(\n\tdefinitions: readonly AgentEvalDefinition[],\n\toptions: AgentEvalBrowserRunnerOptions,\n): Promise<AgentEvalBrowserRunnerResult> {\n\tconst runInvocationId = `browser-run-${nextBrowserRunInvocationIndex++}`\n\tconst queuedRuns: AgentEvalRunStartContext[] = []\n\tconst completedRunIds = new Set<string>()\n\tconst transcripts: AgentEvalBrowserTranscript[] = []\n\tlet runIndex = 0\n\tfor (let definitionIndex = 0; definitionIndex < definitions.length; definitionIndex++) {\n\t\tconst definition = definitions[definitionIndex]\n\t\tif (definition === undefined) continue\n\t\tfor (let modelConfigIndex = 0; modelConfigIndex < options.modelConfigs.length; modelConfigIndex++) {\n\t\t\tconst modelConfig = options.modelConfigs[modelConfigIndex]\n\t\t\tif (modelConfig === undefined) continue\n\t\t\tfor (let runNumber = 1; runNumber <= options.runs; runNumber++) {\n\t\t\t\tconst context: AgentEvalRunSelectionContext = {\n\t\t\t\t\tdefinition,\n\t\t\t\t\tmodelConfig,\n\t\t\t\t\trunNumber,\n\t\t\t\t\ttotalRuns: options.runs,\n\t\t\t\t\trunInvocationId,\n\t\t\t\t\tdefinitionIndex,\n\t\t\t\t\tmodelConfigIndex,\n\t\t\t\t\trunIndex,\n\t\t\t\t}\n\t\t\t\trunIndex++\n\t\t\t\tif (options.shouldRun !== undefined && !options.shouldRun(context)) continue\n\t\t\t\tqueuedRuns.push(context)\n\t\t\t\tawait options.onRunQueued?.(context)\n\t\t\t}\n\t\t}\n\t}\n\tconst results = await runAgentEvalDefinitions(definitions, {\n\t\tmodelConfigs: options.modelConfigs,\n\t\truns: options.runs,\n\t\tsignal: options.signal,\n\t\ttranscript: options.transcript,\n\t\twriteTranscript: createBrowserTranscriptWriter(transcripts),\n\t\tonProgress: options.onProgress,\n\t\tshouldRun: options.shouldRun,\n\t\tonRunStart: context => options.onRunStart?.({ ...context, runInvocationId }),\n\t\tonRunProgressMessage: context => options.onRunProgressMessage?.({ ...context, runInvocationId }),\n\t\tonRunUpdate: update => options.onRunUpdate?.({ ...update, runInvocationId }),\n\t\tonRunComplete: async result => {\n\t\t\tconst run = adaptAgentEvalRunResultToUiRun(result, runInvocationId)\n\t\t\tcompletedRunIds.add(run.id)\n\t\t\tawait options.onRun?.(run)\n\t\t},\n\t})\n\tif (options.signal?.aborted) {\n\t\tfor (const queuedRun of queuedRuns) {\n\t\t\tif (completedRunIds.has(createRunId(queuedRun))) continue\n\t\t\tawait options.onRunStopped?.(queuedRun)\n\t\t}\n\t}\n\n\tconst report = createAgentEvalJsonReport(results)\n\treturn {\n\t\tresults,\n\t\treport,\n\t\tuiReport: adaptAgentEvalJsonReportToUiReport(report, runInvocationId),\n\t\ttranscripts,\n\t}\n}\n\nfunction createRunId(context: AgentEvalRunStartContext): string {\n\treturn createAgentEvalUiRunId(\n\t\tcontext.runInvocationId,\n\t\tcontext.definition.id,\n\t\tcontext.modelConfig.model,\n\t\tcontext.modelConfig.reasoningEffort,\n\t\tcontext.runNumber,\n\t)\n}\n", "import { registerAgentEval, withAgentEvalSourceFile as runWithAgentEvalSourceFile } from \"./definition.ts\"\n\nexport interface AgentEvalFileImporter {\n\tsourceFile: string\n\timportEvalFile: () => Promise<unknown>\n}\n\nexport function ensureAgentEvalExpectGlobal(\n\texpectGlobal: unknown,\n\thasExistingExpectGlobal: () => boolean = () => Reflect.get(globalThis, \"expect\") !== undefined,\n): void {\n\tif (hasExistingExpectGlobal()) return\n\tObject.defineProperty(globalThis, \"expect\", {\n\t\tvalue: expectGlobal,\n\t\tconfigurable: true,\n\t\twritable: true,\n\t})\n}\n\nexport async function withAgentEvalGlobal<T>(callback: () => Promise<T>): Promise<T> {\n\tconst hadOriginalEvaluation = Object.prototype.hasOwnProperty.call(globalThis, \"evaluation\")\n\tconst originalEvaluation = globalThis.evaluation\n\n\tObject.defineProperty(globalThis, \"evaluation\", {\n\t\tvalue: registerAgentEval,\n\t\tconfigurable: true,\n\t\twritable: true,\n\t})\n\n\ttry {\n\t\treturn await callback()\n\t} finally {\n\t\tif (hadOriginalEvaluation) {\n\t\t\tObject.defineProperty(globalThis, \"evaluation\", {\n\t\t\t\tvalue: originalEvaluation,\n\t\t\t\tconfigurable: true,\n\t\t\t\twritable: true,\n\t\t\t})\n\t\t} else {\n\t\t\tReflect.deleteProperty(globalThis, \"evaluation\")\n\t\t}\n\t}\n}\n\nexport async function importAgentEvalFilesWithGlobals(\n\timporters: readonly AgentEvalFileImporter[],\n\texpectGlobal: unknown,\n\thasExistingExpectGlobal?: () => boolean,\n): Promise<void> {\n\tensureAgentEvalExpectGlobal(expectGlobal, hasExistingExpectGlobal)\n\tawait withAgentEvalGlobal(async () => {\n\t\tfor (const importer of importers) {\n\t\t\t// Callers provide the import callback so this shared path stays browser-safe and Node-free.\n\t\t\tawait runWithAgentEvalSourceFile(importer.sourceFile, importer.importEvalFile)\n\t\t}\n\t})\n}\n", "import { isEqual } from \"library/render/utils/isEqual.ts\"\nimport { type AgentEvalFileImporter, importAgentEvalFilesWithGlobals } from \"./evalGlobals.ts\"\nimport { recordPassedAssertion } from \"./passedAssertionCapture.ts\"\n\ninterface BrowserEvalExpectation<T> {\n\treadonly not: BrowserEvalExpectation<T>\n\ttoBe(expected: T): void\n\ttoEqual(expected: unknown): void\n\ttoMatch(expected: string | RegExp): void\n\ttoMatchObject(expected: Record<string, unknown>): void\n\ttoBeDefined(): void\n\ttoBeUndefined(): void\n\ttoBeTruthy(): void\n\ttoBeFalsy(): void\n\ttoHaveLength(expected: number): void\n\ttoContain(expected: unknown): void\n\ttoContainEqual(expected: unknown): void\n\ttoBeCloseTo(expected: number, precision?: number): void\n\ttoBeGreaterThan(expected: number): void\n\ttoBeGreaterThanOrEqual(expected: number): void\n\ttoBeLessThan(expected: number): void\n\ttoBeLessThanOrEqual(expected: number): void\n}\n\ninterface BrowserEvalAnyConstructor {\n\treadonly name: string\n\treadonly prototype?: object\n}\n\nconst browserEvalAsymmetricMatcher = Symbol(\"BrowserEvalAsymmetricMatcher\")\n\ninterface BrowserEvalAsymmetricMatcher {\n\treadonly [browserEvalAsymmetricMatcher]: true\n\treadonly label: string\n\tmatches(actual: unknown): boolean\n}\n\ninterface BrowserEvalExpect {\n\t<T>(actual: T): BrowserEvalExpectation<T>\n\tany(expected: BrowserEvalAnyConstructor): BrowserEvalAsymmetricMatcher\n\tanything(): BrowserEvalAsymmetricMatcher\n\tarrayContaining(expected: readonly unknown[]): BrowserEvalAsymmetricMatcher\n\tobjectContaining(expected: Record<string, unknown>): BrowserEvalAsymmetricMatcher\n\tstringContaining(expected: string): BrowserEvalAsymmetricMatcher\n\tstringMatching(expected: string | RegExp): BrowserEvalAsymmetricMatcher\n}\n\nconst browserEvalExpect: BrowserEvalExpect = Object.assign(\n\t<T>(actual: T) => createBrowserEvalExpectation(actual, false),\n\t{\n\t\tany: (expected: BrowserEvalAnyConstructor) =>\n\t\t\tcreateBrowserEvalAsymmetricMatcher(`expect.any(${expected.name})`, actual =>\n\t\t\t\tmatchesAnyConstructor(actual, expected),\n\t\t\t),\n\t\tanything: () =>\n\t\t\tcreateBrowserEvalAsymmetricMatcher(\"expect.anything()\", actual => actual !== null && actual !== undefined),\n\t\tarrayContaining: (expected: readonly unknown[]) =>\n\t\t\tcreateBrowserEvalAsymmetricMatcher(`expect.arrayContaining(${formatValue(expected)})`, actual =>\n\t\t\t\tmatchesArrayContaining(actual, expected),\n\t\t\t),\n\t\tobjectContaining: (expected: Record<string, unknown>) =>\n\t\t\tcreateBrowserEvalAsymmetricMatcher(`expect.objectContaining(${formatValue(expected)})`, actual =>\n\t\t\t\tmatchesObjectContaining(actual, expected),\n\t\t\t),\n\t\tstringContaining: (expected: string) =>\n\t\t\tcreateBrowserEvalAsymmetricMatcher(`expect.stringContaining(${formatValue(expected)})`, actual =>\n\t\t\t\tmatchesStringContaining(actual, expected),\n\t\t\t),\n\t\tstringMatching: (expected: string | RegExp) =>\n\t\t\tcreateBrowserEvalAsymmetricMatcher(`expect.stringMatching(${formatValue(expected)})`, actual =>\n\t\t\t\tmatchesStringMatching(actual, expected),\n\t\t\t),\n\t},\n)\n\ninterface BrowserEvalAssertionDetails {\n\tmatcher: string\n\texpected?: string\n\treceived?: string\n}\n\nclass BrowserEvalAssertionError extends Error {\n\treadonly assertion: BrowserEvalAssertionDetails\n\n\tconstructor(message: string, assertion: BrowserEvalAssertionDetails) {\n\t\tsuper(message)\n\t\tthis.name = \"BrowserEvalAssertionError\"\n\t\tthis.assertion = assertion\n\t}\n}\n\nfunction createBrowserEvalAsymmetricMatcher(\n\tlabel: string,\n\tmatches: (actual: unknown) => boolean,\n): BrowserEvalAsymmetricMatcher {\n\treturn {\n\t\t[browserEvalAsymmetricMatcher]: true,\n\t\tlabel,\n\t\tmatches,\n\t}\n}\n\nfunction formatValue(value: unknown): string {\n\tif (isBrowserEvalAsymmetricMatcher(value)) return value.label\n\tif (value instanceof RegExp) return value.toString()\n\ttry {\n\t\treturn JSON.stringify(value) ?? String(value)\n\t} catch {\n\t\treturn String(value)\n\t}\n}\n\nfunction createBrowserEvalExpectation<T>(actual: T, negated: boolean): BrowserEvalExpectation<T> {\n\tfunction assertCondition(condition: boolean, message: string, assertion: BrowserEvalAssertionDetails): void {\n\t\tif (!negated === condition) {\n\t\t\trecordPassedAssertion({ message, ...assertion })\n\t\t\treturn\n\t\t}\n\t\tthrow new BrowserEvalAssertionError(message, assertion)\n\t}\n\n\tconst expectation: BrowserEvalExpectation<T> = {\n\t\tget not() {\n\t\t\treturn createBrowserEvalExpectation(actual, !negated)\n\t\t},\n\t\ttoBe: expected => {\n\t\t\tassertCondition(\n\t\t\t\tObject.is(actual, expected),\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be ${formatValue(expected)}`,\n\t\t\t\t{ matcher: negated ? \"not.toBe\" : \"toBe\", expected: formatValue(expected), received: formatValue(actual) },\n\t\t\t)\n\t\t},\n\t\ttoEqual: expected => {\n\t\t\tassertCondition(\n\t\t\t\tmatchesExpected(actual, expected),\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to equal ${formatValue(expected)}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toEqual\" : \"toEqual\",\n\t\t\t\t\texpected: formatValue(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoMatch: expected => {\n\t\t\tassertCondition(\n\t\t\t\tmatchesStringMatching(actual, expected),\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to match ${formatValue(expected)}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toMatch\" : \"toMatch\",\n\t\t\t\t\texpected: formatValue(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoMatchObject: expected => {\n\t\t\tassertCondition(\n\t\t\t\tmatchesObjectContaining(actual, expected),\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to match object ${formatValue(expected)}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toMatchObject\" : \"toMatchObject\",\n\t\t\t\t\texpected: formatValue(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoBeDefined: () => {\n\t\t\tassertCondition(actual !== undefined, `Expected value ${negated ? \"not \" : \"\"}to be defined`, {\n\t\t\t\tmatcher: negated ? \"not.toBeDefined\" : \"toBeDefined\",\n\t\t\t\texpected: negated ? \"undefined\" : \"defined\",\n\t\t\t\treceived: formatValue(actual),\n\t\t\t})\n\t\t},\n\t\ttoBeUndefined: () => {\n\t\t\tassertCondition(actual === undefined, `Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be undefined`, {\n\t\t\t\tmatcher: negated ? \"not.toBeUndefined\" : \"toBeUndefined\",\n\t\t\t\texpected: negated ? \"defined\" : \"undefined\",\n\t\t\t\treceived: formatValue(actual),\n\t\t\t})\n\t\t},\n\t\ttoBeTruthy: () => {\n\t\t\tassertCondition(Boolean(actual), `Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be truthy`, {\n\t\t\t\tmatcher: negated ? \"not.toBeTruthy\" : \"toBeTruthy\",\n\t\t\t\texpected: negated ? \"falsy\" : \"truthy\",\n\t\t\t\treceived: formatValue(actual),\n\t\t\t})\n\t\t},\n\t\ttoBeFalsy: () => {\n\t\t\tassertCondition(!actual, `Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be falsy`, {\n\t\t\t\tmatcher: negated ? \"not.toBeFalsy\" : \"toBeFalsy\",\n\t\t\t\texpected: negated ? \"truthy\" : \"falsy\",\n\t\t\t\treceived: formatValue(actual),\n\t\t\t})\n\t\t},\n\t\ttoHaveLength: expected => {\n\t\t\tconst actualLength = getLength(actual)\n\t\t\tassertCondition(\n\t\t\t\tactualLength === expected,\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to have length ${expected}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toHaveLength\" : \"toHaveLength\",\n\t\t\t\t\texpected: String(expected),\n\t\t\t\t\treceived: String(actualLength),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoContain: expected => {\n\t\t\tassertCondition(\n\t\t\t\tcontainsValue(actual, expected),\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to contain ${formatValue(expected)}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toContain\" : \"toContain\",\n\t\t\t\t\texpected: formatValue(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoContainEqual: expected => {\n\t\t\tassertCondition(\n\t\t\t\tcontainsEqualValue(actual, expected),\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to contain equal ${formatValue(expected)}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toContainEqual\" : \"toContainEqual\",\n\t\t\t\t\texpected: formatValue(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoBeCloseTo: (expected, precision = 2) => {\n\t\t\tconst difference = typeof actual === \"number\" ? Math.abs(actual - expected) : Number.POSITIVE_INFINITY\n\t\t\tconst threshold = 0.5 * 10 ** -precision\n\t\t\tassertCondition(\n\t\t\t\tdifference < threshold,\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be close to ${expected}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toBeCloseTo\" : \"toBeCloseTo\",\n\t\t\t\t\texpected: String(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoBeGreaterThan: expected => {\n\t\t\tassertCondition(\n\t\t\t\ttypeof actual === \"number\" && actual > expected,\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be > ${expected}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toBeGreaterThan\" : \"toBeGreaterThan\",\n\t\t\t\t\texpected: String(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoBeGreaterThanOrEqual: expected => {\n\t\t\tassertCondition(\n\t\t\t\ttypeof actual === \"number\" && actual >= expected,\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be >= ${expected}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toBeGreaterThanOrEqual\" : \"toBeGreaterThanOrEqual\",\n\t\t\t\t\texpected: String(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoBeLessThan: expected => {\n\t\t\tassertCondition(\n\t\t\t\ttypeof actual === \"number\" && actual < expected,\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be < ${expected}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toBeLessThan\" : \"toBeLessThan\",\n\t\t\t\t\texpected: String(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t\ttoBeLessThanOrEqual: expected => {\n\t\t\tassertCondition(\n\t\t\t\ttypeof actual === \"number\" && actual <= expected,\n\t\t\t\t`Expected ${formatValue(actual)} ${negated ? \"not \" : \"\"}to be <= ${expected}`,\n\t\t\t\t{\n\t\t\t\t\tmatcher: negated ? \"not.toBeLessThanOrEqual\" : \"toBeLessThanOrEqual\",\n\t\t\t\t\texpected: String(expected),\n\t\t\t\t\treceived: formatValue(actual),\n\t\t\t\t},\n\t\t\t)\n\t\t},\n\t}\n\treturn expectation\n}\n\nfunction isObjectLike(value: unknown): value is object {\n\treturn (typeof value === \"object\" && value !== null) || typeof value === \"function\"\n}\n\nfunction isPlainObject(value: unknown): value is Record<string, unknown> {\n\tif (!isObjectLike(value) || Array.isArray(value)) return false\n\tconst prototype = Object.getPrototypeOf(value)\n\treturn prototype === Object.prototype || prototype === null\n}\n\nfunction isBrowserEvalAsymmetricMatcher(value: unknown): value is BrowserEvalAsymmetricMatcher {\n\treturn (\n\t\tisObjectLike(value) &&\n\t\tReflect.get(value, browserEvalAsymmetricMatcher) === true &&\n\t\ttypeof Reflect.get(value, \"matches\") === \"function\"\n\t)\n}\n\nfunction matchesExpected(actual: unknown, expected: unknown): boolean {\n\tif (isBrowserEvalAsymmetricMatcher(expected)) return expected.matches(actual)\n\tif (!containsAsymmetricMatcher(expected)) return isEqual(actual, expected)\n\tif (Array.isArray(expected)) {\n\t\tif (!Array.isArray(actual) || actual.length !== expected.length) return false\n\t\treturn expected.every((expectedItem, index) => matchesExpected(actual[index], expectedItem))\n\t}\n\tif (isObjectLike(actual) && isObjectLike(expected)) return matchesObjectExactly(actual, expected)\n\treturn isEqual(actual, expected)\n}\n\nfunction containsAsymmetricMatcher(value: unknown, seen = new Set<object>()): boolean {\n\tif (isBrowserEvalAsymmetricMatcher(value)) return true\n\tif (!isObjectLike(value) || seen.has(value)) return false\n\tseen.add(value)\n\tif (Array.isArray(value)) return value.some(item => containsAsymmetricMatcher(item, seen))\n\treturn Object.keys(value).some(key => containsAsymmetricMatcher(Reflect.get(value, key), seen))\n}\n\nfunction matchesObjectExactly(actual: object, expected: object): boolean {\n\tconst actualKeys = Object.keys(actual)\n\tconst expectedKeys = Object.keys(expected)\n\tif (actualKeys.length !== expectedKeys.length) return false\n\tfor (const key of expectedKeys) {\n\t\tif (!Object.prototype.hasOwnProperty.call(actual, key)) return false\n\t\tif (!matchesExpected(Reflect.get(actual, key), Reflect.get(expected, key))) return false\n\t}\n\treturn true\n}\n\nfunction matchesObjectContaining(actual: unknown, expected: Record<string, unknown>): boolean {\n\tif (!isObjectLike(actual)) return false\n\tfor (const key of Object.keys(expected)) {\n\t\tif (!hasPropertyInObject(actual, key)) return false\n\t\tif (!matchesContainedExpected(Reflect.get(actual, key), Reflect.get(expected, key))) return false\n\t}\n\treturn true\n}\n\n/** Same as Jest's `hasPropertyInObject` from `@jest/expect-utils`. */\nfunction hasPropertyInObject(object: unknown, key: string): boolean {\n\tif (!isObjectLike(object) || object === Object.prototype) return false\n\tif (Object.prototype.hasOwnProperty.call(object, key)) return true\n\treturn hasPropertyInObject(Object.getPrototypeOf(object), key)\n}\n\nfunction matchesContainedExpected(actual: unknown, expected: unknown): boolean {\n\tif (isBrowserEvalAsymmetricMatcher(expected)) return expected.matches(actual)\n\tif (Array.isArray(expected)) return matchesContainedArray(actual, expected)\n\tif (isPlainObject(expected)) return matchesObjectContaining(actual, expected)\n\treturn isEqual(actual, expected)\n}\n\nfunction matchesContainedArray(actual: unknown, expected: readonly unknown[]): boolean {\n\tif (!Array.isArray(actual) || actual.length !== expected.length) return false\n\treturn expected.every((expectedItem, index) => matchesContainedExpected(actual[index], expectedItem))\n}\n\nfunction matchesArrayContaining(actual: unknown, expected: readonly unknown[]): boolean {\n\tif (!Array.isArray(actual)) return false\n\treturn expected.every(expectedItem => actual.some(actualItem => matchesExpected(actualItem, expectedItem)))\n}\n\nfunction matchesStringContaining(actual: unknown, expected: string): boolean {\n\treturn typeof actual === \"string\" && actual.includes(expected)\n}\n\nfunction matchesStringMatching(actual: unknown, expected: string | RegExp): boolean {\n\tif (typeof actual !== \"string\") return false\n\tif (typeof expected === \"string\") return actual.includes(expected)\n\texpected.lastIndex = 0\n\treturn expected.test(actual)\n}\n\nfunction matchesAnyConstructor(actual: unknown, expected: BrowserEvalAnyConstructor): boolean {\n\tif (expected === String) return typeof actual === \"string\" || actual instanceof String\n\tif (expected === Number) return typeof actual === \"number\" || actual instanceof Number\n\tif (expected === Boolean) return typeof actual === \"boolean\" || actual instanceof Boolean\n\tif (expected === Function) return typeof actual === \"function\"\n\tif (expected === Object) return isObjectLike(actual)\n\tif (expected === Array) return Array.isArray(actual)\n\tif (!isObjectLike(actual) || expected.prototype === undefined) return false\n\treturn Object.prototype.isPrototypeOf.call(expected.prototype, Object(actual))\n}\n\nfunction getLength(value: unknown): number | undefined {\n\tif (value === null || value === undefined) return undefined\n\tconst length = Reflect.get(Object(value), \"length\")\n\treturn typeof length === \"number\" ? length : undefined\n}\n\nfunction containsValue(actual: unknown, expected: unknown): boolean {\n\tif (typeof actual === \"string\") return typeof expected === \"string\" && actual.includes(expected)\n\tif (Array.isArray(actual)) return actual.some(value => matchesExpected(value, expected))\n\treturn false\n}\n\nfunction containsEqualValue(actual: unknown, expected: unknown): boolean {\n\tif (!isIterable(actual)) return false\n\tfor (const value of actual) {\n\t\tif (matchesExpected(value, expected)) return true\n\t}\n\treturn false\n}\n\nfunction isIterable(value: unknown): value is Iterable<unknown> {\n\treturn value !== null && value !== undefined && typeof Reflect.get(Object(value), Symbol.iterator) === \"function\"\n}\n\nexport function importBrowserAgentEvalFilesWithGlobalScope(importers: readonly AgentEvalFileImporter[]): Promise<void> {\n\treturn importAgentEvalFilesWithGlobals(importers, browserEvalExpect)\n}\n\nexport const testing = {\n\texpect: browserEvalExpect,\n}\n", "\nimport { importBrowserAgentEvalFilesWithGlobalScope } from \"/Users/alex/Projects/FramerStudio/src/app/vekter/src/app/ai/agents/evals2/harness/browserEvalGlobals.ts\"\n\nconst importers = [\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/breakpoints/overlappingBreakpoint.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-0\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/checklist/checklistBehavior.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-1\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/addMarkdownArticle.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-2\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/cmsCore.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-3\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/cmsDetailPageNavigation.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-4\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/cmsFieldConversions.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-5\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/cmsFilterListByStaticEnum.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-6\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/cmsMoveItems.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-7\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/componentPresetRichText.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-8\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/csvImportIntoExistingCollections.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-9\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/limitJobsPagination.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-10\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/cms/uploadCsvCollection.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-11\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/component/buttonComponentControls.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-12\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/component/create-component-with-variants.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-13\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/component/edit-source-from-component-instance.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-14\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/component/newTestimonialComponent.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-15\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/component/requestCodeFileChanges.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-16\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/computedValues/convertBooleanToColor.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-17\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/computedValues/convertBooleanToString.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-18\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/computedValues/greaterThan.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-19\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/computedValues/numberToStringCurrency.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-20\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/creation.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-21\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/creationQuestions.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-22\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/dynamicFilters/dynamicFilters.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-23\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/dynamicFilters/dynamicFiltersEnum.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-24\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/fonts.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-25\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/forms/contactForm.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-26\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/images/cmsImageAttributes.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-27\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/images/regularImageAttributes.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-28\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/images/unsplashImageSize.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-29\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/absolutePinning.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-30\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/centeredNavigation.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-31\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/dataListColumns.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-32\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/denseGrid.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-33\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/featureImageGrid.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-34\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/fixedColumnDenseGrid.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-35\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/imageGrid2x2.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-36\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/logoStackSpacing.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-37\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/makeImageWider.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-38\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/minColumnDenseGrid.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-39\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/navFractions.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-40\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layout/responsiveGridToStack.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-41\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplateAssign.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-42\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplateChildFill.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-43\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplateControl.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-44\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplateCreate.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-45\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplatePageStructure.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-46\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplatePositioning.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-47\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplateTheme.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-48\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/layoutTemplate/layoutTemplateUsage.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-49\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkExternal.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-50\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkInternalPage.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-51\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkInternalSection.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-52\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkNewTab.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-53\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkRel.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-54\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkRemove.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-55\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkRichTextWord.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-56\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/link/linkTrackingId.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-57\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/navigations/navigations.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-58\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/overlay/componentInstanceOverlay.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-59\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/overlay/overlayInteractions.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-60\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/overlay/variantTransition.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-61\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/prematureCompletion.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-62\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/prose/prose.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-63\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/reuse/reuse.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-64\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/richText/createWordColors.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-65\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/richText/formatRichText.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-66\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/richText/tables.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-67\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/richText/updateWordColor.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-68\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/shaders/addShader.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-69\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/shaders/updateShader.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-70\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/style/accentColor.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-71\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/style/cardBoxShadows.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-72\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/addLargeAndUpdateOthers.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-73\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/addResponsiveBreakpoints.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-74\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/minWidthOrder.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-75\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/removeSlot.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-76\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/updateAndRemove.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-77\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/updateExistingAddNew.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-78\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/textStylePresetBreakpoint/updateParagraphSpacing.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-79\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/thinking/thinkingLatency.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-80\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/vectorSets/replaceWithIcon.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-81\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/vision.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-82\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/scenarios/workingScope/pageRouting.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-83\") },\n\t{ sourceFile: \"src/app/ai/agents/evals2/unsupportedCapabilities.eval.ts\", importEvalFile: () => import(\"agent-evals-browser-manifest/eval-84\") }\n]\n\nexport async function importBundledAgentEvalFiles(_dir) {\n\tawait importBrowserAgentEvalFilesWithGlobalScope(importers)\n\treturn true\n}\n\t\t\t\t\t", "import type { AgentEvalDefinition } from \"./definition.ts\"\n\nexport function filterAgentEvalDefinitions(\n\tdefinitions: readonly AgentEvalDefinition[],\n\tmaxSteps: number | undefined,\n\tevalPattern?: string | undefined,\n): readonly AgentEvalDefinition[] {\n\tconst maxStepFiltered =\n\t\tmaxSteps === undefined ? definitions : definitions.filter(definition => definition.options.maxSteps === maxSteps)\n\tif (evalPattern === undefined) return maxStepFiltered\n\n\tconst normalizedPattern = evalPattern.trim().toLowerCase()\n\tif (normalizedPattern.length === 0) return maxStepFiltered\n\n\tconst patternMatches = (candidates: readonly AgentEvalDefinition[]) =>\n\t\tcandidates.filter(definition => {\n\t\t\tconst matches = [definition.name, definition.id, definition.sourceFile]\n\t\t\treturn matches.some(candidate => candidate.toLowerCase().includes(normalizedPattern))\n\t\t})\n\n\tconst maxStepMatches = patternMatches(maxStepFiltered)\n\tif (maxStepMatches.length > 0) return maxStepMatches\n\tif (maxSteps === undefined) return maxStepMatches\n\n\tconst patternMatchesAcrossMaxSteps = patternMatches(definitions)\n\treturn patternMatchesAcrossMaxSteps.length === 1 ? patternMatchesAcrossMaxSteps : []\n}\n", "import { importBundledAgentEvalFiles } from \"./bundledEvalFiles.ts\"\nimport type { importEvalFiles as importEvalFilesType, walkEvalFiles as walkEvalFilesType } from \"./cli/discovery.ts\"\nimport { getRegisteredAgentEvals } from \"./definition.ts\"\nimport type { AgentEvalDefinition } from \"./definition.ts\"\nimport { filterAgentEvalDefinitions } from \"./definitionFilter.ts\"\n\ninterface ImportAgentEvalDefinitionsOptions {\n\tdir?: string\n\tfilter?: string\n\tmaxSteps?: number\n}\n\nfunction getDefaultImportDir(): string {\n\treturn typeof process === \"undefined\" ? \".\" : process.cwd()\n}\n\nexport async function importAgentEvalDefinitions(\n\toptions: ImportAgentEvalDefinitionsOptions = {},\n): Promise<readonly AgentEvalDefinition[]> {\n\tconst dir = options.dir ?? getDefaultImportDir()\n\tif (getRegisteredAgentEvals().length === 0) {\n\t\tconst importedBundledEvalFiles = await importBundledAgentEvalFiles(dir)\n\t\t// Browser eval builds replace bundledEvalFiles.ts with a generated manifest of eval imports.\n\t\tif (!importedBundledEvalFiles) {\n\t\t\t// Keep CLI discovery out of browser eval chunks; the split path keeps bundlers from\n\t\t\t// resolving this Node fs/path import statically.\n\t\t\tconst cliDiscoveryModule = \"./cli/\" + \"discovery.ts\"\n\t\t\tconst { importEvalFiles, walkEvalFiles } = (await import(cliDiscoveryModule)) as {\n\t\t\t\timportEvalFiles: typeof importEvalFilesType\n\t\t\t\twalkEvalFiles: typeof walkEvalFilesType\n\t\t\t}\n\t\t\tawait importEvalFiles(await walkEvalFiles(dir))\n\t\t}\n\t}\n\n\treturn filterAgentEvalDefinitions(getRegisteredAgentEvals(), options.maxSteps, options.filter)\n}\n", "import { assert } from \"@framerjs/shared/src/assert.ts\"\nimport { defaultModels as defaultAgentUserModels } from \"app/agent/components/ModelPicker/models.ts\"\nimport { parseAgentModelConfig, type AgentModelConfig } from \"app/ai/agentModelConfig.ts\"\nimport { LanguageModel } from \"app/ai/languageModels.ts\"\nimport { getDefaultReasoningEffortForModel, type AgentReasoningEffort } from \"app/ai/models.ts\"\n\nexport type AgentEvalModelConfig = AgentModelConfig\n\nexport const defaultAgentEvalRunCount = 2\n\nconst defaultAgentEvalModels = [...defaultAgentUserModels, LanguageModel.Contour] as const\nconst defaultAgentBrowserEvalModels = [...defaultAgentUserModels, LanguageModel.GPTNEXT, LanguageModel.Contour] as const\n\n// CI should exercise the same default model choices users see without advanced controls.\nexport const defaultAgentEvalModelConfigs: readonly AgentEvalModelConfig[] =\n\tcreateDefaultAgentEvalModelConfigs(defaultAgentEvalModels)\n\nexport const defaultAgentBrowserEvalModelConfigs: readonly AgentEvalModelConfig[] =\n\tcreateDefaultAgentEvalModelConfigs(defaultAgentBrowserEvalModels)\n\nfunction createDefaultAgentEvalModelConfigs(models: readonly LanguageModel[]): readonly AgentEvalModelConfig[] {\n\treturn models.map(model => ({\n\t\tmodel,\n\t\t// The agent UI always submits a concrete selected effort; mirror that instead of the runtime's omitted-effort fallback.\n\t\treasoningEffort: getDefaultReasoningEffortForModel(model),\n\t}))\n}\n\nexport function getEffectiveAgentEvalReasoningEffort(config: AgentEvalModelConfig): AgentReasoningEffort {\n\treturn config.reasoningEffort ?? getDefaultReasoningEffortForModel(config.model)\n}\n\nexport function formatModelConfigForDisplay(config: AgentEvalModelConfig): string {\n\treturn `${config.model} (${getEffectiveAgentEvalReasoningEffort(config)})`\n}\n\nexport function parseAgentEvalModelConfig(value: string): AgentEvalModelConfig {\n\treturn parseAgentModelConfig(value, \"MODELS entry\")\n}\n\nexport function parseAgentEvalModelConfigs(\n\tvalue: string | undefined,\n\tdefaultModelConfigs: readonly AgentEvalModelConfig[] = defaultAgentEvalModelConfigs,\n): readonly AgentEvalModelConfig[] {\n\tif (!value) return defaultModelConfigs\n\tassert(!/\\s/u.test(value), \"MODELS must be a comma-separated list without spaces.\")\n\tconst modelConfigs = value.split(\",\").map(parseAgentEvalModelConfig)\n\treturn modelConfigs.length > 0 ? modelConfigs : defaultModelConfigs\n}\n", "import type { AgentEvalDefinition } from \"app/ai/agents/evals2/harness/definition.ts\"\nimport { filterAgentEvalDefinitions as filterHarnessAgentEvalDefinitions } from \"app/ai/agents/evals2/harness/definitionFilter.ts\"\nimport type { AgentEvalModelConfig } from \"app/ai/agents/evals2/harness/modelConfig.ts\"\nimport type { AgentEvalRunSelectionContext } from \"app/ai/agents/evals2/harness/runner.ts\"\nimport { isLanguageModel } from \"app/ai/languageModels.ts\"\nimport { isAgentReasoningEffort, isValidEffortForModel } from \"app/ai/models.ts\"\nimport { isObject } from \"utils/typeChecks.ts\"\n\nexport interface EvalRunOptions {\n\tparallelism: number\n\tindex: number\n\tmodels?: readonly AgentEvalModelConfig[]\n\trunCount?: number\n\tevalPattern?: string\n\tmaxSteps?: number\n\ttranscript?: boolean\n}\n\ninterface AgentEvalDefinitionView {\n\tid: string\n\ttitle: string\n\tdescription: string\n}\n\ninterface AgentEvalShardRunSummary {\n\tevalIds: ReadonlySet<string>\n\trunCount: number\n\ttotalRunCount: number\n}\n\nfunction getShortSourcePath(path: string): string {\n\tconst trimmed = path.trim().replaceAll(\"\\\\\", \"/\")\n\tconst segments = trimmed.split(\"/\").filter(Boolean)\n\tconst fileName = segments.at(-1)\n\tif (segments.length < 2 || !fileName) return path\n\n\treturn `${segments.at(-2)}/${fileName}`\n}\n\nexport function validateEvalRunOptions(value: unknown): EvalRunOptions {\n\tif (!isObject(value) || !(\"parallelism\" in value) || !(\"index\" in value)) {\n\t\tthrow new Error(\"Vekter.evals.run expects an options object with parallelism and index.\")\n\t}\n\n\tconst { parallelism, index } = value\n\n\tif (typeof parallelism !== \"number\" || !Number.isInteger(parallelism) || parallelism <= 0) {\n\t\tthrow new Error(\"Vekter.evals.run requires parallelism to be a positive integer.\")\n\t}\n\tif (typeof index !== \"number\" || !Number.isInteger(index) || index < 0 || index >= parallelism) {\n\t\tthrow new Error(\"Vekter.evals.run requires index to be an integer where 0 <= index < parallelism.\")\n\t}\n\n\tconst options: EvalRunOptions = { parallelism, index }\n\tif (value.models !== undefined) {\n\t\tif (!Array.isArray(value.models) || value.models.length === 0 || !value.models.every(isEvalModelConfig)) {\n\t\t\tthrow new Error(\"Vekter.evals.run requires models to be a non-empty array of supported model configs.\")\n\t\t}\n\t\toptions.models = value.models\n\t}\n\tif (value.runCount !== undefined) {\n\t\tif (typeof value.runCount !== \"number\" || !Number.isInteger(value.runCount) || value.runCount <= 0) {\n\t\t\tthrow new Error(\"Vekter.evals.run requires runCount to be a positive integer.\")\n\t\t}\n\t\toptions.runCount = value.runCount\n\t}\n\tif (value.evalPattern !== undefined) {\n\t\tif (typeof value.evalPattern !== \"string\") {\n\t\t\tthrow new Error(\"Vekter.evals.run requires evalPattern to be a string.\")\n\t\t}\n\t\tconst evalPattern = value.evalPattern.trim()\n\t\tif (evalPattern.length > 0) options.evalPattern = evalPattern\n\t}\n\tif (value.maxSteps !== undefined) {\n\t\tif (typeof value.maxSteps !== \"number\" || !Number.isInteger(value.maxSteps) || value.maxSteps < 0) {\n\t\t\tthrow new Error(\"Vekter.evals.run requires maxSteps to be a non-negative integer.\")\n\t\t}\n\t\toptions.maxSteps = value.maxSteps\n\t}\n\tif (value.transcript !== undefined) {\n\t\tif (typeof value.transcript !== \"boolean\") {\n\t\t\tthrow new Error(\"Vekter.evals.run requires transcript to be a boolean.\")\n\t\t}\n\t\toptions.transcript = value.transcript\n\t}\n\n\treturn options\n}\n\nfunction isEvalModelConfig(value: unknown): value is AgentEvalModelConfig {\n\tif (!isObject(value)) return false\n\tconst { model, reasoningEffort } = value\n\treturn (\n\t\tisLanguageModel(model) &&\n\t\t(reasoningEffort === undefined ||\n\t\t\t(isAgentReasoningEffort(reasoningEffort) && isValidEffortForModel(reasoningEffort, model)))\n\t)\n}\n\nexport function getAgentEvalDefinitionView(definition: AgentEvalDefinition): AgentEvalDefinitionView {\n\tconst maxSteps = definition.options.maxSteps === undefined ? \"all\" : definition.options.maxSteps\n\treturn {\n\t\tid: definition.id,\n\t\ttitle: definition.name,\n\t\tdescription: `steps: ${maxSteps} - ${getShortSourcePath(definition.sourceFile)}`,\n\t}\n}\n\nexport function filterAgentEvalDefinitions(\n\tdefinitions: readonly AgentEvalDefinition[],\n\tquery: string,\n): readonly AgentEvalDefinition[] {\n\tconst normalizedQuery = query.trim().toLocaleLowerCase()\n\tif (!normalizedQuery) return definitions\n\n\treturn definitions.filter(definition => doesAgentEvalDefinitionMatchFilter(definition, normalizedQuery))\n}\n\nfunction doesAgentEvalDefinitionMatchFilter(definition: AgentEvalDefinition, normalizedQuery: string): boolean {\n\tconst view = getAgentEvalDefinitionView(definition)\n\treturn [definition.id, definition.name, definition.sourceFile, definition.fixture.id, view.description].some(value =>\n\t\tvalue.toLocaleLowerCase().includes(normalizedQuery),\n\t)\n}\n\nexport function getAgentEvalDefinitionsForRunOptions(\n\tdefinitions: readonly AgentEvalDefinition[],\n\toptions: EvalRunOptions,\n): readonly AgentEvalDefinition[] {\n\treturn filterHarnessAgentEvalDefinitions(definitions, options.maxSteps, options.evalPattern)\n}\n\nexport function isAgentEvalRunSelectedForShard(\n\tcontext: AgentEvalRunSelectionContext,\n\toptions: EvalRunOptions,\n): boolean {\n\treturn context.runIndex % options.parallelism === options.index\n}\n\nexport function* iterateAgentEvalRunSelectionContexts(\n\tdefinitions: readonly AgentEvalDefinition[],\n\tmodelConfigs: readonly AgentEvalModelConfig[],\n\truns: number,\n): Generator<AgentEvalRunSelectionContext> {\n\tlet runIndex = 0\n\tfor (let definitionIndex = 0; definitionIndex < definitions.length; definitionIndex++) {\n\t\tconst definition = definitions[definitionIndex]\n\t\tif (definition === undefined) continue\n\t\tfor (let modelConfigIndex = 0; modelConfigIndex < modelConfigs.length; modelConfigIndex++) {\n\t\t\tconst modelConfig = modelConfigs[modelConfigIndex]\n\t\t\tif (modelConfig === undefined) continue\n\t\t\tfor (let runNumber = 1; runNumber <= runs; runNumber++) {\n\t\t\t\tyield {\n\t\t\t\t\tdefinition,\n\t\t\t\t\tmodelConfig,\n\t\t\t\t\trunNumber,\n\t\t\t\t\ttotalRuns: runs,\n\t\t\t\t\tdefinitionIndex,\n\t\t\t\t\tmodelConfigIndex,\n\t\t\t\t\trunIndex,\n\t\t\t\t}\n\t\t\t\trunIndex++\n\t\t\t}\n\t\t}\n\t}\n}\n\nexport function getAgentEvalShardRunSummary(\n\tdefinitions: readonly AgentEvalDefinition[],\n\tmodelConfigs: readonly AgentEvalModelConfig[],\n\truns: number,\n\toptions: EvalRunOptions,\n): AgentEvalShardRunSummary {\n\tconst evalIds = new Set<string>()\n\tconst filteredDefinitions = getAgentEvalDefinitionsForRunOptions(definitions, options)\n\tlet runCount = 0\n\tlet totalRunCount = 0\n\tfor (const context of iterateAgentEvalRunSelectionContexts(filteredDefinitions, modelConfigs, runs)) {\n\t\ttotalRunCount++\n\t\tif (!isAgentEvalRunSelectedForShard(context, options)) continue\n\t\trunCount++\n\t\tevalIds.add(context.definition.id)\n\t}\n\treturn { evalIds, runCount, totalRunCount }\n}\n", "import type { AgentID } from \"app/ai/agents/Agent.ts\"\nimport type { AgentEvalJsonReport } from \"app/ai/agents/evals2/harness/jsonReportTypes.ts\"\nimport type { AgentEvalTranscriptInputMessages } from \"app/ai/agents/evals2/harness/transcriptData.ts\"\nimport {\n\tadaptAgentEvalJsonReportToUiReport,\n\tcreateAgentEvalUiRunId,\n\ttype AgentEvalUiRun,\n} from \"app/ai/agents/evals2/harness/uiAdapter.ts\"\nimport type { AgentRequest } from \"app/ai/agents/types.ts\"\nimport type { LanguageModel } from \"app/ai/languageModels.ts\"\nimport type { AgentReasoningEffort } from \"app/ai/models.ts\"\nimport type { CanvasTree, NodeID } from \"document/models/CanvasTree/index.ts\"\nimport type { EvalRunOptions } from \"./evalDefinitions.ts\"\n\nlet currentEvalRunOptions: EvalRunOptions = { parallelism: 1, index: 0 }\nconst runOptionsListeners = new Set<() => void>()\n\ntype EvaluationRunStatus = \"queued\" | \"loading\" | \"running\" | \"passed\" | \"failed\" | \"error\" | \"stopped\"\n\nexport interface EvaluationRunRecord {\n\tid: string\n\trunInvocationId?: string\n\tevalId: string\n\trunNumber: number\n\tstatus: EvaluationRunStatus\n\tmodel?: LanguageModel\n\treasoningEffort?: AgentReasoningEffort\n\tprogress?: string\n\ttree?: CanvasTree\n\tagentId?: AgentID\n\tscopeId?: NodeID\n\tselectedNodeId?: NodeID\n\trequests?: readonly AgentRequest[]\n\ttranscriptInputMessages?: AgentEvalTranscriptInputMessages\n\terror?: string\n\tharnessRun?: AgentEvalUiRun\n\tstartedAt?: number\n\tfinishedAt?: number\n}\n\ninterface EvaluationRunViewState {\n\tactiveEvalId?: string\n\tactiveRunId?: string\n\tmanuallySelectedRunId?: string\n\tmountedRunId?: string\n\tlatestReport?: AgentEvalJsonReport\n\trecords: Readonly<Record<string, EvaluationRunRecord>>\n\trunIdsByEvalId: Readonly<Record<string, readonly string[]>>\n}\n\nlet currentEvalRunViewState: EvaluationRunViewState = { records: {}, runIdsByEvalId: {} }\nconst runViewListeners = new Set<() => void>()\n\nexport function getCurrentEvalRunOptions(): EvalRunOptions {\n\treturn currentEvalRunOptions\n}\n\nexport function setCurrentEvalRunOptions(options: EvalRunOptions) {\n\tcurrentEvalRunOptions = options\n\tfor (const listener of runOptionsListeners) listener()\n}\n\nexport function subscribeToEvalRunOptions(listener: () => void): () => void {\n\trunOptionsListeners.add(listener)\n\treturn () => runOptionsListeners.delete(listener)\n}\n\nexport function getCurrentEvalRunViewState(): EvaluationRunViewState {\n\treturn currentEvalRunViewState\n}\n\nexport function subscribeToEvalRunViewState(listener: () => void): () => void {\n\trunViewListeners.add(listener)\n\treturn () => runViewListeners.delete(listener)\n}\n\ninterface ActiveRunSelectionOptions {\n\tmanuallySelected?: boolean\n}\n\nexport function setActiveEvalId(id: string | undefined, options: ActiveRunSelectionOptions = {}) {\n\tconst latestRunId = id ? currentEvalRunViewState.runIdsByEvalId[id]?.at(-1) : undefined\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: id,\n\t\tactiveRunId: latestRunId,\n\t\tmanuallySelectedRunId: options.manuallySelected ? latestRunId : undefined,\n\t})\n}\n\nexport function setActiveRunId(id: string | undefined, options: ActiveRunSelectionOptions = {}) {\n\tconst record = id ? currentEvalRunViewState.records[id] : undefined\n\tif (id && !record) return\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: record?.evalId ?? currentEvalRunViewState.activeEvalId,\n\t\tactiveRunId: id,\n\t\tmanuallySelectedRunId: options.manuallySelected ? id : undefined,\n\t})\n}\n\nexport function recordAgentEvalUiRun(run: AgentEvalUiRun) {\n\tconst previous = currentEvalRunViewState.records[run.id]\n\tconst runIds = currentEvalRunViewState.runIdsByEvalId[run.evalId] ?? []\n\tconst nextRunIds = runIds.includes(run.id) ? runIds : [...runIds, run.id]\n\tconst shouldActivate = shouldActivateRunLifecycle()\n\tconst record: EvaluationRunRecord = {\n\t\tid: run.id,\n\t\trunInvocationId: run.runInvocationId ?? previous?.runInvocationId,\n\t\tevalId: run.evalId,\n\t\trunNumber: run.runNumber,\n\t\tstatus: run.panelStatus,\n\t\tmodel: run.model,\n\t\treasoningEffort: run.reasoningEffort,\n\t\terror: run.error,\n\t\tharnessRun: run,\n\t\ttree: previous?.tree,\n\t\tagentId: previous?.agentId,\n\t\tscopeId: previous?.scopeId,\n\t\tselectedNodeId: previous?.selectedNodeId,\n\t\trequests: previous?.requests,\n\t\ttranscriptInputMessages: previous?.transcriptInputMessages,\n\t\tstartedAt: previous?.startedAt,\n\t\tfinishedAt: Date.now(),\n\t}\n\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: shouldActivate ? run.evalId : currentEvalRunViewState.activeEvalId,\n\t\tactiveRunId: shouldActivate ? run.id : currentEvalRunViewState.activeRunId,\n\t\tmanuallySelectedRunId: shouldActivate ? undefined : currentEvalRunViewState.manuallySelectedRunId,\n\t\trecords: {\n\t\t\t...currentEvalRunViewState.records,\n\t\t\t[run.id]: record,\n\t\t},\n\t\trunIdsByEvalId: {\n\t\t\t...currentEvalRunViewState.runIdsByEvalId,\n\t\t\t[run.evalId]: nextRunIds,\n\t\t},\n\t})\n\n\treturn record\n}\n\nexport function setLatestAgentEvalJsonReport(report: AgentEvalJsonReport | undefined) {\n\tupdateEvalRunViewState({ latestReport: report })\n}\n\nexport function restoreAgentEvalJsonReport(report: AgentEvalJsonReport) {\n\tconst uiReport = adaptAgentEvalJsonReportToUiReport(report)\n\tconst records: Record<string, EvaluationRunRecord> = {}\n\tconst runIdsByEvalId: Record<string, string[]> = {}\n\tconst finishedAt = Date.now()\n\n\tfor (const run of uiReport.runs) {\n\t\t// Canonical JSON reports intentionally omit live runtime state, so restored rows only carry report data.\n\t\trecords[run.id] = {\n\t\t\tid: run.id,\n\t\t\trunInvocationId: run.runInvocationId,\n\t\t\tevalId: run.evalId,\n\t\t\trunNumber: run.runNumber,\n\t\t\tstatus: run.panelStatus,\n\t\t\tmodel: run.model,\n\t\t\treasoningEffort: run.reasoningEffort,\n\t\t\terror: run.error,\n\t\t\tharnessRun: run,\n\t\t\tfinishedAt,\n\t\t}\n\t\trunIdsByEvalId[run.evalId] = [...(runIdsByEvalId[run.evalId] ?? []), run.id]\n\t}\n\n\tconst firstRun = uiReport.runs[0]\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: firstRun?.evalId,\n\t\tactiveRunId: firstRun?.id,\n\t\tmanuallySelectedRunId: undefined,\n\t\tmountedRunId: undefined,\n\t\tlatestReport: report,\n\t\trecords,\n\t\trunIdsByEvalId,\n\t})\n}\n\ninterface AgentEvalRunIdentity {\n\tevalId: string\n\trunInvocationId?: string\n\tmodel: LanguageModel\n\treasoningEffort?: AgentReasoningEffort\n\trunNumber: number\n}\n\ninterface AgentEvalLiveRunUpdate extends AgentEvalRunIdentity {\n\tagentId: AgentID\n\tscopeId: NodeID\n\trequests: readonly AgentRequest[]\n\ttree?: CanvasTree\n\tselectedNodeId?: NodeID\n\ttranscriptInputMessages: AgentEvalTranscriptInputMessages\n}\n\ninterface AgentEvalPendingRunUpdate extends AgentEvalRunIdentity {\n\tstatus: \"queued\" | \"loading\"\n}\n\ninterface AgentEvalRunProgressUpdate extends AgentEvalRunIdentity {\n\tprogress: string\n}\n\nfunction snapshotAgentRequest(request: AgentRequest): AgentRequest {\n\treturn {\n\t\t...request,\n\t\tparts: [...request.parts],\n\t\timages: [...request.images],\n\t\tcontextMessages: [...request.contextMessages],\n\t\tsteps: request.steps.map(step => ({\n\t\t\t...step,\n\t\t\tcontent: [...step.content],\n\t\t\ttoolResults: [...step.toolResults],\n\t\t\traw: step.raw === undefined ? undefined : [...step.raw],\n\t\t\tmetadata: {\n\t\t\t\t...step.metadata,\n\t\t\t\tcrdtSnapshot: step.metadata.crdtSnapshot === undefined ? undefined : { ...step.metadata.crdtSnapshot },\n\t\t\t},\n\t\t})),\n\t\tchangeset: request.changeset === undefined ? undefined : [...request.changeset],\n\t\tcodeFileChanges: request.codeFileChanges === undefined ? undefined : [...request.codeFileChanges],\n\t\tselection: request.selection === undefined ? undefined : [...request.selection],\n\t\tstate: {\n\t\t\tmessages: request.state.messages.map(message => ({ ...message })),\n\t\t},\n\t}\n}\n\nfunction snapshotAgentRequests(requests: readonly AgentRequest[]): readonly AgentRequest[] {\n\treturn requests.map(snapshotAgentRequest)\n}\n\nexport function recordAgentEvalPendingRun(update: AgentEvalPendingRunUpdate) {\n\tconst runId = createEvaluationRunRecordId(update)\n\tconst previous = currentEvalRunViewState.records[runId]\n\tconst runIds = currentEvalRunViewState.runIdsByEvalId[update.evalId] ?? []\n\tconst nextRunIds = runIds.includes(runId) ? runIds : [...runIds, runId]\n\tconst shouldActivate =\n\t\tupdate.status === \"loading\" ? shouldActivateRunLifecycle() : !currentEvalRunViewState.activeRunId\n\tconst record: EvaluationRunRecord = {\n\t\t...previous,\n\t\tid: runId,\n\t\trunInvocationId: update.runInvocationId ?? previous?.runInvocationId,\n\t\tevalId: update.evalId,\n\t\trunNumber: update.runNumber,\n\t\tstatus: update.status,\n\t\tmodel: update.model,\n\t\treasoningEffort: update.reasoningEffort,\n\t\tprogress: previous?.progress,\n\t\terror: undefined,\n\t\tstartedAt: previous?.startedAt ?? (update.status === \"loading\" ? Date.now() : undefined),\n\t\tfinishedAt: undefined,\n\t}\n\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: shouldActivate ? update.evalId : currentEvalRunViewState.activeEvalId,\n\t\tactiveRunId: shouldActivate ? runId : currentEvalRunViewState.activeRunId,\n\t\tmanuallySelectedRunId: shouldActivate ? undefined : currentEvalRunViewState.manuallySelectedRunId,\n\t\trecords: {\n\t\t\t...currentEvalRunViewState.records,\n\t\t\t[runId]: record,\n\t\t},\n\t\trunIdsByEvalId: {\n\t\t\t...currentEvalRunViewState.runIdsByEvalId,\n\t\t\t[update.evalId]: nextRunIds,\n\t\t},\n\t})\n\n\treturn record\n}\n\nexport function recordAgentEvalLiveRun(update: AgentEvalLiveRunUpdate) {\n\tconst runId = createEvaluationRunRecordId(update)\n\tconst previous = currentEvalRunViewState.records[runId]\n\tconst runIds = currentEvalRunViewState.runIdsByEvalId[update.evalId] ?? []\n\tconst nextRunIds = runIds.includes(runId) ? runIds : [...runIds, runId]\n\tconst shouldActivate = shouldActivateRunLifecycle()\n\tconst record: EvaluationRunRecord = {\n\t\t...previous,\n\t\tid: runId,\n\t\trunInvocationId: update.runInvocationId ?? previous?.runInvocationId,\n\t\tevalId: update.evalId,\n\t\trunNumber: update.runNumber,\n\t\tstatus: \"running\",\n\t\tmodel: update.model,\n\t\treasoningEffort: update.reasoningEffort,\n\t\tprogress: previous?.progress,\n\t\tagentId: update.agentId,\n\t\tscopeId: update.scopeId,\n\t\tselectedNodeId: update.selectedNodeId,\n\t\trequests: snapshotAgentRequests(update.requests),\n\t\ttranscriptInputMessages: new Map(update.transcriptInputMessages),\n\t\ttree: update.tree ?? previous?.tree,\n\t\terror: undefined,\n\t\tstartedAt: previous?.startedAt ?? Date.now(),\n\t\tfinishedAt: undefined,\n\t}\n\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: shouldActivate ? update.evalId : currentEvalRunViewState.activeEvalId,\n\t\tactiveRunId: shouldActivate ? runId : currentEvalRunViewState.activeRunId,\n\t\tmanuallySelectedRunId: shouldActivate ? undefined : currentEvalRunViewState.manuallySelectedRunId,\n\t\trecords: {\n\t\t\t...currentEvalRunViewState.records,\n\t\t\t[runId]: record,\n\t\t},\n\t\trunIdsByEvalId: {\n\t\t\t...currentEvalRunViewState.runIdsByEvalId,\n\t\t\t[update.evalId]: nextRunIds,\n\t\t},\n\t})\n\n\treturn record\n}\n\nexport function recordAgentEvalRunProgress(update: AgentEvalRunProgressUpdate) {\n\tconst runId = createEvaluationRunRecordId(update)\n\tconst previous = currentEvalRunViewState.records[runId]\n\tif (!previous || !isActiveEvaluationRunStatus(previous.status)) return\n\n\tupdateEvaluationRecord(runId, { progress: update.progress }, { activate: false })\n}\n\nexport function markAgentEvalPendingRunStopped(update: AgentEvalRunIdentity) {\n\tconst runId = createEvaluationRunRecordId(update)\n\tconst previous = currentEvalRunViewState.records[runId]\n\tif (!previous || (previous.status !== \"queued\" && previous.status !== \"loading\")) return\n\n\tupdateEvaluationRecord(\n\t\trunId,\n\t\t{\n\t\t\tstatus: \"stopped\",\n\t\t\tprogress: \"Stopped before runtime loaded.\",\n\t\t\tfinishedAt: Date.now(),\n\t\t},\n\t\t{ activate: false },\n\t)\n}\n\nexport function updateEvaluationRunTree(\n\trunId: string,\n\ttree: CanvasTree,\n\tscopeId: NodeID | undefined,\n\tselectedNodeId: NodeID | undefined,\n) {\n\tupdateEvaluationRecord(\n\t\trunId,\n\t\t{\n\t\t\ttree,\n\t\t\tscopeId,\n\t\t\tselectedNodeId,\n\t\t},\n\t\t{ activate: false },\n\t)\n}\n\nexport function markEvaluationRunMounted(runId: string) {\n\tupdateEvaluationRecord(runId, {}, { mounted: true })\n}\n\nexport function resetEvaluationRunViewState() {\n\tcurrentEvalRunViewState = { records: {}, runIdsByEvalId: {} }\n\tfor (const listener of runViewListeners) listener()\n}\n\nfunction updateEvaluationRecord(\n\trunId: string,\n\trecord: Partial<EvaluationRunRecord>,\n\toptions: { activate?: boolean; mounted?: boolean } = {},\n) {\n\tconst previous = currentEvalRunViewState.records[runId]\n\tif (!previous) return\n\tconst shouldActivate = options.activate ?? true\n\n\tupdateEvalRunViewState({\n\t\tactiveEvalId: shouldActivate ? previous.evalId : currentEvalRunViewState.activeEvalId,\n\t\tactiveRunId: shouldActivate ? runId : currentEvalRunViewState.activeRunId,\n\t\tmountedRunId: options.mounted ? runId : currentEvalRunViewState.mountedRunId,\n\t\trecords: {\n\t\t\t...currentEvalRunViewState.records,\n\t\t\t[runId]: {\n\t\t\t\t...previous,\n\t\t\t\t...record,\n\t\t\t\tid: runId,\n\t\t\t},\n\t\t},\n\t})\n}\n\nfunction shouldActivateRunLifecycle(): boolean {\n\tif (currentEvalRunViewState.manuallySelectedRunId) return false\n\treturn (\n\t\t!currentEvalRunViewState.mountedRunId ||\n\t\tcurrentEvalRunViewState.activeRunId === currentEvalRunViewState.mountedRunId\n\t)\n}\n\nfunction createEvaluationRunRecordId(update: AgentEvalRunIdentity): string {\n\treturn createAgentEvalUiRunId(\n\t\tupdate.runInvocationId,\n\t\tupdate.evalId,\n\t\tupdate.model,\n\t\tupdate.reasoningEffort,\n\t\tupdate.runNumber,\n\t)\n}\n\nfunction isActiveEvaluationRunStatus(status: EvaluationRunStatus): boolean {\n\treturn status === \"queued\" || status === \"loading\" || status === \"running\"\n}\n\nfunction updateEvalRunViewState(update: Partial<EvaluationRunViewState>) {\n\tcurrentEvalRunViewState = {\n\t\t...currentEvalRunViewState,\n\t\t...update,\n\t}\n\tfor (const listener of runViewListeners) listener()\n}\n", "import { assert } from \"@framerjs/shared\"\nimport type { AgentLifeCycleHooks } from \"app/ai/agents/Agent.ts\"\nimport type { EvalExportArchiveSnapshot } from \"app/ai/agents/evals/export/AgentStoreEvalExport.ts\"\nimport type { LoadEvalExportOptions } from \"app/ai/agents/evals/export/loadEvalExportDocument.ts\"\nimport { runAgentEvalDefinitionsForBrowser } from \"app/ai/agents/evals2/harness/browserRunner.ts\"\nimport type {\n\tAgentEvalBrowserRunnerResult,\n\tAgentEvalBrowserTranscript,\n} from \"app/ai/agents/evals2/harness/browserRunner.ts\"\nimport type { AgentEvalDefinition } from \"app/ai/agents/evals2/harness/definition.ts\"\nimport { setBrowserEvalRuntimeLoader } from \"app/ai/agents/evals2/harness/fixture.ts\"\nimport { importAgentEvalDefinitions } from \"app/ai/agents/evals2/harness/importEvalDefinitions.ts\"\nimport { defaultAgentEvalModelConfigs, type AgentEvalModelConfig } from \"app/ai/agents/evals2/harness/modelConfig.ts\"\nimport type { AgentEvalRunStartContext, AgentEvalRunUpdate } from \"app/ai/agents/evals2/harness/runner.ts\"\nimport type { AgentEvalUiRun } from \"app/ai/agents/evals2/harness/uiAdapter.ts\"\nimport type { VekterEngine } from \"document/VekterEngine.ts\"\nimport engine from \"document/engine.ts\"\nimport { CanvasTree, type NodeID } from \"document/models/CanvasTree/index.ts\"\nimport {\n\ttype EvalRunOptions,\n\tgetAgentEvalDefinitionsForRunOptions,\n\tgetAgentEvalShardRunSummary,\n\tisAgentEvalRunSelectedForShard,\n\tvalidateEvalRunOptions,\n} from \"./evalDefinitions.ts\"\nimport {\n\tgetCurrentEvalRunViewState,\n\tmarkEvaluationRunMounted,\n\tmarkAgentEvalPendingRunStopped,\n\trecordAgentEvalLiveRun,\n\trecordAgentEvalPendingRun,\n\trecordAgentEvalRunProgress,\n\trecordAgentEvalUiRun,\n\tsetLatestAgentEvalJsonReport,\n\tsetCurrentEvalRunOptions,\n\tupdateEvaluationRunTree,\n} from \"./evalRunState.ts\"\n\nfunction enterEvaluationsMode() {\n\tconst { agentStore, chromeStore } = engine.stores\n\tif (!chromeStore.isEvaluationsModeActive) {\n\t\tengine.cancelTool()\n\t\tchromeStore.reset()\n\t}\n\tagentStore.enterEvaluationsMode()\n}\n\nasync function prepareGlobalEngineForBrowserEvalRun(): Promise<void> {\n\tconst activeAgentId = engine.stores.agentStore.activeEvaluationAgentId\n\tif (activeAgentId) {\n\t\tengine.stores.agentStore.stop(activeAgentId)\n\t\tengine.stores.agentStore.clearActiveEvaluationAgentId(activeAgentId)\n\t}\n\tawait engine.stores.agentStore.clearHistory()\n\tengine.stores.agentStore.detachProjectForEvaluations()\n\tengine.stores.modulesStore.resetModuleStateAndPermissions(\"readwrite-detached\")\n}\n\nasync function loadBrowserEvalRuntimeOnGlobalEngine({\n\tarchiveSnapshot,\n\tloadOptions,\n\tlifecycleHooks,\n}: {\n\tarchiveSnapshot: EvalExportArchiveSnapshot\n\tloadOptions: LoadEvalExportOptions\n\tlifecycleHooks: AgentLifeCycleHooks | undefined\n}) {\n\tawait prepareGlobalEngineForBrowserEvalRun()\n\tconst agent = await engine.stores.agentStore.loadEvalExportArchiveSnapshot(\n\t\tarchiveSnapshot,\n\t\tloadOptions,\n\t\tlifecycleHooks,\n\t)\n\tengine.stores.agentStore.activeEvaluationAgentId = agent.id\n\treturn {\n\t\tengine,\n\t\tagent,\n\t\tdisposeEngine: false,\n\t\tdispose: async () => {\n\t\t\tengine.stores.agentStore.stop(agent.id)\n\t\t\tawait engine.stores.agentStore.clearHistory()\n\t\t\tengine.stores.agentStore.clearActiveEvaluationAgentId(agent.id)\n\t\t},\n\t}\n}\n\ninterface RunEvaluationsSettings {\n\tmodelConfigs?: readonly AgentEvalModelConfig[]\n\trunCount?: number\n\tsignal?: AbortSignal\n}\n\nexport interface AgentEvalHudRunResults extends AgentEvalBrowserRunnerResult {\n\truns: readonly AgentEvalUiRun[]\n\tparallelism: number\n\tindex: number\n\ttranscripts: readonly AgentEvalBrowserTranscript[]\n\tdefinitionCount: number\n\tmodelConfigCount: number\n\trunCount: number\n\ttotalRunCount: number\n\tassignedRunCount: number\n\tevalPattern?: string\n\tmaxSteps?: number\n}\n\ninterface EvaluationTreeMount {\n\ttree: CanvasTree\n\tscopeId: NodeID\n\tselectedNodeId: NodeID\n}\n\nexport async function activateEvaluationRun(runId: string): Promise<boolean> {\n\tconst state = getCurrentEvalRunViewState()\n\tconst record = state.records[runId]\n\tif (!record?.tree || !record.scopeId) return false\n\n\tconst isLiveGlobalEngineRuntime =\n\t\trecord.agentId !== undefined && engine.stores.agentStore.activeEvaluationAgentId === record.agentId\n\tif (isLiveGlobalEngineRuntime) {\n\t\tselectEvaluationScope(record.scopeId, record.selectedNodeId)\n\t\tmarkEvaluationRunMounted(runId)\n\t\treturn true\n\t}\n\n\tif (state.mountedRunId === runId && record.tree === engine.tree) {\n\t\tselectEvaluationScope(record.scopeId, record.selectedNodeId)\n\t\tmarkEvaluationRunMounted(runId)\n\t\treturn true\n\t}\n\n\tpersistMountedEvaluationRunTree()\n\tconst mountedTree = await loadEvaluationTree({\n\t\ttree: record.tree,\n\t\tscopeId: record.scopeId,\n\t\tselectedNodeId: record.selectedNodeId ?? record.scopeId,\n\t})\n\tif (!mountedTree) return false\n\n\tupdateEvaluationRunTree(runId, mountedTree.tree, mountedTree.scopeId, mountedTree.selectedNodeId)\n\tmarkEvaluationRunMounted(runId)\n\n\treturn true\n}\n\nasync function loadEvaluationTree(\n\t{ tree, scopeId, selectedNodeId }: EvaluationTreeMount,\n\tsignal?: AbortSignal,\n): Promise<EvaluationTreeMount | undefined> {\n\tconst treeToLoad = prepareSavedEvaluationTreeForLoad(tree)\n\tawait engine.stores.modulesStore.waitForModulesToSave()\n\tif (signal?.aborted) return\n\tengine.stores.agentStore.detachProjectForEvaluations()\n\tengine.stores.modulesStore.resetModuleStateAndPermissions(\"readwrite-detached\")\n\tengine.stores.treeStore.prepareDetachedRootReplacement(treeToLoad)\n\tengine.load(treeToLoad)\n\tselectEvaluationScope(scopeId, selectedNodeId)\n\treturn { tree: treeToLoad, scopeId, selectedNodeId }\n}\n\nfunction persistMountedEvaluationRunTree() {\n\tconst { mountedRunId, records } = getCurrentEvalRunViewState()\n\tif (!mountedRunId) return\n\tconst record = records[mountedRunId]\n\tif (!record?.tree) return\n\n\tconst tree = getActiveEvaluationTreeSnapshot()\n\tupdateEvaluationRunTree(mountedRunId, tree, engine.stores.scopeStore.active.id, engine.stores.selectionStore.ids[0])\n}\n\nfunction getActiveEvaluationTreeSnapshot(): CanvasTree {\n\tif (engine.stores.treeStore.hasUncommittedChanges()) {\n\t\tengine.doPostProcessing(false)\n\t}\n\treturn createCleanEvaluationTreeSnapshot(engine.tree)\n}\n\nfunction createCleanEvaluationTreeSnapshot(tree: CanvasTree): CanvasTree {\n\ttree.inEditor = true\n\tconst cleanTree = CanvasTree.fromJS(tree.toJS(), engine.componentLoader)\n\tassert(cleanTree, \"Evaluation tree snapshots must be cloneable.\")\n\tprepareCleanEvaluationTreeSnapshot(cleanTree)\n\treturn cleanTree\n}\n\nfunction prepareSavedEvaluationTreeForLoad(tree: CanvasTree): CanvasTree {\n\tprepareCleanEvaluationTreeSnapshot(tree)\n\tif (!tree.isLatest()) {\n\t\ttree.makeLatest()\n\t}\n\tassert(tree.isLatest(), \"Saved evaluation trees must be latest before loading.\")\n\treturn tree\n}\n\nfunction prepareCleanEvaluationTreeSnapshot(tree: CanvasTree) {\n\ttree.inEditor = true\n\tassert(!tree.hasUncommittedChanges(), \"Evaluation tree snapshots must be clean.\")\n\tassert(tree.inEditor, \"Evaluation tree snapshots must be marked as being inEditor.\")\n}\n\nfunction selectEvaluationScope(scopeId: NodeID, selectedNodeId: NodeID | undefined) {\n\tif (!engine.tree.get(scopeId)) return\n\n\tengine.stores.scopeStore.select(scopeId, { keepHistory: false })\n\tif (selectedNodeId && engine.tree.get(selectedNodeId)) {\n\t\tengine.stores.selectionStore.set(selectedNodeId)\n\t}\n}\n\nexport async function runAgentHarnessEvaluations(\n\tdefinitions: readonly AgentEvalDefinition[],\n\toptions: EvalRunOptions,\n\tsettings: RunEvaluationsSettings = {},\n): Promise<AgentEvalHudRunResults> {\n\tenterEvaluationsMode()\n\tsetCurrentEvalRunOptions(options)\n\tsetLatestAgentEvalJsonReport(undefined)\n\tconst resetBrowserRuntimeLoader = setBrowserEvalRuntimeLoader(loadBrowserEvalRuntimeOnGlobalEngine)\n\tconst modelConfigs = getEvaluationModelConfigs(settings)\n\tconst runCount = getEvaluationRunCount(settings)\n\tconst filteredDefinitions = getAgentEvalDefinitionsForRunOptions(definitions, options)\n\tconst shardSummary = getAgentEvalShardRunSummary(definitions, modelConfigs, runCount, options)\n\n\tif (shardSummary.totalRunCount > 0) {\n\t\tassert(\n\t\t\tshardSummary.totalRunCount >= options.parallelism,\n\t\t\t`Provisioned more shards than needed. (${shardSummary.totalRunCount} = ${filteredDefinitions.length} eval(s) \u00D7 ${modelConfigs.length} model(s) \u00D7 ${runCount} run(s), but got ${options.parallelism} shards).`,\n\t\t)\n\t} else {\n\t\t// Let Playwright take over and report the empty runs\n\t}\n\n\tconst result = await runAgentEvalDefinitionsForBrowser(filteredDefinitions, {\n\t\tmodelConfigs,\n\t\truns: runCount,\n\t\tsignal: settings.signal,\n\t\ttranscript: options.transcript,\n\t\tshouldRun: context => isAgentEvalRunSelectedForShard(context, options),\n\t\tonRunQueued: context => {\n\t\t\trecordAgentEvalPendingRun({\n\t\t\t\tevalId: context.definition.id,\n\t\t\t\trunInvocationId: context.runInvocationId,\n\t\t\t\tmodel: context.modelConfig.model,\n\t\t\t\treasoningEffort: context.modelConfig.reasoningEffort,\n\t\t\t\trunNumber: context.runNumber,\n\t\t\t\tstatus: \"queued\",\n\t\t\t})\n\t\t},\n\t\tonRunStart: context => {\n\t\t\trecordAgentEvalStart(context)\n\t\t},\n\t\tonRunProgressMessage: context => {\n\t\t\trecordAgentEvalRunProgress({\n\t\t\t\tevalId: context.definition.id,\n\t\t\t\trunInvocationId: context.runInvocationId,\n\t\t\t\tmodel: context.modelConfig.model,\n\t\t\t\treasoningEffort: context.modelConfig.reasoningEffort,\n\t\t\t\trunNumber: context.runNumber,\n\t\t\t\tprogress: context.message,\n\t\t\t})\n\t\t},\n\t\tonRunStopped: context => {\n\t\t\tmarkAgentEvalPendingRunStopped({\n\t\t\t\tevalId: context.definition.id,\n\t\t\t\trunInvocationId: context.runInvocationId,\n\t\t\t\tmodel: context.modelConfig.model,\n\t\t\t\treasoningEffort: context.modelConfig.reasoningEffort,\n\t\t\t\trunNumber: context.runNumber,\n\t\t\t})\n\t\t},\n\t\tonRun: run => {\n\t\t\trecordAgentEvalUiRun(run)\n\t\t},\n\t\tonRunUpdate: update => {\n\t\t\treturn recordAgentEvalRuntimeUpdate(update)\n\t\t},\n\t}).finally(resetBrowserRuntimeLoader)\n\tsetLatestAgentEvalJsonReport(result.report)\n\n\treturn {\n\t\t...result,\n\t\truns: result.uiReport.runs,\n\t\tparallelism: options.parallelism,\n\t\tindex: options.index,\n\t\tdefinitionCount: filteredDefinitions.length,\n\t\tmodelConfigCount: modelConfigs.length,\n\t\trunCount,\n\t\ttotalRunCount: shardSummary.totalRunCount,\n\t\tassignedRunCount: shardSummary.runCount,\n\t\tevalPattern: options.evalPattern,\n\t\tmaxSteps: options.maxSteps,\n\t}\n}\n\nfunction getEvaluationModelConfigs(settings: RunEvaluationsSettings): readonly AgentEvalModelConfig[] {\n\tif (settings.modelConfigs && settings.modelConfigs.length > 0) return settings.modelConfigs\n\treturn defaultAgentEvalModelConfigs\n}\n\nfunction recordAgentEvalStart(context: AgentEvalRunStartContext): void {\n\trecordAgentEvalPendingRun({\n\t\tevalId: context.definition.id,\n\t\trunInvocationId: context.runInvocationId,\n\t\tmodel: context.modelConfig.model,\n\t\treasoningEffort: context.modelConfig.reasoningEffort,\n\t\trunNumber: context.runNumber,\n\t\tstatus: \"loading\",\n\t})\n}\n\nasync function recordAgentEvalRuntimeUpdate(update: AgentEvalRunUpdate): Promise<void> {\n\tconst runtimeEngine = update.runtime.engine\n\tconst selectedNodeId = runtimeEngine.stores.selectionStore.ids[0]\n\tconst run = recordAgentEvalLiveRun({\n\t\tevalId: update.definition.id,\n\t\trunInvocationId: update.runInvocationId,\n\t\tmodel: update.model,\n\t\treasoningEffort: update.reasoningEffort,\n\t\trunNumber: update.runNumber,\n\t\tagentId: update.runtime.agent.id,\n\t\tscopeId: update.runtime.agent.scopeId,\n\t\tselectedNodeId,\n\t\trequests: update.runtime.agent.chatMessages,\n\t\ttranscriptInputMessages: update.transcriptInputMessages,\n\t\ttree: getEvaluationRuntimeTreeSnapshot(runtimeEngine),\n\t})\n\tif (runtimeEngine === engine) {\n\t\tif (shouldMountLiveAgentEvalRun(run.id)) {\n\t\t\tmarkEvaluationRunMounted(run.id)\n\t\t}\n\t\treturn\n\t}\n\tif (shouldMountLiveAgentEvalRun(run.id)) {\n\t\tawait activateEvaluationRun(run.id)\n\t}\n}\n\nfunction shouldMountLiveAgentEvalRun(runId: string): boolean {\n\tconst state = getCurrentEvalRunViewState()\n\tif (state.manuallySelectedRunId && state.manuallySelectedRunId !== runId) return false\n\treturn state.activeRunId === runId\n}\n\nfunction getEvaluationRuntimeTreeSnapshot(runtimeEngine: VekterEngine): CanvasTree {\n\tif (runtimeEngine.stores.treeStore.hasUncommittedChanges()) {\n\t\truntimeEngine.doPostProcessing(false)\n\t}\n\tconst cleanTree = CanvasTree.fromJS(runtimeEngine.tree.toJS(), runtimeEngine.componentLoader)\n\tassert(cleanTree, \"Evaluation runtime tree snapshots must be cloneable.\")\n\tprepareCleanEvaluationTreeSnapshot(cleanTree)\n\treturn cleanTree\n}\n\nfunction getEvaluationRunCount(settings: RunEvaluationsSettings): number {\n\treturn Math.max(1, Math.floor(settings.runCount ?? 1))\n}\n\nexport async function runAgentHarnessEvaluationsFromGlobal(options: unknown): Promise<AgentEvalHudRunResults> {\n\tconst validatedOptions = validateEvalRunOptions(options)\n\tconst abortController = new AbortController()\n\tengine.stores.agentStore.activeEvaluationRunAbortController = abortController\n\tenterEvaluationsMode()\n\tconst definitions = await importAgentEvalDefinitions()\n\ttry {\n\t\treturn await runAgentHarnessEvaluations(definitions, validatedOptions, {\n\t\t\tmodelConfigs: getModelConfigsForGlobalRunOptions(validatedOptions),\n\t\t\trunCount: validatedOptions.runCount,\n\t\t\tsignal: abortController.signal,\n\t\t})\n\t} finally {\n\t\tengine.stores.agentStore.clearActiveEvaluationRunAbortController(abortController)\n\t}\n}\n\nfunction getModelConfigsForGlobalRunOptions(options: EvalRunOptions): readonly AgentEvalModelConfig[] {\n\tif (options.models && options.models.length > 0) return options.models\n\treturn defaultAgentEvalModelConfigs\n}\n"],
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  "names": ["results", "options", "categories", "importers", "importers", "filterAgentEvalDefinitions"]
}