@mastra/core
Version:
Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.
865 lines (862 loc) • 43.8 kB
JavaScript
import { z } from 'zod/v4';
// ../_internal-core/dist/index.js
var EntityType = /* @__PURE__ */ ((EntityType2) => {
EntityType2["AGENT"] = "agent";
EntityType2["SCORER"] = "scorer";
EntityType2["RAG_INGESTION"] = "rag_ingestion";
EntityType2["TRAJECTORY"] = "trajectory";
EntityType2["INPUT_PROCESSOR"] = "input_processor";
EntityType2["INPUT_STEP_PROCESSOR"] = "input_step_processor";
EntityType2["OUTPUT_PROCESSOR"] = "output_processor";
EntityType2["OUTPUT_STEP_PROCESSOR"] = "output_step_processor";
EntityType2["WORKFLOW_STEP"] = "workflow_step";
EntityType2["TOOL"] = "tool";
EntityType2["WORKFLOW_RUN"] = "workflow_run";
EntityType2["MEMORY"] = "memory";
return EntityType2;
})(EntityType || {});
var createdAtField = z.date().describe("Database record creation time");
var updatedAtField = z.date().describe("Database record last update time");
var dbTimestamps = {
createdAt: createdAtField,
updatedAt: updatedAtField.nullable()
};
var paginationArgsSchema = z.object({
page: z.coerce.number().int().min(0).optional().default(0).describe("Zero-indexed page number"),
perPage: z.coerce.number().int().min(1).max(100).optional().default(10).describe("Number of items per page")
}).describe("Pagination options for list queries");
var paginationInfoSchema = z.object({
total: z.number().describe("Total number of items available"),
page: z.number().describe("Current page"),
perPage: z.union([z.number(), z.literal(false)]).describe("Number of items per page, or false if pagination is disabled"),
hasMore: z.boolean().describe("True if more pages are available")
});
var deltaCursorSchema = z.string().min(1).describe("Opaque cursor value for incremental polling");
var listModeSchema = z.enum(["page", "delta"]).describe("List mode: 'page' | 'delta', defaults to 'page' when omitted.");
var deltaLimitSchema = z.coerce.number().int().min(1).max(100).optional().describe("Maximum number of updates to return in one delta poll");
var defaultPaginationArgs = {
page: 0,
perPage: 10
};
var defaultDeltaLimit = 10;
function refineObservabilityListMode(value, ctx) {
if (value.mode === "delta") {
if (value.pagination !== void 0) {
ctx.addIssue({ code: "custom", path: ["pagination"], message: "pagination is not allowed in delta mode" });
}
if (value.orderBy !== void 0) {
ctx.addIssue({ code: "custom", path: ["orderBy"], message: "orderBy is not allowed in delta mode" });
}
return;
}
if (value.after !== void 0) {
ctx.addIssue({ code: "custom", path: ["after"], message: "after is only allowed in delta mode" });
}
if (value.limit !== void 0) {
ctx.addIssue({ code: "custom", path: ["limit"], message: "limit is only allowed in delta mode" });
}
}
function normalizeObservabilityListArgs(value, defaults) {
return {
mode: value.mode === "delta" ? "delta" : "page",
filters: value.filters,
pagination: value.pagination ?? defaults.pagination ?? defaultPaginationArgs,
orderBy: value.orderBy ?? defaults.orderBy,
after: value.after,
limit: value.limit ?? defaults.limit ?? defaultDeltaLimit
};
}
var deltaInfoSchema = z.object({
limit: z.number().describe("Maximum number of updates requested for this delta poll"),
hasMore: z.boolean().describe("True when more matching updates remain after this response")
}).describe("Incremental polling metadata");
var dateRangeSchema = z.object({
start: z.coerce.date().optional().describe("Start of date range (inclusive by default)"),
end: z.coerce.date().optional().describe("End of date range (inclusive by default)"),
startExclusive: z.boolean().optional().describe("When true, excludes the start date from results (uses > instead of >=)"),
endExclusive: z.boolean().optional().describe("When true, excludes the end date from results (uses < instead of <=)")
}).describe("Date range filter for timestamps");
var sortDirectionSchema = z.enum(["ASC", "DESC"]).describe("Sort direction: 'ASC' | 'DESC'");
var aggregationTypeSchema = z.enum(["sum", "avg", "min", "max", "count", "count_distinct", "last"]).describe("Aggregation function");
var aggregationIntervalSchema = z.enum(["1m", "5m", "15m", "1h", "1d"]).describe("Time bucket interval");
var comparePeriodSchema = z.enum(["previous_period", "previous_day", "previous_week"]).describe("Comparison period for aggregate queries");
var groupBySchema = z.array(z.string()).min(1).describe("Fields to group by");
var percentilesSchema = z.array(z.number().min(0).max(1)).min(1).describe("Percentile values (0-1)");
var aggregateResponseFields = {
value: z.number().nullable().describe("Aggregated value"),
previousValue: z.number().nullable().optional().describe("Value from comparison period"),
changePercent: z.number().nullable().optional().describe("Percentage change from comparison period")
};
var dimensionsField = z.record(z.string(), z.string().nullable()).describe("Dimension values for this group");
var aggregatedValueField = z.number().describe("Aggregated value");
var bucketTimestampField = z.date().describe("Bucket timestamp");
var percentileField = z.number().describe("Percentile value");
var percentileBucketValueField = z.number().describe("Percentile value at this bucket");
var entityTypeField = z.nativeEnum(EntityType).describe(`Entity type (e.g., 'agent' | 'processor' | 'tool' | 'workflow')`);
var entityIdField = z.string().describe('ID of the entity (e.g., "weatherAgent", "orderWorkflow")');
var entityNameField = z.string().describe("Name of the entity");
var userIdField = z.string().describe("Human end-user who triggered execution");
var organizationIdField = z.string().describe("Multi-tenant organization/account");
var resourceIdField = z.string().describe("Broader resource context (Mastra memory compatibility)");
var runIdField = z.string().describe("Unique execution run identifier");
var sessionIdField = z.string().describe("Session identifier for grouping traces");
var threadIdField = z.string().describe("Conversation thread identifier");
var requestIdField = z.string().describe("HTTP request ID for log correlation");
var environmentField = z.string().describe(`Environment (e.g., "production" | "staging" | "development")`);
var sourceField = z.string().describe(`Source of execution (e.g., "local" | "cloud" | "ci")`);
var executionSourceField = z.string().describe(`Source of execution (e.g., "local" | "cloud" | "ci")`);
var serviceNameField = z.string().describe("Name of the service");
var parentEntityTypeField = z.nativeEnum(EntityType).describe("Entity type of the parent entity");
var parentEntityIdField = z.string().describe("ID of the parent entity");
var parentEntityNameField = z.string().describe("Name of the parent entity");
var rootEntityTypeField = z.nativeEnum(EntityType).describe("Entity type of the root entity");
var rootEntityIdField = z.string().describe("ID of the root entity");
var rootEntityNameField = z.string().describe("Name of the root entity");
var entityVersionIdField = z.string().describe("Version ID of the entity that produced this signal (e.g., agent version, workflow version)");
var parentEntityVersionIdField = z.string().describe("Version ID of the parent entity that produced this signal");
var rootEntityVersionIdField = z.string().describe("Version ID of the root entity that produced this signal");
var experimentIdField = z.string().describe("Experiment or eval run identifier");
var scopeField = z.record(z.string(), z.unknown()).describe('Arbitrary package/app version info (e.g., {"core": "1.0.0", "memory": "1.0.0", "gitSha": "abcd1234"})');
var metadataField = z.record(z.string(), z.unknown()).describe("User-defined metadata for custom filtering");
var tagsField = z.array(z.string()).describe("Labels for filtering");
var contextFieldsBase = {
// Entity identification
entityType: entityTypeField.nullish(),
entityId: entityIdField.nullish(),
entityName: entityNameField.nullish(),
// Parent entity hierarchy
parentEntityType: parentEntityTypeField.nullish(),
parentEntityId: parentEntityIdField.nullish(),
parentEntityName: parentEntityNameField.nullish(),
// Root entity hierarchy
rootEntityType: rootEntityTypeField.nullish(),
rootEntityId: rootEntityIdField.nullish(),
rootEntityName: rootEntityNameField.nullish(),
// Identity & tenancy
userId: userIdField.nullish(),
organizationId: organizationIdField.nullish(),
resourceId: resourceIdField.nullish(),
// Correlation IDs
runId: runIdField.nullish(),
sessionId: sessionIdField.nullish(),
threadId: threadIdField.nullish(),
requestId: requestIdField.nullish(),
// Deployment context
environment: environmentField.nullish(),
serviceName: serviceNameField.nullish(),
scope: scopeField.nullish(),
// Entity versioning
entityVersionId: entityVersionIdField.nullish(),
parentEntityVersionId: parentEntityVersionIdField.nullish(),
rootEntityVersionId: rootEntityVersionIdField.nullish(),
// Experimentation
experimentId: experimentIdField.nullish()
};
var contextFields = {
...contextFieldsBase,
executionSource: executionSourceField.nullish(),
tags: tagsField.nullish()
};
var spanContextFields = {
...contextFieldsBase,
source: sourceField.nullish()
};
var commonFilterFields = {
timestamp: dateRangeSchema.optional().describe("Filter by timestamp range"),
traceId: z.string().optional().describe("Filter by trace ID"),
spanId: z.string().optional().describe("Filter by span ID"),
entityType: entityTypeField.optional(),
entityName: entityNameField.optional(),
entityVersionId: entityVersionIdField.optional(),
parentEntityVersionId: parentEntityVersionIdField.optional(),
rootEntityVersionId: rootEntityVersionIdField.optional(),
userId: userIdField.optional(),
organizationId: organizationIdField.optional(),
experimentId: experimentIdField.optional(),
serviceName: serviceNameField.optional(),
environment: environmentField.optional(),
parentEntityType: parentEntityTypeField.optional(),
parentEntityName: parentEntityNameField.optional(),
rootEntityType: rootEntityTypeField.optional(),
rootEntityName: rootEntityNameField.optional(),
resourceId: resourceIdField.optional(),
runId: runIdField.optional(),
sessionId: sessionIdField.optional(),
threadId: threadIdField.optional(),
requestId: requestIdField.optional(),
executionSource: executionSourceField.optional(),
tags: z.array(z.string()).optional().describe("Filter by tags (must have all specified tags)")
};
var traceIdField = z.string().describe("Unique trace identifier");
var spanIdField = z.string().describe("Unique span identifier within a trace");
var logLevelSchema = z.enum(["debug", "info", "warn", "error", "fatal"]);
var messageField = z.string().describe("Log message");
var logDataField = z.record(z.string(), z.unknown()).describe("Structured data attached to the log");
var logRecordSchema = z.object({
logId: z.string().nullish().describe("Unique id for this log event"),
timestamp: z.date().describe("When the log was created"),
level: logLevelSchema.describe("Log severity level"),
message: messageField,
data: logDataField.nullish(),
// Correlation
traceId: traceIdField.nullish(),
spanId: spanIdField.nullish(),
// Context fields
...contextFields,
/**
* @deprecated Use `executionSource` instead.
*/
source: z.string().nullish().describe("Execution source"),
metadata: metadataField.nullish()
}).describe("Log record as stored in the database");
var logRecordInputSchema = z.object({
level: logLevelSchema,
message: messageField,
data: logDataField.optional(),
tags: tagsField.optional()
}).describe("User-provided log input");
var createLogRecordSchema = logRecordSchema;
var batchCreateLogsArgsSchema = z.object({
logs: z.array(createLogRecordSchema)
}).describe("Arguments for batch creating logs");
var logsFilterSchema = z.object({
...commonFilterFields,
// Log-specific filters
/**
* @deprecated Use `executionSource` instead.
*/
source: z.string().optional().describe("Filter by execution source"),
level: z.union([logLevelSchema, z.array(logLevelSchema)]).optional().describe("Filter by log level(s)")
}).describe("Filters for querying logs");
var logsOrderByFieldSchema = z.enum(["timestamp"]).describe("Field to order by: 'timestamp'");
var logsOrderBySchema = z.object({
field: logsOrderByFieldSchema.default("timestamp").describe("Field to order by"),
direction: sortDirectionSchema.default("DESC").describe("Sort direction")
}).describe("Order by configuration");
var listLogsArgsSchema = z.object({
mode: listModeSchema.optional(),
filters: logsFilterSchema.optional().describe("Optional filters to apply"),
pagination: paginationArgsSchema.optional(),
orderBy: logsOrderBySchema.optional(),
after: deltaCursorSchema.optional(),
limit: deltaLimitSchema
}).strict().superRefine(refineObservabilityListMode).transform(
(value) => normalizeObservabilityListArgs(value, {
orderBy: { field: "timestamp", direction: "DESC" }
})
).describe("Arguments for listing logs");
var listLogsResponseSchema = z.object({
pagination: paginationInfoSchema.optional(),
delta: deltaInfoSchema.optional(),
deltaCursor: deltaCursorSchema.optional(),
logs: z.array(logRecordSchema)
}).describe("Response from listing logs");
var scorerIdField = z.string().describe("Identifier of the scorer (e.g., relevance, accuracy)");
var scorerNameField = z.string().describe("Display name of the scorer");
var scorerVersionField = z.string().describe("Version of the scorer");
var scoreSourceField = z.string().describe("How the score was produced (e.g., manual, automated, experiment)");
var scoreValueField = z.number().describe("Score value (range defined by scorer)");
var scoreReasonField = z.string().describe("Explanation for the score");
var scoreRecordSchema = z.object({
scoreId: z.string().nullish().describe("Unique id for this score event"),
timestamp: z.date().describe("When the score was recorded"),
// Target
traceId: traceIdField.nullish().describe("Trace that anchors the scored target when available"),
spanId: spanIdField.nullish().describe("Span ID this score applies to"),
// Score data
scorerId: scorerIdField,
scorerName: scorerNameField.nullish(),
scorerVersion: scorerVersionField.nullish(),
scoreSource: scoreSourceField.nullish(),
/**
* @deprecated Use `scoreSource` instead.
*/
source: scoreSourceField.nullish(),
score: scoreValueField,
reason: scoreReasonField.nullish(),
// Context (entity hierarchy, identity, correlation, deployment, experimentation)
...contextFields,
/** Trace ID of the scoring run (links to trace that generated this score) */
scoreTraceId: z.string().nullish().describe("Trace ID of the scoring run for debugging score generation"),
// User-defined metadata (context fields stored here)
metadata: z.record(z.string(), z.unknown()).nullish().describe("User-defined metadata")
}).describe("Score record as stored in the database");
var scoreInputSchema = z.object({
scorerId: scorerIdField,
scorerName: scorerNameField.optional(),
scorerVersion: scorerVersionField.optional(),
scoreSource: scoreSourceField.optional(),
/**
* @deprecated Use `scoreSource` instead.
*/
source: scoreSourceField.optional(),
score: scoreValueField,
reason: scoreReasonField.optional(),
metadata: z.record(z.string(), z.unknown()).optional().describe("Additional scorer-specific metadata"),
experimentId: experimentIdField.optional(),
scoreTraceId: z.string().optional().describe("Trace ID of the scoring run for debugging score generation"),
targetEntityType: entityTypeField.optional().describe("Entity type the scorer evaluated when known")
}).describe("User-provided score input");
var createScoreRecordSchema = scoreRecordSchema;
var createScoreArgsSchema = z.object({
score: createScoreRecordSchema
}).describe("Arguments for creating a score");
var createScoreBodySchema = z.object({
score: createScoreRecordSchema.omit({ timestamp: true })
}).describe("Arguments for creating a score");
var createScoreResponseSchema = z.object({ success: z.boolean() }).describe("Response from creating a score");
var batchCreateScoresArgsSchema = z.object({
scores: z.array(createScoreRecordSchema)
}).describe("Arguments for batch recording scores");
var scoresFilterSchema = z.object({
...commonFilterFields,
// Score-specific filters
scorerId: z.union([z.string(), z.array(z.string())]).optional().describe("Filter by scorer ID(s)"),
scoreSource: scoreSourceField.optional().describe("Filter by how the score was produced"),
/**
* @deprecated Use `scoreSource` instead.
*/
source: scoreSourceField.optional().describe("Filter by how the score was produced")
}).describe("Filters for querying scores");
var scoresOrderByFieldSchema = z.enum(["timestamp", "score"]).describe("Field to order by: 'timestamp' | 'score'");
var scoresOrderBySchema = z.object({
field: scoresOrderByFieldSchema.default("timestamp").describe("Field to order by"),
direction: sortDirectionSchema.default("DESC").describe("Sort direction")
}).describe("Order by configuration");
var listScoresArgsSchema = z.object({
mode: listModeSchema.optional(),
filters: scoresFilterSchema.optional(),
pagination: paginationArgsSchema.optional(),
orderBy: scoresOrderBySchema.optional(),
after: deltaCursorSchema.optional(),
limit: deltaLimitSchema
}).strict().superRefine(refineObservabilityListMode).transform(
(value) => normalizeObservabilityListArgs(value, {
orderBy: { field: "timestamp", direction: "DESC" }
})
).describe("Arguments for listing scores");
var listScoresResponseSchema = z.object({
pagination: paginationInfoSchema.optional(),
delta: deltaInfoSchema.optional(),
deltaCursor: deltaCursorSchema.optional(),
scores: z.array(scoreRecordSchema)
}).describe("Response from listing scores");
var getScoreAggregateArgsSchema = z.object({
scorerId: scorerIdField,
scoreSource: scoreSourceField.optional(),
aggregation: aggregationTypeSchema,
filters: scoresFilterSchema.optional(),
comparePeriod: comparePeriodSchema.optional()
}).describe("Arguments for getting a score aggregate");
var getScoreAggregateResponseSchema = z.object(aggregateResponseFields);
var getScoreBreakdownArgsSchema = z.object({
scorerId: scorerIdField,
scoreSource: scoreSourceField.optional(),
groupBy: groupBySchema,
aggregation: aggregationTypeSchema,
filters: scoresFilterSchema.optional()
}).describe("Arguments for getting a score breakdown");
var getScoreBreakdownResponseSchema = z.object({
groups: z.array(
z.object({
dimensions: dimensionsField,
value: aggregatedValueField
})
)
});
var getScoreTimeSeriesArgsSchema = z.object({
scorerId: scorerIdField,
scoreSource: scoreSourceField.optional(),
interval: aggregationIntervalSchema,
aggregation: aggregationTypeSchema,
filters: scoresFilterSchema.optional(),
groupBy: groupBySchema.optional()
}).describe("Arguments for getting score time series");
var getScoreTimeSeriesResponseSchema = z.object({
series: z.array(
z.object({
name: z.string().describe("Series name (scorer ID or group key)"),
points: z.array(
z.object({
timestamp: bucketTimestampField,
value: aggregatedValueField
})
)
})
)
});
var getScorePercentilesArgsSchema = z.object({
scorerId: scorerIdField,
scoreSource: scoreSourceField.optional(),
percentiles: percentilesSchema,
interval: aggregationIntervalSchema,
filters: scoresFilterSchema.optional()
}).describe("Arguments for getting score percentiles");
var getScorePercentilesResponseSchema = z.object({
series: z.array(
z.object({
percentile: percentileField,
points: z.array(
z.object({
timestamp: bucketTimestampField,
value: percentileBucketValueField
})
)
})
)
});
var feedbackSourceField = z.string().describe("Source of feedback (e.g., 'user', 'system', 'manual')");
var feedbackTypeField = z.string().describe("Type of feedback (e.g., 'thumbs', 'rating', 'correction')");
var feedbackValueField = z.union([z.number(), z.string()]).describe("Feedback value (rating number or correction text)");
var feedbackCommentField = z.string().describe("Additional comment or context");
var feedbackUserIdField = z.string().describe("User who provided the feedback");
function normalizeLegacyFeedbackActor(input) {
if (!input || typeof input !== "object" || Array.isArray(input)) {
return input;
}
const record = { ...input };
if (typeof record.userId === "string" && record.feedbackUserId == null) {
record.feedbackUserId = record.userId;
delete record.userId;
}
return record;
}
var feedbackRecordObjectSchema = z.object({
feedbackId: z.string().nullish().describe("Unique id for this feedback event"),
timestamp: z.date().describe("When the feedback was recorded"),
// Target
traceId: traceIdField.nullish().describe("Trace that anchors the feedback target when available"),
spanId: spanIdField.nullish().describe("Span ID this feedback applies to"),
// Feedback data
feedbackSource: feedbackSourceField.nullish(),
/**
* @deprecated Use `feedbackSource` instead.
*/
source: feedbackSourceField.nullish(),
feedbackType: feedbackTypeField,
value: feedbackValueField,
comment: feedbackCommentField.nullish(),
// Feedback actor identity
feedbackUserId: feedbackUserIdField.nullish(),
// Context (entity hierarchy, identity, correlation, deployment, experimentation)
...contextFields,
// Source linkage (e.g. dataset item result ID)
sourceId: z.string().nullish().describe("ID of the source record this feedback is linked to (e.g. experiment result ID)"),
// User-defined metadata (context fields stored here)
metadata: z.record(z.string(), z.unknown()).nullish().describe("User-defined metadata")
});
var feedbackRecordSchema = z.object(feedbackRecordObjectSchema.shape).describe("Feedback record as stored in the database");
var feedbackInputObjectSchema = z.object({
feedbackSource: feedbackSourceField.optional(),
/**
* @deprecated Use `feedbackSource` instead.
*/
source: feedbackSourceField.optional(),
feedbackType: feedbackTypeField,
value: feedbackValueField,
comment: feedbackCommentField.optional(),
feedbackUserId: feedbackUserIdField.optional(),
/**
* @deprecated Use `feedbackUserId` instead.
*/
userId: feedbackUserIdField.optional(),
metadata: z.record(z.string(), z.unknown()).optional().describe("Additional feedback-specific metadata"),
experimentId: experimentIdField.optional(),
sourceId: z.string().optional().describe("ID of the source record this feedback is linked to")
});
var feedbackInputSchema = z.object(feedbackInputObjectSchema.shape).describe("User-provided feedback input");
var createFeedbackRecordSchema = feedbackRecordSchema;
var createFeedbackArgsSchema = z.object({
feedback: z.preprocess(normalizeLegacyFeedbackActor, feedbackRecordObjectSchema)
}).describe("Arguments for creating feedback");
var createFeedbackBodySchema = z.object({
feedback: feedbackRecordObjectSchema.omit({ timestamp: true })
}).describe("Arguments for creating feedback");
var createFeedbackResponseSchema = z.object({ success: z.boolean() }).describe("Response from creating feedback");
var batchCreateFeedbackArgsSchema = z.object({
feedbacks: z.array(z.preprocess(normalizeLegacyFeedbackActor, feedbackRecordObjectSchema))
}).describe("Arguments for batch recording feedback");
var feedbackFilterObjectSchema = z.object({
...commonFilterFields,
// Feedback-specific filters
feedbackType: z.union([z.string(), z.array(z.string())]).optional().describe("Filter by feedback type(s)"),
feedbackSource: feedbackSourceField.optional(),
/**
* @deprecated Use `feedbackSource` instead.
*/
source: feedbackSourceField.optional(),
feedbackUserId: feedbackUserIdField.optional()
});
var feedbackFilterSchema = z.object(feedbackFilterObjectSchema.shape).describe("Filters for querying feedback");
var feedbackOrderByFieldSchema = z.enum(["timestamp"]).describe("Field to order by: 'timestamp'");
var feedbackOrderBySchema = z.object({
field: feedbackOrderByFieldSchema.default("timestamp").describe("Field to order by"),
direction: sortDirectionSchema.default("DESC").describe("Sort direction")
}).describe("Order by configuration");
var listFeedbackArgsSchema = z.object({
mode: listModeSchema.optional(),
filters: z.preprocess(normalizeLegacyFeedbackActor, feedbackFilterObjectSchema).optional(),
pagination: paginationArgsSchema.optional(),
orderBy: feedbackOrderBySchema.optional(),
after: deltaCursorSchema.optional(),
limit: deltaLimitSchema
}).strict().superRefine(refineObservabilityListMode).transform(
(value) => normalizeObservabilityListArgs(value, {
orderBy: { field: "timestamp", direction: "DESC" }
})
).describe("Arguments for listing feedback");
var listFeedbackResponseSchema = z.object({
pagination: paginationInfoSchema.optional(),
delta: deltaInfoSchema.optional(),
deltaCursor: deltaCursorSchema.optional(),
feedback: z.array(feedbackRecordSchema)
}).describe("Response from listing feedback");
var getFeedbackAggregateArgsSchema = z.object({
feedbackType: feedbackTypeField,
feedbackSource: feedbackSourceField.optional(),
aggregation: aggregationTypeSchema,
filters: feedbackFilterSchema.optional(),
comparePeriod: comparePeriodSchema.optional()
}).describe("Arguments for getting a feedback aggregate over numeric values");
var getFeedbackAggregateResponseSchema = z.object(aggregateResponseFields);
var getFeedbackBreakdownArgsSchema = z.object({
feedbackType: feedbackTypeField,
feedbackSource: feedbackSourceField.optional(),
groupBy: groupBySchema,
aggregation: aggregationTypeSchema,
filters: feedbackFilterSchema.optional()
}).describe("Arguments for getting a feedback breakdown over numeric values");
var getFeedbackBreakdownResponseSchema = z.object({
groups: z.array(
z.object({
dimensions: dimensionsField,
value: aggregatedValueField
})
)
});
var getFeedbackTimeSeriesArgsSchema = z.object({
feedbackType: feedbackTypeField,
feedbackSource: feedbackSourceField.optional(),
interval: aggregationIntervalSchema,
aggregation: aggregationTypeSchema,
filters: feedbackFilterSchema.optional(),
groupBy: groupBySchema.optional()
}).describe("Arguments for getting feedback time series over numeric values");
var getFeedbackTimeSeriesResponseSchema = z.object({
series: z.array(
z.object({
name: z.string().describe("Series name (feedback type or group key)"),
points: z.array(
z.object({
timestamp: bucketTimestampField,
value: aggregatedValueField
})
)
})
)
});
var getFeedbackPercentilesArgsSchema = z.object({
feedbackType: feedbackTypeField,
feedbackSource: feedbackSourceField.optional(),
percentiles: percentilesSchema,
interval: aggregationIntervalSchema,
filters: feedbackFilterSchema.optional()
}).describe("Arguments for getting feedback percentiles over numeric values");
var getFeedbackPercentilesResponseSchema = z.object({
series: z.array(
z.object({
percentile: percentileField,
points: z.array(
z.object({
timestamp: bucketTimestampField,
value: percentileBucketValueField
})
)
})
)
});
var metricTypeSchema = z.enum(["counter", "gauge", "histogram"]);
var metricNameField = z.string().describe("Metric name (e.g., mastra_agent_duration_ms)");
var metricValueField = z.number().describe("Metric value");
var labelsField = z.record(z.string(), z.string()).describe("Metric labels for dimensional filtering");
var providerField = z.string().describe("Model provider");
var modelField = z.string().describe("Model");
var estimatedCostField = z.number().describe("Estimated cost");
var costUnitField = z.string().describe("Unit for the estimated cost (e.g., usd)");
var costMetadField = z.record(z.string(), z.unknown()).nullish().describe("Structured costing metadata");
var metricRecordSchema = z.object({
metricId: z.string().nullish().describe("Unique id for this metric event"),
timestamp: z.date().describe("When the metric was recorded"),
name: metricNameField,
value: metricValueField,
// Correlation
traceId: traceIdField.nullish(),
spanId: spanIdField.nullish(),
// Context (entity hierarchy, identity, correlation, deployment, experimentation)
...contextFields,
/**
* @deprecated Use `executionSource` instead.
*/
source: z.string().nullish().describe("Execution source"),
// Canonical costing fields
provider: providerField.nullish(),
model: modelField.nullish(),
// Estimated cost related fields
estimatedCost: estimatedCostField.nullish(),
costUnit: costUnitField.nullish(),
costMetadata: costMetadField.nullish(),
// User-defined labels used for filtering
labels: labelsField.default({}),
// User-defined metadata
metadata: metadataField.nullish()
}).describe("Metric record as stored in the database");
var metricInputSchema = z.object({
name: metricNameField,
value: metricValueField,
labels: labelsField.optional()
}).describe("User-provided metric input");
var createMetricRecordSchema = metricRecordSchema;
var batchCreateMetricsArgsSchema = z.object({
metrics: z.array(createMetricRecordSchema)
}).describe("Arguments for batch recording metrics");
var metricsAggregationSchema = z.object({
type: aggregationTypeSchema,
interval: aggregationIntervalSchema.optional(),
groupBy: groupBySchema.optional()
}).describe("Metrics aggregation configuration");
var metricsFilterSchema = z.object({
...commonFilterFields,
// Metric identification
name: z.array(z.string()).nonempty().optional().describe("Filter by metric name(s)"),
/**
* @deprecated Use `executionSource` instead.
*/
source: z.string().optional().describe("Filter by execution source"),
// Canonical costing filters
provider: providerField.optional(),
model: modelField.optional(),
costUnit: costUnitField.optional(),
// Label filters (exact match on label values)
labels: z.record(z.string(), z.string()).optional().describe("Exact match on label key-value pairs")
}).describe("Filters for querying metrics");
var metricsOrderByFieldSchema = z.enum(["timestamp"]).describe("Field to order by: 'timestamp'");
var metricsOrderBySchema = z.object({
field: metricsOrderByFieldSchema.default("timestamp").describe("Field to order by"),
direction: sortDirectionSchema.default("DESC").describe("Sort direction")
}).describe("Order by configuration");
var listMetricsArgsSchema = z.object({
mode: listModeSchema.optional(),
filters: metricsFilterSchema.optional(),
pagination: paginationArgsSchema.optional(),
orderBy: metricsOrderBySchema.optional(),
after: deltaCursorSchema.optional(),
limit: deltaLimitSchema
}).strict().superRefine(refineObservabilityListMode).transform(
(value) => normalizeObservabilityListArgs(value, {
orderBy: { field: "timestamp", direction: "DESC" }
})
).describe("Arguments for listing metrics");
var listMetricsResponseSchema = z.object({
pagination: paginationInfoSchema.optional(),
delta: deltaInfoSchema.optional(),
deltaCursor: deltaCursorSchema.optional(),
metrics: z.array(metricRecordSchema)
}).describe("Response from listing metrics");
var METRIC_DISTINCT_COLUMNS = [
"entityType",
"entityName",
"parentEntityType",
"parentEntityName",
"rootEntityType",
"rootEntityName",
"name",
"provider",
"model",
"environment",
"executionSource",
"serviceName",
"threadId",
"resourceId"
];
var distinctColumnSchema = z.enum(METRIC_DISTINCT_COLUMNS).optional().describe(
"Column to apply count_distinct over (required when aggregation is 'count_distinct'). Restricted to allowlisted metric dimensions."
);
var requireDistinctColumnRefinement = {
check: (data) => data.aggregation !== "count_distinct" || data.distinctColumn !== void 0,
options: {
message: "distinctColumn is required when aggregation is 'count_distinct'",
path: ["distinctColumn"]
}
};
var getMetricAggregateArgsSchema = z.object({
name: z.array(z.string()).nonempty().describe("Metric name(s) to aggregate"),
aggregation: aggregationTypeSchema,
distinctColumn: distinctColumnSchema,
filters: metricsFilterSchema.optional(),
comparePeriod: comparePeriodSchema.optional()
}).refine(requireDistinctColumnRefinement.check, requireDistinctColumnRefinement.options).describe("Arguments for getting a metric aggregate");
var getMetricAggregateResponseSchema = z.object({
...aggregateResponseFields,
estimatedCost: z.number().nullable().optional().describe("Aggregated estimated cost from the same filtered row set"),
costUnit: z.string().nullable().optional().describe("Shared cost unit for the aggregated rows, or null when mixed/unknown"),
previousEstimatedCost: z.number().nullable().optional().describe("Aggregated estimated cost from the comparison period"),
costChangePercent: z.number().nullable().optional().describe("Percentage change in estimated cost from comparison period")
});
var getMetricBreakdownArgsSchema = z.object({
name: z.array(z.string()).nonempty().describe("Metric name(s) to break down"),
groupBy: groupBySchema,
aggregation: aggregationTypeSchema,
distinctColumn: distinctColumnSchema,
filters: metricsFilterSchema.optional(),
limit: z.number().int().positive().max(1e3).optional().describe("Maximum number of groups to return (server-side TopK). Required for high-cardinality groupBy."),
orderDirection: sortDirectionSchema.optional().describe(
"Sort direction for the aggregated value (defaults to 'DESC' at the storage layer; pairs with limit for top/bottom-N)."
)
}).refine(requireDistinctColumnRefinement.check, requireDistinctColumnRefinement.options).describe("Arguments for getting a metric breakdown");
var getMetricBreakdownResponseSchema = z.object({
groups: z.array(
z.object({
dimensions: dimensionsField,
value: aggregatedValueField,
estimatedCost: z.number().nullable().optional().describe("Summed estimated cost for this group"),
costUnit: z.string().nullable().optional().describe("Shared cost unit for this group, or null when mixed/unknown")
})
)
});
var getMetricTimeSeriesArgsSchema = z.object({
name: z.array(z.string()).nonempty().describe("Metric name(s)"),
interval: aggregationIntervalSchema,
aggregation: aggregationTypeSchema,
distinctColumn: distinctColumnSchema,
filters: metricsFilterSchema.optional(),
groupBy: groupBySchema.optional()
}).refine(requireDistinctColumnRefinement.check, requireDistinctColumnRefinement.options).describe("Arguments for getting metric time series");
var getMetricTimeSeriesResponseSchema = z.object({
series: z.array(
z.object({
name: z.string().describe("Series name (metric name or group key)"),
costUnit: z.string().nullable().optional().describe("Shared cost unit for this series, or null when mixed/unknown"),
points: z.array(
z.object({
timestamp: bucketTimestampField,
value: aggregatedValueField,
estimatedCost: z.number().nullable().optional().describe("Summed estimated cost in this bucket")
})
)
})
)
});
var getMetricPercentilesArgsSchema = z.object({
name: z.string().describe("Metric name"),
percentiles: percentilesSchema,
interval: aggregationIntervalSchema,
filters: metricsFilterSchema.optional()
}).describe("Arguments for getting metric percentiles");
var getMetricPercentilesResponseSchema = z.object({
series: z.array(
z.object({
percentile: percentileField,
points: z.array(
z.object({
timestamp: bucketTimestampField,
value: percentileBucketValueField
})
)
})
)
});
var getMetricNamesArgsSchema = z.object({
prefix: z.string().optional().describe("Filter metric names by prefix"),
limit: z.coerce.number().int().min(1).optional().describe("Maximum number of names to return")
}).describe("Arguments for getting metric names");
var getMetricNamesResponseSchema = z.object({
names: z.array(z.string()).describe("Distinct metric names")
});
var getMetricLabelKeysArgsSchema = z.object({
metricName: z.string().describe("Metric name to get label keys for")
}).describe("Arguments for getting metric label keys");
var getMetricLabelKeysResponseSchema = z.object({
keys: z.array(z.string()).describe("Distinct label keys for the metric")
});
var getMetricLabelValuesArgsSchema = z.object({
metricName: z.string().describe("Metric name"),
labelKey: z.string().describe("Label key to get values for"),
prefix: z.string().optional().describe("Filter values by prefix"),
limit: z.coerce.number().int().min(1).optional().describe("Maximum number of values to return")
}).describe("Arguments for getting label values");
var getMetricLabelValuesResponseSchema = z.object({
values: z.array(z.string()).describe("Distinct label values")
});
var getEntityTypesArgsSchema = z.object({}).describe("Arguments for getting entity types");
var getEntityTypesResponseSchema = z.object({
entityTypes: z.array(entityTypeField).describe("Distinct entity types")
});
var getEntityNamesArgsSchema = z.object({
entityType: entityTypeField.optional().describe("Optional entity type filter")
}).describe("Arguments for getting entity names");
var getEntityNamesResponseSchema = z.object({
names: z.array(z.string()).describe("Distinct entity names")
});
var getServiceNamesArgsSchema = z.object({}).describe("Arguments for getting service names");
var getServiceNamesResponseSchema = z.object({
serviceNames: z.array(z.string()).describe("Distinct service names")
});
var getEnvironmentsArgsSchema = z.object({}).describe("Arguments for getting environments");
var getEnvironmentsResponseSchema = z.object({
environments: z.array(z.string()).describe("Distinct environments")
});
var getTagsArgsSchema = z.object({
entityType: entityTypeField.optional().describe("Optional entity type filter")
}).describe("Arguments for getting tags");
var getTagsResponseSchema = z.object({
tags: z.array(z.string()).describe("Distinct tags")
});
// src/observability/types/tracing.ts
var SpanType = /* @__PURE__ */ ((SpanType2) => {
SpanType2["AGENT_RUN"] = "agent_run";
SpanType2["SCORER_RUN"] = "scorer_run";
SpanType2["SCORER_STEP"] = "scorer_step";
SpanType2["GENERIC"] = "generic";
SpanType2["MODEL_GENERATION"] = "model_generation";
SpanType2["MODEL_STEP"] = "model_step";
SpanType2["MODEL_INFERENCE"] = "model_inference";
SpanType2["MODEL_CHUNK"] = "model_chunk";
SpanType2["MCP_TOOL_CALL"] = "mcp_tool_call";
SpanType2["PROCESSOR_RUN"] = "processor_run";
SpanType2["TOOL_CALL"] = "tool_call";
SpanType2["WORKFLOW_RUN"] = "workflow_run";
SpanType2["WORKFLOW_STEP"] = "workflow_step";
SpanType2["WORKFLOW_CONDITIONAL"] = "workflow_conditional";
SpanType2["WORKFLOW_CONDITIONAL_EVAL"] = "workflow_conditional_eval";
SpanType2["WORKFLOW_PARALLEL"] = "workflow_parallel";
SpanType2["WORKFLOW_LOOP"] = "workflow_loop";
SpanType2["WORKFLOW_SLEEP"] = "workflow_sleep";
SpanType2["WORKFLOW_WAIT_EVENT"] = "workflow_wait_event";
SpanType2["MEMORY_OPERATION"] = "memory_operation";
SpanType2["WORKSPACE_ACTION"] = "workspace_action";
SpanType2["RAG_INGESTION"] = "rag_ingestion";
SpanType2["RAG_EMBEDDING"] = "rag_embedding";
SpanType2["RAG_VECTOR_OPERATION"] = "rag_vector_operation";
SpanType2["RAG_ACTION"] = "rag_action";
SpanType2["GRAPH_ACTION"] = "graph_action";
SpanType2["MAPPING"] = "mapping";
return SpanType2;
})(SpanType || {});
var InternalSpans = /* @__PURE__ */ ((InternalSpans2) => {
InternalSpans2[InternalSpans2["NONE"] = 0] = "NONE";
InternalSpans2[InternalSpans2["WORKFLOW"] = 1] = "WORKFLOW";
InternalSpans2[InternalSpans2["AGENT"] = 2] = "AGENT";
InternalSpans2[InternalSpans2["TOOL"] = 4] = "TOOL";
InternalSpans2[InternalSpans2["MODEL"] = 8] = "MODEL";
InternalSpans2[InternalSpans2["ALL"] = 15] = "ALL";
return InternalSpans2;
})(InternalSpans || {});
var TracingEventType = /* @__PURE__ */ ((TracingEventType2) => {
TracingEventType2["SPAN_STARTED"] = "span_started";
TracingEventType2["SPAN_UPDATED"] = "span_updated";
TracingEventType2["SPAN_ENDED"] = "span_ended";
return TracingEventType2;
})(TracingEventType || {});
export { EntityType, InternalSpans, METRIC_DISTINCT_COLUMNS, SpanType, TracingEventType, aggregationIntervalSchema, aggregationTypeSchema, batchCreateFeedbackArgsSchema, batchCreateLogsArgsSchema, batchCreateMetricsArgsSchema, batchCreateScoresArgsSchema, commonFilterFields, comparePeriodSchema, contextFields, createFeedbackArgsSchema, createFeedbackBodySchema, createFeedbackRecordSchema, createFeedbackResponseSchema, createLogRecordSchema, createMetricRecordSchema, createScoreArgsSchema, createScoreBodySchema, createScoreRecordSchema, createScoreResponseSchema, createdAtField, dateRangeSchema, dbTimestamps, defaultDeltaLimit, defaultPaginationArgs, deltaCursorSchema, deltaInfoSchema, deltaLimitSchema, distinctColumnSchema, entityIdField, entityNameField, entityTypeField, environmentField, executionSourceField, experimentIdField, feedbackFilterSchema, feedbackInputSchema, feedbackOrderByFieldSchema, feedbackOrderBySchema, feedbackRecordSchema, getEntityNamesArgsSchema, getEntityNamesResponseSchema, getEntityTypesArgsSchema, getEntityTypesResponseSchema, getEnvironmentsArgsSchema, getEnvironmentsResponseSchema, getFeedbackAggregateArgsSchema, getFeedbackAggregateResponseSchema, getFeedbackBreakdownArgsSchema, getFeedbackBreakdownResponseSchema, getFeedbackPercentilesArgsSchema, getFeedbackPercentilesResponseSchema, getFeedbackTimeSeriesArgsSchema, getFeedbackTimeSeriesResponseSchema, getMetricAggregateArgsSchema, getMetricAggregateResponseSchema, getMetricBreakdownArgsSchema, getMetricBreakdownResponseSchema, getMetricLabelKeysArgsSchema, getMetricLabelKeysResponseSchema, getMetricLabelValuesArgsSchema, getMetricLabelValuesResponseSchema, getMetricNamesArgsSchema, getMetricNamesResponseSchema, getMetricPercentilesArgsSchema, getMetricPercentilesResponseSchema, getMetricTimeSeriesArgsSchema, getMetricTimeSeriesResponseSchema, getScoreAggregateArgsSchema, getScoreAggregateResponseSchema, getScoreBreakdownArgsSchema, getScoreBreakdownResponseSchema, getScorePercentilesArgsSchema, getScorePercentilesResponseSchema, getScoreTimeSeriesArgsSchema, getScoreTimeSeriesResponseSchema, getServiceNamesArgsSchema, getServiceNamesResponseSchema, getTagsArgsSchema, getTagsResponseSchema, listFeedbackArgsSchema, listFeedbackResponseSchema, listLogsArgsSchema, listLogsResponseSchema, listMetricsArgsSchema, listMetricsResponseSchema, listModeSchema, listScoresArgsSchema, listScoresResponseSchema, logLevelSchema, logRecordInputSchema, logRecordSchema, logsFilterSchema, logsOrderByFieldSchema, logsOrderBySchema, metadataField, metricInputSchema, metricRecordSchema, metricTypeSchema, metricsAggregationSchema, metricsFilterSchema, metricsOrderByFieldSchema, metricsOrderBySchema, normalizeObservabilityListArgs, organizationIdField, paginationArgsSchema, paginationInfoSchema, parentEntityIdField, parentEntityNameField, parentEntityTypeField, refineObservabilityListMode, requestIdField, resourceIdField, rootEntityIdField, rootEntityNameField, rootEntityTypeField, runIdField, scopeField, scoreInputSchema, scoreRecordSchema, scoresFilterSchema, scoresOrderByFieldSchema, scoresOrderBySchema, serviceNameField, sessionIdField, sortDirectionSchema, sourceField, spanContextFields, spanIdField, tagsField, threadIdField, traceIdField, updatedAtField, userIdField };
//# sourceMappingURL=chunk-QAXRURAT.js.map
//# sourceMappingURL=chunk-QAXRURAT.js.map