Dimension to group usage by (one of: "model", "customer_id", "event_type", "provider")
Start of the date range (ISO 8601 format) (ISO 8601 format, e.g., "2024-01-01T00:00:00Z")
End of the date range (ISO 8601 format) (ISO 8601 format, e.g., "2024-01-01T00:00:00Z")
OptionalcustomerId: stringFilter usage by customer ID before grouping
OptionaleventType: stringFilter usage by event type before grouping
Optionalmodel: stringFilter usage by model name before grouping
Usage breakdown
Get usage summary
Retrieve aggregated usage metrics for the project.
Returns totals for events, tokens, and costs within the specified date range. You can filter by customer, event type, or model to get specific subsets of data.
Metrics Included:*
Start of the date range (ISO 8601 format) (ISO 8601 format, e.g., "2024-01-01T00:00:00Z")
End of the date range (ISO 8601 format) (ISO 8601 format, e.g., "2024-01-01T00:00:00Z")
OptionalcustomerId: stringFilter usage by customer ID
OptionaleventType: stringFilter usage by event type (e.g., "model_call", "embedding")
Optionalmodel: stringFilter usage by model name (e.g., "gpt-4", "claude-3")
Usage summary
Get usage timeseries
Retrieve usage metrics bucketed by time interval.
Returns time-series data showing how usage changes over time. Useful for creating charts, identifying trends, and monitoring usage patterns.
Intervals:*
hour: Bucket data by hourday: Bucket data by dayweek: Bucket data by weekEach data point includes the timestamp and all usage metrics for that time period.
Time interval for bucketing data (one of: "hour", "day", "week")
Start of the date range (ISO 8601 format) (ISO 8601 format, e.g., "2024-01-01T00:00:00Z")
End of the date range (ISO 8601 format) (ISO 8601 format, e.g., "2024-01-01T00:00:00Z")
OptionalcustomerId: stringFilter usage by customer ID
OptionaleventType: stringFilter usage by event type
Optionalmodel: stringFilter usage by model name
Usage timeseries
Get usage breakdown
Retrieve usage metrics grouped by a specific dimension.
This endpoint provides detailed breakdowns of usage data, allowing you to see how usage is distributed across different dimensions like models, customers, event types, or providers.
Use Cases:*