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Use inf trace to inspect multi-step LLM workflows captured by Catalyst Tracing. It mirrors the dashboard trace viewer for headless debugging: list trace summaries, open a trace tree, render a timeline, inspect captured conversation messages, discover filter facets, and queue/download trace exports. Alias: inf traces

inf trace upload

Upload a JSONL trace file into the active project. The CLI validates the format locally (OTLP or Langfuse export), uploads it in parts, waits for processing to finish, and prints the upload ID plus line counts. Same flow as the dashboard Upload button and inf dataset upload.

Arguments

Options

Uploaded traces appear under the Traces tab once processing completes. Filter them with all-time range and the upload ID (trace_import_id in filters):

inf trace list

Display trace summaries in the active project.
Alias: inf trace ls

Options

Use --json for the raw API payload with full trace IDs, pagination cursors, and aggregate counts.

Examples

inf trace get

Open a single trace and its spans.
Alias: inf trace show

Arguments

Options

The default summary view prints trace metadata and an ASCII span tree. Use --view raw or global --json when piping trace data into scripts.

Examples

inf trace facets

Inspect available trace filter values and counts. This is useful when building a repeatable query and you do not know the exact model, service, environment, or attribute values in a project.

Options

inf trace facets accepts the same filter flags as inf trace list, plus:

Examples

Advanced filter syntax

--filter, --metadata, and --resource are repeatable. Quote expressions so your shell does not interpret operators.

inf trace export

Trace exports create downloadable JSONL files for offline analysis, support escalations, or long-running review workflows.

inf trace export create

Queue an export job.

inf trace export list

inf trace export status

inf trace export download