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Capture Codex LLM usage metadata variants #3

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82 changes: 82 additions & 0 deletions plugins/trace-codex/src/agents/codex/event-processor.test.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -1168,6 +1168,88 @@ describe("CodexEventProcessor: llm spans", () => {
);
});

test("llm token metrics normalize alternate and nested usage shapes", async () => {
await assertProducesTrace(
[
sessionStart(),
sessionMeta({ cwd: "/work" }),
turnContext({ model: "gpt-5.5" }),
taskStarted({ turn_id: "t1" }),
userMessage({ message: "yo!" }),
assistantMessage("Hey."),
tokenCount({
prompt_tokens: 100,
completion_tokens: 14,
prompt_tokens_details: { cached_tokens: 25, cache_creation_tokens: 7 },
completion_tokens_details: { reasoning_tokens: 4 },
cost: 0.1234,
}),
taskComplete({ turn_id: "t1", last_agent_message: "Hey." }),
stop({ turn_id: "t1" }),
],
{
span_attributes: { name: "codex: work", type: "task" },
ended: true,
children: [
{
span_attributes: { name: "turn: t1", type: "task" },
ended: true,
children: [
{
span_attributes: { name: "gpt-5.5", type: "llm" },
output: { role: "assistant", content: "Hey." },
metrics: {
prompt_tokens: 100,
completion_tokens: 14,
tokens: 114,
prompt_cached_tokens: 25,
prompt_cache_creation_tokens: 7,
completion_reasoning_tokens: 4,
cost: 0.1234,
estimated_cost: 0.1234,
},
ended: true,
},
],
},
],
},
);
});

test("a dangling llm span records why token usage is unavailable", async () => {
await assertProducesTrace(
[
sessionStart(),
sessionMeta({ cwd: "/work" }),
turnContext({ model: "gpt-5.5" }),
taskStarted({ turn_id: "t1" }),
userMessage({ message: "yo!" }),
assistantMessage("Hey."),
taskComplete({ turn_id: "t1", last_agent_message: "Hey." }),
stop({ turn_id: "t1" }),
],
{
span_attributes: { name: "codex: work", type: "task" },
ended: true,
children: [
{
span_attributes: { name: "turn: t1", type: "task" },
ended: true,
children: [
{
span_attributes: { name: "gpt-5.5", type: "llm" },
output: { role: "assistant", content: "Hey." },
metadata: { usage_unavailable_reason: "codex_transcript_missing_token_count" },
ended: true,
},
],
},
],
},
);
});

// A reasoning item with a readable summary is surfaced as a `reasoning` entry
// in the llm output (Braintrust's OpenAI Responses shape), interleaved before
// the assistant message.
Expand Down
56 changes: 53 additions & 3 deletions plugins/trace-codex/src/agents/codex/event-processor.ts
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Expand Up @@ -276,17 +276,53 @@ function tokenMetrics(usage: Record<string, unknown>): Record<string, number> {
const metrics: Record<string, number> = {};
const num = (v: unknown): number | undefined =>
typeof v === "number" && Number.isFinite(v) ? v : undefined;
const at = (path: string): number | undefined => {
let cur: unknown = usage;
for (const part of path.split(".")) {
if (cur === null || typeof cur !== "object") return undefined;
cur = (cur as Record<string, unknown>)[part];
}
return num(cur);
};
const map: Array<[string, string]> = [
["input_tokens", "prompt_tokens"],
["prompt_tokens", "prompt_tokens"],
["output_tokens", "completion_tokens"],
["completion_tokens", "completion_tokens"],
["total_tokens", "tokens"],
["tokens", "tokens"],
["cached_input_tokens", "prompt_cached_tokens"],
["prompt_cached_tokens", "prompt_cached_tokens"],
["input_tokens_details.cached_tokens", "prompt_cached_tokens"],
["prompt_tokens_details.cached_tokens", "prompt_cached_tokens"],
["prompt_cache_creation_tokens", "prompt_cache_creation_tokens"],
["input_tokens_details.cache_creation_tokens", "prompt_cache_creation_tokens"],
["input_tokens_details.cache_write_tokens", "prompt_cache_creation_tokens"],
["prompt_tokens_details.cache_creation_tokens", "prompt_cache_creation_tokens"],
["prompt_tokens_details.cache_write_tokens", "prompt_cache_creation_tokens"],
["reasoning_output_tokens", "completion_reasoning_tokens"],
["completion_reasoning_tokens", "completion_reasoning_tokens"],
["reasoning_tokens", "completion_reasoning_tokens"],
["output_tokens_details.reasoning_tokens", "completion_reasoning_tokens"],
["completion_tokens_details.reasoning_tokens", "completion_reasoning_tokens"],
["cost", "cost"],
["cost", "estimated_cost"],
["estimated_cost", "estimated_cost"],
["total_cost", "estimated_cost"],
["cost_usd", "estimated_cost"],
];
for (const [from, to] of map) {
const v = num(usage[from]);
if (metrics[to] !== undefined) continue;
const v = at(from);
if (v !== undefined) metrics[to] = v;
}
if (
metrics.tokens === undefined &&
metrics.prompt_tokens !== undefined &&
metrics.completion_tokens !== undefined
) {
metrics.tokens = metrics.prompt_tokens + metrics.completion_tokens;
}
return metrics;
}

Expand Down Expand Up @@ -1467,6 +1503,15 @@ export class CodexEventProcessor implements EventProcessor {
const info = (payload.info ?? {}) as Record<string, unknown>;
const usage = (info.last_token_usage ?? {}) as Record<string, unknown>;
const metrics = tokenMetrics(usage);
const metadata =
Object.keys(metrics).length === 0
? {
usage_unavailable_reason:
Object.keys(usage).length === 0
? "codex_token_count_missing_usage"
: "codex_token_count_unrecognized_usage",
}
: undefined;
const { span, turnId, output, outputPreset, lastOutputTime } = scope.openLlm;
// End the span when the model last generated (its last output item), NOT at
// this token_count: Codex writes the token_count after the tool result (at
Expand All @@ -1476,7 +1521,11 @@ export class CodexEventProcessor implements EventProcessor {
// Fall back to the token_count time if we somehow have no output time.
const endTime = lastOutputTime ?? isoToUnixSeconds(record.timestamp);
try {
span.log(outputPreset ? { metrics } : { output: llmOutput(output), metrics });
span.log(
outputPreset
? { metrics, ...(metadata !== undefined ? { metadata } : {}) }
: { output: llmOutput(output), metrics, ...(metadata !== undefined ? { metadata } : {}) },
);
span.end(endTime !== undefined ? { endTime } : undefined);
// This LLM call is a child of its turn; advance the turn's boundary so the
// next child (LLM or tool) starts where this one ended (its last output).
Expand All @@ -1501,7 +1550,8 @@ export class CodexEventProcessor implements EventProcessor {
const { span, turnId, output, lastOutputTime } = scope.openLlm;
const effectiveEnd = lastOutputTime ?? endTime;
try {
if (output.length > 0) span.log({ output: llmOutput(output) });
const metadata = { usage_unavailable_reason: "codex_transcript_missing_token_count" };
span.log(output.length > 0 ? { output: llmOutput(output), metadata } : { metadata });
span.end(effectiveEnd !== undefined ? { endTime: effectiveEnd } : undefined);
this.noteChildEnded(scope, turnId, effectiveEnd);
} catch (err) {
Expand Down
2 changes: 1 addition & 1 deletion plugins/trace-codex/src/agents/codex/test-helpers.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -228,7 +228,7 @@ export function reasoning(summary: string[] = []): TranscriptEntry {
* token_count event: closes the current llm span. `usage` maps the Codex token
* keys (input_tokens, output_tokens, total_tokens, ...) onto last_token_usage.
*/
export function tokenCount(usage: Record<string, number> = {}): TranscriptEntry {
export function tokenCount(usage: Record<string, unknown> = {}): TranscriptEntry {
return transcript({
type: "event_msg",
payload: { type: "token_count", info: { last_token_usage: usage } },
Expand Down
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