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Included review availability: Your plan provides up to 2 included reviews per hour; 1 remains after this review. 📝 WalkthroughWalkthroughThe OpenAI instrumentation now records cached prompt tokens for chat and text-completion spans. The chat test verifies the attribute value using refreshed recording data. ChangesOpenAI cache-read token instrumentation
Priority: ⬇️ Low Estimated code review effort: 2 (Simple) | ~10 minutes Change: Bug fix Merge Risk: ⚪ Minimal · up to This change adds a new span attribute for cached prompt tokens without altering existing usage totals, and the addition is guarded so it has no effect when the underlying data is absent. The behavior is exercised by an updated test using refreshed recording data. No merge-blocking issues were identified. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
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Inline comments:
In `@packages/instrumentation-openai/src/instrumentation.ts`:
- Around line 897-901: Update the cached-token extraction near result.usage to
use the generated OpenAI usage type directly, removing the local structural cast
and accessing prompt_tokens_details?.cached_tokens from result.usage while
preserving the existing optional behavior.
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packages/instrumentation-openai/src/instrumentation.tspackages/instrumentation-openai/test/instrumentation.test.tspackages/instrumentation-openai/test/recordings/Test-OpenAI-instrumentation_1770406427/should-set-attributes-in-span-for-chat_1427850401/recording.har
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Drop the local structural cast; openai@6.32.0 types prompt_tokens_details.cached_tokens on completion usage, so result.usage?.prompt_tokens_details?.cached_tokens typechecks directly.
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Addressed in the latest push: the structural cast is gone, the attribute now reads |
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Description
The chat completions path of
@traceloop/instrumentation-openainever emitsgen_ai.usage.cache_read.input_tokens, even when OpenAI reports cached tokensin
usage.prompt_tokens_details.cached_tokens. The attribute is only emittedby the Responses API path (
_endResponsesSpan), so two calls hitting the sameprompt cache produce inconsistent telemetry depending on the API surface.
The gap is visible in our own test recordings: the HAR for
should set attributes in span for chatalready contains a real response with"prompt_tokens_details":{"cached_tokens":0,...}, but_endSpanreads onlytotal_tokens/completion_tokens/prompt_tokensfromusage.Note this is complementary to #940/#941: once #941 captures the final usage
chunk on streams,
_endSpanstill would not emit the cache breakdown withoutthis change.
Per the OTel GenAI semconv,
gen_ai.usage.cache_read.input_tokensis a subsetof
gen_ai.usage.input_tokensfor OpenAI (cached tokens are already includedin
prompt_tokens), so this only adds the breakdown attribute and does notchange the totals.
Changes
_endSpan(packages/instrumentation-openai/src/instrumentation.ts): whenresult.usageis present, readusage.prompt_tokens_details.cached_tokens(optional chaining; the field isabsent on some SDK versions) and emit
ATTR_GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS.This branch is shared by chat completions and legacy completions, both of
which use the same
CompletionUsageshape.Testing
should set attributes in span for chatso thereal response's
prompt_tokens_details.cached_tokensis5(decoded thegzip+base64 Polly payload, changed the one field, re-encoded).
ATTR_GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS == 5on the span.Verified against commit 1faf69d. I could not
run the suite locally (mocha 11 + Node 20 loads
.tsspecs through the ESMloader in my sandbox, which bypasses the ts-node require hook), so the test is
provided per the existing suite conventions for CI to run.
Repro fixtures: AgentMeasure conformance pack — plain JSONL + expected totals, no runtime install. Found during an open ecosystem audit of usage-accounting tools.
Summary by CodeRabbit
New Features
Tests