feat(llmobs): add reasoning token metrics in openai plugin

[XG-xin]

What does this PR do?

Add reasoning tokens metric
MLOB-4745

Motivation

Plugin Checklist

• Unit tests.
• Integration tests.
• Benchmarks.
• TypeScript definitions.
• TypeScript tests.
• API documentation.
• CI jobs/workflows.

Additional Notes

[github-actions]

Overall package size

Self size: 13.46 MB
Deduped: 113.66 MB
No deduping: 128.67 MB

Dependency sizes

| name | version | self size | total size | |------|---------|-----------|------------| | @datadog/libdatadog | 0.7.0 | 35.02 MB | 35.02 MB | | @datadog/native-appsec | 10.3.0 | 20.73 MB | 20.74 MB | | @datadog/pprof | 5.12.0 | 11.19 MB | 11.57 MB | | @datadog/native-iast-taint-tracking | 4.1.0 | 9.01 MB | 9.02 MB | | @opentelemetry/resources | 1.30.1 | 557.67 kB | 7.71 MB | | @opentelemetry/core | 1.30.1 | 908.66 kB | 7.16 MB | | protobufjs | 7.5.4 | 2.95 MB | 5.83 MB | | @datadog/wasm-js-rewriter | 5.0.1 | 2.82 MB | 3.53 MB | | @datadog/native-metrics | 3.1.1 | 1.02 MB | 1.43 MB | | @opentelemetry/api-logs | 0.208.0 | 199.48 kB | 1.42 MB | | @opentelemetry/api | 1.9.0 | 1.22 MB | 1.22 MB | | jsonpath-plus | 10.3.0 | 617.18 kB | 1.08 MB | | import-in-the-middle | 1.15.0 | 127.66 kB | 856.24 kB | | lru-cache | 10.4.3 | 804.3 kB | 804.3 kB | | @datadog/openfeature-node-server | 0.2.0 | 118.51 kB | 437.19 kB | | opentracing | 0.14.7 | 194.81 kB | 194.81 kB | | source-map | 0.7.6 | 185.63 kB | 185.63 kB | | pprof-format | 2.2.1 | 163.06 kB | 163.06 kB | | @datadog/sketches-js | 2.1.1 | 109.9 kB | 109.9 kB | | @isaacs/ttlcache | 2.1.3 | 90.79 kB | 90.79 kB | | lodash.sortby | 4.7.0 | 75.76 kB | 75.76 kB | | ignore | 7.0.5 | 63.38 kB | 63.38 kB | | istanbul-lib-coverage | 3.2.2 | 34.37 kB | 34.37 kB | | rfdc | 1.4.1 | 27.15 kB | 27.15 kB | | dc-polyfill | 0.1.10 | 26.73 kB | 26.73 kB | | tlhunter-sorted-set | 0.1.0 | 24.94 kB | 24.94 kB | | shell-quote | 1.8.3 | 23.74 kB | 23.74 kB | | limiter | 1.1.5 | 23.17 kB | 23.17 kB | | retry | 0.13.1 | 18.85 kB | 18.85 kB | | semifies | 1.0.0 | 15.84 kB | 15.84 kB | | jest-docblock | 29.7.0 | 8.99 kB | 12.76 kB | | crypto-randomuuid | 1.0.0 | 11.18 kB | 11.18 kB | | ttl-set | 1.0.0 | 4.61 kB | 9.69 kB | | mutexify | 1.4.0 | 5.71 kB | 8.74 kB | | path-to-regexp | 0.1.12 | 6.6 kB | 6.6 kB | | module-details-from-path | 1.0.4 | 3.96 kB | 3.96 kB | | escape-string-regexp | 5.0.0 | 3.66 kB | 3.66 kB |

_{🤖 This report was automatically generated by heaviest-objects-in-the-universe}

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 84.95%. Comparing base (0bb1f17) to head (75a21c4).
⚠️ Report is 7 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #7026      +/-   ##
==========================================
+ Coverage   84.94%   84.95%   +0.01%     
==========================================
  Files         514      514              
  Lines       21754    21796      +42     
==========================================
+ Hits        18478    18517      +39     
- Misses       3276     3279       +3     

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[pr-commenter]

Benchmarks

Benchmark execution time: 2025-12-05 20:49:36

Comparing candidate commit e00c7b3 in PR branch xinyuan/openai-add-reasoning-token-metric with baseline commit 0bb1f17 in branch master.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 288 metrics, 32 unstable metrics.

[sabrenner]

nice lgtm! just one question & one code style suggestion. will stamp once we have system tests updated 😎

[sabrenner]

we could probably shorten this to something like

Suggested change

	if (tokenUsage.output_tokens_details) {
	const reasoningOutputTokens = tokenUsage.output_tokens_details.reasoning_tokens
	if (reasoningOutputTokens !== undefined) metrics.reasoningOutputTokens = reasoningOutputTokens
	} else if (tokenUsage.completion_tokens_details) {
	const reasoningOutputTokens = tokenUsage.completion_tokens_details.reasoning_tokens
	if (reasoningOutputTokens !== undefined) {
	metrics.reasoningOutputTokens = reasoningOutputTokens
	}
	}
	const reasoningOutputObject = tokenUsage.output_tokens_details ?? tokenUsage.completion_tokens_details
	const reasoningOutputTokens = reasoningOutputObject?.reasoning_tokens ?? 0
	if (reasoningOutputTokens !== undefined) metrics.reasoningOutputTokens = reasoningOutputTokens

taking either tokenUsage.output_tokens_details or tokenUsage.completion_tokens_details, then getting reasoning_tokens from whichever one exists, defaulting to 0

optional though, def not needed!

[sabrenner]

i think node.js still uses the input model name, so this should be gpt-5-mini, but lmk if you experienced differently!

this is something i'll look to change soon 🙇