feat(appkit): mlflow tracing for agents (stack 1/5) - #477
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📦 Bundle size reportCompared against
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| dist | raw | gzip |
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| JS (runtime) | 861 KB (+6.1 KB) | 300 KB (+2.3 KB) |
| Type declarations | 314 KB | 109 KB (+9 B) |
| Source maps | 1.7 MB (+11 KB) | 561 KB (+3.9 KB) |
| Other | 11 KB | 3.7 KB |
| Total | 2.8 MB (+17 KB) | 974 KB (+6.3 KB) |
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87 KB | 2.5 KB | 90 KB | external | 285 KB |
./beta |
48 KB (+771 B) | 459 B | 49 KB (+771 B) | external | 142 KB (+2.0 KB) |
./type-generator |
20 KB | 0 B | 20 KB | external | 57 KB |
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lazy | 2.5 KB |
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beta.js |
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stream-manager.js |
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wide-event-emitter.js |
initial | 3.2 KB |
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databricks.js |
initial | 3.0 KB |
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configuration.js |
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service-context.js |
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client.js |
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databricks.js |
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index.js |
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@databricks/appkit-ui
npm tarball (packed): 309 KB — gzipped download (dist + bin; excludes release-only docs/NOTICE).
| dist | raw | gzip |
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| JS (runtime) | 362 KB | 121 KB |
| Type declarations | 209 KB | 76 KB |
| Source maps | 693 KB | 227 KB |
| CSS | 16 KB | 3.3 KB |
| Total | 1.3 MB | 427 KB |
Per-entry composition (consumer bundle — deps bundled, peerDeps external)
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4.3 KB | 49 KB | 54 KB | 208 KB | 12 KB |
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./react |
429 KB | 49 KB | 478 KB | 1.3 MB | 168 KB |
./react/beta |
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./js/beta |
beta.js |
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./react |
index.js |
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tslib |
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apache-arrow |
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Trace agent turns and tool calls to MLflow via the mlflow-tracing SDK. Adds an optional 'experiment' resource to the agents plugin; when bound (MLFLOW_EXPERIMENT_ID), each turn opens an AGENT span and each tool call a nested TOOL span, with auth resolved from the app's Databricks credentials. A turn's trace can be linked to an evaluation run via mlflow.sourceRun. Signed-off-by: MarioCadenas <[email protected]>
Signed-off-by: MarioCadenas <[email protected]>
Signed-off-by: MarioCadenas <[email protected]>
Signed-off-by: MarioCadenas <[email protected]>
currentTraceId() used getLastActiveTraceId(), which is only set when a root span ends (on export). Read mid-turn it returned the previous turn's id — or another turn's under concurrency. Read the context-active span instead, matching linkTraceToRun. Also read mlflowRunId from the validated schema (capped at 64 chars) instead of casting raw req.body, and drop two unused imports. Adds tracing tests covering trace-id source and output auto-capture. Signed-off-by: MarioCadenas <[email protected]>
/invocations and /responses drove tool calls through traceTool but had no traceAgent wrapper, so with tracing enabled each tool call became an orphan root TOOL trace instead of nesting under a turn. Wrap the adapter run in traceAgent, mirroring the streaming path, so both surfaces produce the same trace shape. Also drop a dead flushTraces mock left from the flushAgentTraces removal. Signed-off-by: MarioCadenas <[email protected]>
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🤖 AppKit PR bot🔬 Run evalsStart an eval for this PR from the evals-monitor app: Go to Evals Monitor → 📦 Try this PR's app templateScaffolds a new app from this PR's SDK build. Run it in any folder (requires the GitHub CLI — gh run download 31019968101 -R databricks/appkit -n appkit-template-0.55.0-pr.002c2ae-pr-agent-evals-1-tracing-477 -D appkit-pr-477 \
&& unzip -o "appkit-pr-477/appkit-template-0.55.0-pr.002c2ae-pr-agent-evals-1-tracing-477.zip" -d "appkit-pr-477" \
&& databricks apps init --template "appkit-pr-477"The template pins |
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Stack 1/5 · targets
main.Adds MLflow tracing to the agents plugin. Agent turns and tool calls are traced to a bound MLflow experiment via the
mlflow-tracingSDK (OpenTelemetry under the hood). Tracing is a no-op unless the plugin's optionalexperimentresource is set (MLFLOW_EXPERIMENT_ID); auth is resolved from the app's own Databricks credentials, so no tokens or OTLP headers are wired by hand.withAgentSpanwraps each turn (AGENT span) and tool dispatch (TOOL span, auto-nested).mlflow.traceNametag.experimentoptional resource in the agents manifest.This is the base of a 5-PR stack that builds out an agent evaluation framework. Reviewable on its own — touches only the agents plugin.