| name | adapt-server-config |
| description | Convert InferenceX DB config/benchmark pairs, Dynamo recipe YAML, or confirmed custom serving configs into validated aiconfigurator estimate requests. Use when adapting server configuration, checking whether a recipe can be estimated, generating canonical request JSON, or explicitly running estimates from adapted requests. |
Adapt Server Config
Create versioned AIC estimate requests without silently dropping operating points. Keep adaptation separate from estimate execution.
Choose the workflow
- InferenceX DB record plus benchmark row: use the helper with
--format inferencex.
- DynamoGraphDeployment with optional
perf.yaml, or a concrete dynamo-ci SGLang benchmark recipe: use the helper with --format dynamo.
- Existing canonical request: use the helper with
--format request to validate it.
- Any other format: follow custom-mapping.md. Do not pass it to a known-format adapter.
Adapt a known format
Run from the aiconfigurator repository root:
uv run python .agents/skills/adapt-server-config/scripts/adapt_config.py \
--format inferencex --config configs-record.json --benchmark benchmark-row.json \
--overrides '{"backend_version":"0.19.0"}'
uv run python .agents/skills/adapt-server-config/scripts/adapt_config.py \
--format dynamo --deploy deploy.yaml --perf perf.yaml \
--overrides '{"system_name":"h200_sxm"}'
The helper prints an ordered adaptation report. Preserve every outcome, including rejected points and warnings. Treat any rejection as unresolved; do not repair it with guesses.
For benchmark cookbooks or Slurm command templates, require a rendered concrete recipe or DynamoGraphDeployment. For Helm inputs, require a rendered DynamoGraphDeployment; the matching unrendered benchmark-values.yaml can supply literal toolPipeline workload points through --perf. Do not evaluate templates or infer runtime parameters.
The helper validates adapted requests against both the Python model and packaged JSON Schema. Use --output PATH to save the report.
Handle unknown formats
Read custom-mapping.md. Inspect the source, then show the user:
- Explicit source fields.
- Inferred canonical fields and the evidence for each inference.
- Missing fields and assumptions.
- Every discovered operating point in source order.
Obtain confirmation before creating canonical request JSON. After confirmation, create aic-estimate-request/1.0.0 JSON and validate it:
uv run python .agents/skills/adapt-server-config/scripts/adapt_config.py \
--format request --request request.json
Do not add heuristic behavior to the SDK. Do not infer missing model identity, system, workload, concurrency, or speculative-token acceptance without confirmation.
Run estimates only on explicit request
Adaptation never runs an estimate. Add --run-estimate only when the user explicitly asks to execute estimates:
uv run python .agents/skills/adapt-server-config/scripts/adapt_config.py \
--format dynamo --deploy deploy.yaml --perf perf.yaml \
--overrides '{"system_name":"h200_sxm"}' --run-estimate
Never execute recipe shell commands. The SDK only parses literal configuration values.
