refactor: Share GuideLLM dashboard postprocessing - #162
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📝 WalkthroughWalkthroughGuideLLM dashboard helpers now parse artifacts, enrich metrics, generate KPIs, and export CSV data. The llm-d plugin uses these helpers and recovers deployment metadata. RHAIIS delegates to the shared implementation. KPI labels and orchestration settings were updated. ChangesDashboard KPI integration
Estimated code review effort: 4 (Complex) | ~60 minutes Sequence Diagram(s)sequenceDiagram
participant GuideLLMParser
participant LlmDGuideLLMPlugin
participant dashboard_helpers
participant dashboard_csv
GuideLLMParser->>LlmDGuideLLMPlugin: parse benchmark and deployment artifacts
LlmDGuideLLMPlugin->>dashboard_helpers: enrich records and compute KPIs
dashboard_helpers-->>LlmDGuideLLMPlugin: return dashboard KPI records
LlmDGuideLLMPlugin->>dashboard_csv: export dashboard-compatible rows
dashboard_csv-->>LlmDGuideLLMPlugin: write dashboard.csv
Possibly related PRs
Suggested labels: 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
🧪 Generate unit tests (beta)
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Actionable comments posted: 8
🧹 Nitpick comments (5)
projects/guidellm/postprocess/guidellm/parsing/parsers.py (3)
132-140: 📐 Maintainability & Code Quality | 🔵 Trivial | 💤 Low valueUpdate the docstring for the new return fields.
Line 139 states that the function returns
product_version,deployment_profile, andmodel_name. The function now also returnsreplicas,tensor_parallel_size,router_config,image_tag, andruntime_args. Line 133 and line 136 also state "YAML" only, although the function now accepts a.jsonartifact.♻️ Proposed update
""" - Extract multiple fields from LLMInferenceService YAML file. + Extract multiple fields from an LLMInferenceService YAML or JSON file. Args: - file_path: Path to llminferenceservice.yaml file + file_path: Path to the llminferenceservice.yaml, .yml, or .json file Returns: - Dictionary with extracted fields (product_version, deployment_profile, model_name) + Dictionary with extracted fields: product_version, deployment_profile, + model_name, replicas, tensor_parallel_size, router_config, image_tag, + and runtime_args. Absent fields are omitted. """🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@projects/guidellm/postprocess/guidellm/parsing/parsers.py` around lines 132 - 140, Update the docstring for the relevant YAML/JSON parsing function to describe both YAML and JSON artifact inputs, and expand the Returns section to include replicas, tensor_parallel_size, router_config, image_tag, and runtime_args alongside the existing fields.
580-583: 📐 Maintainability & Code Quality | 🔵 Trivial | 💤 Low valueAdd a deterministic tiebreaker to the sort.
The sort places capture-state paths first, which matches the first-file-wins merge at lines 618-622. Python's sort is stable, so files inside each group keep the order of
node.artifact_paths. If that list comes from a directory scan, the order can vary between runs, and the extracted metadata can then vary too.Add the path as a secondary key.
♻️ Proposed change
- llmisvc_files.sort(key=lambda path: "__capture_llmisvc_state" not in str(path)) + llmisvc_files.sort( + key=lambda path: ("__capture_llmisvc_state" not in str(path), str(path)) + )🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@projects/guidellm/postprocess/guidellm/parsing/parsers.py` around lines 580 - 583, Update the llmisvc_files sorting in the parser to retain capture-state paths first while using each path itself as a deterministic secondary sort key. Ensure the resulting order no longer depends on the original node.artifact_paths traversal order before the first-file-wins merge.
118-124: 🗄️ Data Integrity & Integration | 🔵 Trivial | ⚡ Quick winParse
llminferenceservice.jsonwithjson.load, notyaml.safe_load.
llminferenceservice.jsonis produced byoc get llminferenceservice -ojson, and a Kubernetes JSON output can use literal strings such asyes/noin annotation values. YAML 1.1 interprets those literals as booleans, so the.jsonartifact can change the extractedproduct_version/deployment_profile; updateextract_fields_from_llmisvcto choosejson.loadforllminferenceservice.jsonand keepyaml.safe_loadfor YAML artifacts.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@projects/guidellm/postprocess/guidellm/parsing/parsers.py` around lines 118 - 124, Update extract_fields_from_llmisvc to branch on the artifact name before loading content: use json.load for llminferenceservice.json and keep yaml.safe_load for llminferenceservice.yaml and llminferenceservice.yml. Anchor the change in the existing _is_llmisvc_artifact helper and the parsing logic in extract_fields_from_llmisvc so the JSON path preserves literal annotation values and does not run through the YAML parser.projects/guidellm/postprocess/guidellm/dashboard.py (1)
71-75: 📐 Maintainability & Code Quality | 🔵 Trivial | 💤 Low valueDocument the
request_latency_exclusion.
SECONDS_TO_MS_COLUMNSselects every metric with unit"s"except therequest_latency_*columns. The reason is not stated. A reader can interpret the exclusion as an oversight, because those metrics carry the same"s"unit. Add a short comment that states the dashboard expectsrequest_latency_*in seconds.♻️ Proposed comment
+# Dashboard latency columns are milliseconds, except request_latency_*, which +# the dashboard expects in seconds. SECONDS_TO_MS_COLUMNS = frozenset( column for _, _, column, unit, _ in DASHBOARD_METRICS if unit == "s" and not column.startswith("request_latency_") )🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@projects/guidellm/postprocess/guidellm/dashboard.py` around lines 71 - 75, Add a short explanatory comment immediately above SECONDS_TO_MS_COLUMNS stating that the dashboard expects request_latency_* metrics to remain in seconds, documenting why they are excluded despite having unit "s".projects/caliper/tests/test_kpi_format.py (1)
6-28: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winAdd a case for a varying label.
The test locks the merge half of the contract. It does not lock the other half: a label with more than one distinct value in the same run must stay per-KPI and must not reach
output["tests"][0]["labels"]. Theupdatecall atprojects/caliper/engine/kpi/format.pyline 69 relies on the first pass to exclude those keys. A regression in the first pass would leak a varying label to test level, and this test would still pass.💚 Proposed additional test
def test_hierarchical_format_keeps_varying_labels_per_kpi(): kpis = [ { "run_id": "run-1", "kpi_id": "dashboard_ttft_median", "value": 1, "labels": {"model": "llama", "rate_index": "0"}, }, { "run_id": "run-1", "kpi_id": "dashboard_ttft_median", "value": 2, "labels": {"model": "llama", "rate_index": "1"}, }, ] model = type("Model", (), {"plugin_module": "missing.plugin"})() output = transform_kpis_to_hierarchical_format(kpis, model) test = output["tests"][0] assert test["labels"] == {"model": "llama"} assert [kpi["labels"]["rate_index"] for kpi in test["kpis"]] == ["0", "1"]🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@projects/caliper/tests/test_kpi_format.py` around lines 6 - 28, Extend the hierarchical KPI formatting tests with a varying-label case in test_hierarchical_format_keeps_varying_labels_per_kpi: use KPIs from the same run where rate_index has different values, assert output["tests"][0]["labels"] contains only the common model label, and verify each KPI retains its own rate_index label.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@projects/guidellm/postprocess/guidellm/dashboard.py`:
- Around line 200-207: Harden _extract_dashboard_metrics against malformed
benchmark artifacts: at
projects/guidellm/postprocess/guidellm/dashboard.py#L200-L207, skip decoded
payloads that are not dictionaries; at `#L211-L218`, normalize an explicit null
mean to 0 before float conversion; and at `#L247-L253`, catch invalid
prompt_tokens/output_tokens coercion and skip or safely handle that record.
Preserve processing of valid files and metrics.
- Around line 211-218: The benchmark sorting logic in dashboard.py’s
benchmarks.sort key currently calls float() on the nested mean value, which
breaks when a benchmark reports null instead of a number. Update the sort key
path to coerce the extracted mean through a helper or inline fallback that
treats None as 0 before converting to float, while preserving the existing
nested metrics lookup and sort behavior for valid numeric means.
- Around line 254-256: Update _extract_dashboard_metrics to derive and store the
request-rate axis while iterating through benchmarks, alongside curves and
run_uuids. Change compute_dashboard_kpis to use this stored axis instead of
indexing request_rate from GuideLLMParser._create_aggregated_metrics, ensuring
skipped parser benchmarks cannot misalign KPI rate points.
- Around line 418-430: Update the group ordering in the rows-building loop
around groups and sorted(groups) so the second key element, rate_index, is
compared numerically rather than lexicographically. Preserve run_path as the
primary sort key and keep the existing row generation behavior unchanged.
In `@projects/guidellm/postprocess/guidellm/parsing/parsers.py`:
- Around line 173-179: Update the consumer condition around the
result-processing logic at line 621 to check whether field_value is not None
instead of using truthiness, preserving zero-valued replicas and
tensor_parallel_size entries extracted by the parser.
- Around line 151-155: Update the logging in the product-version extraction
block to report the normalized value assigned to result["product_version"],
rather than the raw product_version returned by
parse_product_version_from_annotation. Keep the existing extraction and storage
behavior unchanged.
- Around line 185-196: Update the serving-container extraction in the parser to
select the container with the intended serving name, falling back to index 0
when no name matches, before deriving image_tag and runtime_args. In the env
iteration, only access name and value fields for entries that are mappings,
while preserving the existing VLLM_ADDITIONAL_ARGS behavior.
In `@projects/llm_d/postprocess/plugin.py`:
- Around line 203-205: Restrict exported profile metadata to an explicit
non-sensitive allowlist in extract_kpi_labels_from_config() and
LlmDGuideLLMPlugin; remove runtime_args, env, and arbitrary
vllm_extra.args-derived values before writing KPI labels or CSV metadata. Update
projects/llm_d/postprocess/plugin.py at lines 203-205 and
projects/llm_d/orchestration/test_phase.py at lines 173-174, ensuring only
approved router_config or runtime metadata is emitted.
---
Nitpick comments:
In `@projects/caliper/tests/test_kpi_format.py`:
- Around line 6-28: Extend the hierarchical KPI formatting tests with a
varying-label case in test_hierarchical_format_keeps_varying_labels_per_kpi: use
KPIs from the same run where rate_index has different values, assert
output["tests"][0]["labels"] contains only the common model label, and verify
each KPI retains its own rate_index label.
In `@projects/guidellm/postprocess/guidellm/dashboard.py`:
- Around line 71-75: Add a short explanatory comment immediately above
SECONDS_TO_MS_COLUMNS stating that the dashboard expects request_latency_*
metrics to remain in seconds, documenting why they are excluded despite having
unit "s".
In `@projects/guidellm/postprocess/guidellm/parsing/parsers.py`:
- Around line 132-140: Update the docstring for the relevant YAML/JSON parsing
function to describe both YAML and JSON artifact inputs, and expand the Returns
section to include replicas, tensor_parallel_size, router_config, image_tag, and
runtime_args alongside the existing fields.
- Around line 580-583: Update the llmisvc_files sorting in the parser to retain
capture-state paths first while using each path itself as a deterministic
secondary sort key. Ensure the resulting order no longer depends on the original
node.artifact_paths traversal order before the first-file-wins merge.
- Around line 118-124: Update extract_fields_from_llmisvc to branch on the
artifact name before loading content: use json.load for llminferenceservice.json
and keep yaml.safe_load for llminferenceservice.yaml and
llminferenceservice.yml. Anchor the change in the existing _is_llmisvc_artifact
helper and the parsing logic in extract_fields_from_llmisvc so the JSON path
preserves literal annotation values and does not run through the YAML parser.
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📒 Files selected for processing (17)
projects/caliper/engine/kpi/format.pyprojects/caliper/tests/test_kpi_format.pyprojects/guidellm/postprocess/guidellm/dashboard.pyprojects/guidellm/postprocess/guidellm/parsing/parsers.pyprojects/llm_d/orchestration/config.d/cpt.yamlprojects/llm_d/orchestration/config.yamlprojects/llm_d/orchestration/presets.d/cks.yamlprojects/llm_d/orchestration/presets.d/cpt.yamlprojects/llm_d/orchestration/presets.d/rhoai-rc.yamlprojects/llm_d/orchestration/test_phase.pyprojects/llm_d/postprocess/__init__.pyprojects/llm_d/postprocess/plugin.pyprojects/llm_d/tests/test_postprocess_csv.pyprojects/llm_d/tests/test_profiles.pyprojects/rhaiis/postprocess/kpis.pyprojects/rhaiis/postprocess/parser.pyprojects/rhaiis/postprocess/plugin.py
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/test fournos rhaiis nvidia benchmark hera ci-quick |
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@albertoperdomo2 since I'm not a collaborator on this PR, only you can run the above command. |
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