wangwei and Copilot
f6e10145cd
Fix: build_models resolves separate AsyncOpenAI clients for judge and embedding models
...
Previously, only the judge_model's profile was looked up and its AsyncOpenAI
client was shared with embedding_factory. When embedding_model has a different
base_url/api_key (e.g. Qwen3-Embedding-4B on SiliconFlow vs gpt-5 on another
gateway), the embedding calls silently used the wrong URL, causing 402/404 errors.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com >
2026-07-01 21:15:09 +08:00
wangwei and Claude
f5c2dce64a
feat(advisor): add optimization advisor module
...
- rag_eval/advisor/: new package with rules engine, LLM analyzer, writer
- rules.py: 7-metric diagnostic rules (warning/critical thresholds, top-3 low samples)
- llm_analyzer.py: Chinese optimization report via judge_model, graceful fallback
- writer.py: writes optimization_advice.md + log summary
- __init__.py: run_advisor() entry point (no-op when optimization_advisor=False)
- Scenario.optimization_advisor: new bool field (default False)
- ScenarioModel: same field added, loader.py透传
- RunArtifactPaths.advice_md: new path field
- factory.py: build_models() now public; build_metric_pipeline() accepts pre-built llm/embeddings
- runner.py: lifts llm, passes to pipeline and advisor; calls run_advisor() at end
- siemens online YAML: optimization_advisor: true enabled
- tests: 9 rules tests + 6 writer tests, all pass
- docs: advisor section added to engine-flow.md and architecture.md
Co-Authored-By: Claude <noreply@anthropic.com >
2026-06-16 17:06:19 +08:00
