Convert ml-serving from isolated MLflow runs to nested traces using mlflow.start_span_no_context(). The recommend endpoint now emits a full span tree: recommend (CHAIN) → build_context (TOOL), agent:* (AGENT) ×N, llm_orchestrator (LLM). Compute and infer endpoints each emit a single span. Supporting changes: - mlflow-skinny>=3.1.0 added to requirements - MLflow configured with --serve-artifacts + mlflow-artifacts:/ default root for cross-container artifact proxy (spans now persist from ml-serving) - --allowed-hosts extended to include mlflow:5000 (SDK includes port in Host) - science_destiny slider wired through prompts.py and recommend endpoint - Config page exposes science/destiny slider (0=data-driven, 100=intuitive) - Tip page shows rationale inline on tap Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
8.3 KiB
8.3 KiB