feat(serving): replace MLflow run logging with native trace spans

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>

ml/serving/requirements.txt

@@ -7,3 +7,4 @@ anthropic>=0.40.0
 nats-py>=2.9.0
 structlog>=24.1.0
 sentry-sdk>=2.0.0
+mlflow-skinny>=3.1.0