Check getEligibleAgentIds per user in runCycle before calling
computeAndStore — agents without consented data sources, silenced by
active context, or disabled via preference are skipped rather than
computed unconditionally. Eligibility check failure skips the whole
user (fail-closed). Skipped count added to cycle-complete log line.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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>
Extracts computeAndStore() from the /agents/:agentId/compute route so it
can be called without an HTTP round-trip. startAgentPrecomputeScheduler()
runs every 15 min: fetches active users (tip view in 48h), runs all agents
in parallel per user, then purges outputs expired >24h. Agent IDs are
resolved from ml/serving /health at startup with a fallback hardcoded list.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
