v0.12.0 — configurable artifact columns + ScenarioReport

The tracing release: the traces table now takes configurable, artifact-derived
columns — create_trace_router(store, columns=[TraceColumn(...)]) pulls a
field out of a run's artifacts (agent/type/direction/field/scope), shown in the
list (with a column chooser) and as a Fields card on the run page; scope="session"
resolves as of the row's run, so a chat's question and latest answer show across
HITL-split runs. Also ScenarioReport (token/latency/tool totals via
result.report / scenario.report). Backwards-compatible.

Added

• Configurable artifact columns in the traces table. create_trace_router( store, columns=[TraceColumn(...)]) adds columns pulled from a run's
  artifacts: each TraceColumn names an agent, artifact type (class or
  name), direction (read/write/any) and a dotted field (a list step takes
  its first element unless an explicit index is given). Values are computed
  server-side per run and returned in each /api/traces item as fields
  (GET /api/columns lists the labels); the dashboard renders them with a
  per-browser column chooser. scope="session" resolves a column as of the
  row's run (every run up to it, chronological; read order reversed so the
  triggering artifact is the most recent and index=-1 means "latest so far").
  A chat is many runs and a HITL clarify splits one exchange into two (ask
  turn, then resume), so Question is the message that started the current
  exchange (shown on the resume row too) and Answer the latest reply so far.
  The run page also shows the configured columns as a Fields card
  (/api/traces/{id} carries fields), so the question — and a HITL clarify,
  via a PendingQuestion column — are visible when opening a run, not just in
  the list.
  RuntimeResources(trace_truncate=…) now controls how much artifact/response
  JSON a trace keeps (None = no clip), so deep fields stay resolvable. The
  devops example shows the question, the pending clarify question and the
  final answer; repair (which now mounts the trace dashboard) shows the
  question, the flow stage, the pending approval and the final answer.
• ScenarioResult.report / Scenario.report return a ScenarioReport: token
  totals (prompt_tokens/completion_tokens/total_tokens), llm_calls,
  tool_calls, spans, agents, errors and outcomes for a turn — or
  aggregated across every turn of a multi-turn scenario() — with to_dict()
  and a readable render(). result.llm gained prompt_tokens /
  completion_tokens alongside tokens.