chore: remove Airflow completely from the stack

Drop all four Airflow containers (db, init, webserver, scheduler) from the
mlops compose profile, leaving MLflow as the sole mlops service. Remove
AIRFLOW_* env vars, config fields, health-check entries, DAG trigger code
in admin/bench routes, the airflow_dag_run_id schema column, Airflow nav
links and DAG-run links in the admin UI, the two Airflow DAG files
(bench_dag.py, sim_dag.py), and all related docs/ADR references.
Simulations now run exclusively via the subprocess path.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ml/experiments/bench/README.md

@@ -77,13 +77,9 @@ keys `artifact:candidates.json`, `artifact:prompt.txt`, `artifact:raw.txt`
 (tag fallback because the MLflow server uses a file:// artifact backend
 not accessible via REST from the host).
 
-## Integrating with Airflow (#95)
+## Running standalone
 
-A future DAG `ml/pipelines/prompt_ab_eval.py` will wrap `collect.py`
-exactly as shown in the quick-start, triggered on-demand from the admin
-UI or manually. The results feed into the admin leaderboard view.
-
-For now, the pipeline is runnable standalone on any machine with:
+The pipeline runs on any machine with:
 - Ollama models ≤4B
 - MLflow tracking server
 - Python 3.10+