A3: vLLM scheduler patch for step-level JSONL log

When AGENTIC_STEP_LOG_PATH is set, the scheduler emits one JSONL line
per scheduler step with t_unix, worker_id, prefill/decode token
counts, n_running/n_waiting, preempted ids, and per-request phase
labels. No-op when the env var is unset, so production engines are
not impacted. bench.sh now threads AGENTIC_STEP_LOG_DIR through to
each per-engine launch so step logs end up at engine_${i}.jsonl.

Required by Batch 2 (PD-colo interference index) and Batch 5
(same-worker overlap attribution); engine /metrics polling cannot
provide per-step granularity.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

scripts/bench.sh

@@ -161,12 +161,24 @@ launch_instances() {
         use_mooncake=true
     fi
 
+    # Optional: when AGENTIC_STEP_LOG_DIR is exported, point each engine at its
+    # own JSONL file so the patched scheduler emits per-step records.
+    local step_log_dir="${AGENTIC_STEP_LOG_DIR:-}"
+    if [ -n "$step_log_dir" ]; then
+        mkdir -p "$step_log_dir"
+    fi
+
     for i in $(seq 0 $((N_INSTANCES - 1))); do
         local port=$((BASE_PORT + i))
         local master=$((29500 + i))
         local logfile="$OUTDIR/vllm_inst_${i}.log"
+        local step_env=""
+        if [ -n "$step_log_dir" ]; then
+            step_env="AGENTIC_STEP_LOG_PATH=$step_log_dir/engine_${i}.jsonl AGENTIC_WORKER_ID=engine_${i}"
+        fi
 
         if [ "$use_mooncake" = "true" ]; then
+            env $step_env \
             PYTHONHASHSEED=42 \
             VLLM_MOONCAKE_BOOTSTRAP_PORT=$((8998 + i)) \
             MASTER_PORT=$master \
@@ -180,6 +192,7 @@ launch_instances() {
                 $vllm_extra_args \
                 > "$logfile" 2>&1 &
         else
+            env $step_env \
             MASTER_PORT=$master \
             CUDA_VISIBLE_DEVICES=$i \
             $VLLM serve "$MODEL" \