vllm-async-loading-debug

name: vllm-async-loading-debug description: Debug vLLM async KV loading and PegaFlow connector behavior. Use when investigating async KV loads, WAITING_FOR_REMOTE_KVS states, load/save intents, connector metadata flow, prefetch behavior, or preemption interactions in vLLM scheduler/worker code.

Vllm Async Loading Debug

Overview

Trace the async KV loading path between vLLM scheduler and worker connectors, including prefetch and preemption edges.

Workflow

1) Confirm async-load symptom

• Record request IDs and statuses: WAITING, RUNNING, WAITING_FOR_REMOTE_KVS, PREEMPTED.
• Check async-load logs and whether prefetch is in progress.

2) Follow scheduler-side decisions

• python/pegaflow/connector/scheduler.py: prefetch query + LoadIntent creation.
• .project-plans/scheduler.py (private): load_kv_async gating and WAITING_FOR_REMOTE_KVS transitions.

3) Follow worker-side lifecycle

• python/pegaflow/connector/worker.py: start_load_kv() calls engine_client.load() and tracks PyLoadState.
• get_finished() polls is_ready() and emits finished_recving.

4) Check preemption and retries

• .project-plans/scheduler.py (private): _preempt_request() and reset_prefix_cache() behavior.
• invalid_block_ids handling can trigger recompute or failure based on kv_load_failure_policy.

Reference Files

• Read references/async-loading.md for full call flow and log markers.