[Core][Frontend] Add per-request prefix cache telemetry

[cook1e-0707]

Purpose

Extend the existing opt-in --enable-per-request-metrics facility with
request-attributed prompt and KV-cache telemetry, without changing cache or
scheduler behavior.

For single-sequence chat/completion requests, metrics.prefix_cache contains:

• logical token accounting: computed, cached, local cached, external cached,
  and cache-creation tokens;
• physical KV activity during prefill: new full blocks, allocations, and
  evictions;
• number of prefill chunks and prefill time.

Streaming emits the object on the existing final usage/metrics chunk;
non-streaming emits it in response metrics. The response's existing top-level
id correlates the data with the request. Offline RequestOutput and stat
logger FinishedRequestStats expose the same PrefillStats with their existing
request_id.

The fields intentionally do not enter OpenAI usage: block activity is an
engine implementation detail, and local/external scheduler sources are not
billing-token categories. The patch also avoids changing KV-event schemas while
request identity is under discussion in #51381, and does not duplicate the
prompt_tokens_details work in #52199.

Semantics worth calling out:

• token decomposition is logical first-admission accounting, so recomputation
  after preemption is not double-counted there;
• prefill chunks and physical block activity describe actual work, including
  re-prefill after preemption;
• block counts are physical totals across cache groups;
• an eviction is attributed to the request whose allocation triggered it, not
  to the request that originally owned the evicted cached block;
• external cached tokens describe the scheduler's external KV source and do
  not prove that every transferred block was a hit in an upstream cache;
• prefill_time_ms currently uses the existing TTFT boundaries: first
  scheduling to first output token, including prefill-time preemptions.

Behavior invariants:

• no hash/hash-input changes;
• no cache admission, replacement, eviction choice, free-queue, or refcount
  changes;
• no scheduler budget, priority, preemption, chunk-size, or admission changes;
• no model-output or sampling changes;
• no existing default response change; frontend serialization is still behind
  --enable-per-request-metrics.

The added block-pool counters are monotonic observers incremented only after
existing actions complete. Attribution uses deltas around scheduler-confined
synchronous cache operations, and none of the new counters feeds a decision.

Related work:

• [Frontend] add per-request timing metrics field to response body of Chat/Completions APIs #46768 introduced the per-request metrics surface.
• [Metrics] Add request_id to FinishedRequestStats to enable correlation between metrics and requests #39710 added request_id to finished-request stats.
• [Front-end] [Messages] Populate num_cache_creation_tokens #48535 added cache-creation token plumbing.
• [Feature][Frontend] Expose local/external prefix-cache hit breakdown in prompt_tokens_details #52199 is working on local/external prompt token details in OpenAI usage.
• [Core][KV Events] Echo session_id on GPU BlockStored events #51381 is working on request/session identity for KV events.
• [Core] Distinguish reused from newly cached blocks in BlockStored #51699 evolves KV block events.

AI assistance disclosure: OpenAI Codex assisted with research, implementation,
tests, and this description. The human submitter confirms that they reviewed
every changed line and approved upstream submission. The commit contains both
Assisted-by: OpenAI Codex and the human DCO sign-off.

Test Plan

# Core request attribution
.venv/bin/pytest -q --confcutdir=tests/v1/core \
  tests/v1/core/test_prefix_caching.py
VLLM_TARGET_DEVICE=cpu .venv/bin/pytest -q \
  --confcutdir=tests/v1/core tests/v1/core/test_scheduler.py
PYTHONPATH=. .venv/bin/pytest -q --confcutdir=tests/v1/metrics \
  tests/v1/metrics/test_stats.py

# Frontend streaming/non-streaming and request-id correlation
.venv/bin/pytest -q --confcutdir=tests/entrypoints/openai \
  tests/entrypoints/openai/completion/test_completion_error.py
.venv/bin/pytest -q --confcutdir=tests/entrypoints/openai \
  tests/entrypoints/openai/chat_completion/test_serving_chat.py \
  -k "build_per_request_timing_metrics_valid_timestamps or \
      chat_per_request_metrics or streaming_metrics_ride_on_usage_chunk"

# No-tokenizer RequestOutput propagation
PYTHONPATH=. .venv/bin/pytest -q --confcutdir=tests/v1/engine \
  tests/v1/engine/test_output_processor.py -k prefill_stats

# Applicable formatting/spelling/docs checks
.venv/bin/pre-commit run ruff-check --all-files
.venv/bin/pre-commit run ruff-format --all-files
.venv/bin/pre-commit run typos --files <changed-files>
.venv/bin/pre-commit run markdownlint-cli2 \
  --files docs/features/per_request_metrics.md
git diff --check

Mypy was also compared between this branch and an independent worktree at the
exact base commit, to distinguish pre-existing errors from introduced errors.

Test Result

• 293 non-duplicated tests passed:
  • prefix caching: 93;
  • scheduler: 150;
  • stats: 13;
  • completion frontend: 32;
  • relevant chat frontend: 4;
  • no-tokenizer output propagation: 1.
• ruff-check, ruff-format, typos, markdownlint-cli2, and
  git diff --check passed.
• Feature and clean-base mypy runs reported the same five errors in unchanged
  current-main code; this patch added no observed mypy error. Repository-wide
  mypy is therefore not claimed as green in this environment.
• No GPU/end-to-end model workload or full upstream suite was run.
• The full output-processor test file could not access the gated
  meta-llama/Llama-3.2-1B model (HTTP 401); no credential was supplied or
  exposed, and the dedicated no-tokenizer propagation test passed.

Synthetic block-pool microbenchmark (100,000 allocate/free-eight-block
iterations, seven repeats): clean-base median about 0.13908 s, feature median
about 0.14424 s, or roughly +0.052 microseconds per call (+3.7% in the trivial
Python-only loop). This is not an end-to-end latency claim.

---

• Purpose and related work documented.
• Test plan included.
• Local test results included with limitations.
• Documentation updated.
• Human submitter reviewed every changed line.
• Human submitter approved submission.

[claude]

Claude Code Review

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[mergify]

Documentation preview: https://vllm--53795.org.readthedocs.build/en/53795/

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @cook1e-0707.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[RichardoMrMu]

[P2] Keep telemetry live across streaming-input continuations. Request.take_prefill_stats() clears the accumulator on the first emitted token. A resumable request is then reused by _update_request_as_session() with nonzero num_computed_tokens; that path neither installs a new accumulator nor re-runs the initial .set() branch (num_computed_tokens == 0). Consequently this guard and the block-activity guards skip every later input chunk. RequestState.apply_streaming_update() marks the request as prefilling again, but OutputProcessor only replaces prefill_stats when a non-None value arrives, so subsequent/final RequestOutputs keep the first chunk's stale metrics. A two-chunk StreamingInput where chunk 2 changes cache state therefore omits chunk 2's token accounting, allocations/evictions, and chunk count. Please define session-cumulative versus per-chunk semantics, re-arm/merge at continuation accordingly, and cover the two-chunk lifecycle in tests/v1/streaming_input/test_scheduler_streaming.py plus output propagation.

[cook1e-0707]

Addressed in 2258331.\n\nI defined streaming-input telemetry as session-cumulative at the RequestOutput boundary, while the scheduler records one independent snapshot per admitted input chunk:\n\n- _update_request_as_session() re-arms PrefillStats for every continuation.\n- Retained generated tokens are excluded from the continuation's logical prompt counters.\n- A cached-token baseline excludes retained session KV from the continuation's cache-creation count.\n- OutputProcessor merges chunk snapshots into a new cumulative object, so previously emitted outputs do not mutate.\n- RequestOutput.add() keeps the latest cumulative snapshot.\n\nCoverage now includes a two-chunk scheduler lifecycle where chunk 2 creates a new cache block, plus output propagation/aggregation assertions.\n\nValidation:\n- 24 focused scheduler/metrics/output tests passed.\n- pre-commit on all changed files passed, including Ruff, formatting, mypy, markdownlint, and repository policy hooks.

[RichardoMrMu]

Thanks — the cumulative/immutability pieces are fixed on exact head 2258331e71ab2b8a3f339f841f5761a2dc2931b6, but the retained-KV exclusion is still incomplete for a partial cache block. estimate_cached_tokens() only sees the last full cache-indexed boundary, not every valid KV token already retained by the session. With block size 16, let chunk 1 leave 17 valid KV tokens (16 prompt + 1 retained generated token), so the baseline is 16. Add 16 new prompt tokens: the cached boundary becomes 32, and the current code reports min(32 - 16, 16) = 16 cache-creation tokens. But block [16, 32) contains one old retained token, so only 15 of those tokens belong to the new chunk; its final new token is still in the partial block. The current regression starts exactly on the 16-token boundary and discards the STOP token, so it cannot catch this.

Please baseline against the continuation's full valid-KV boundary (subject to cacheability semantics), or explicitly compute the overlap between the new prompt interval and newly cache-indexed interval, and add a two-chunk test retaining at least one generated token in a partial block. Re-arm, cumulative merge, and prior-output immutability otherwise look good. I did not run the suite locally, so I’m not making an independent runtime-suite claim; this part of the original finding remains open.

[cook1e-0707]

Addressed in c3032a9.

The continuation now records session.num_computed_tokens before appending the new input as prefill_stats_cache_creation_start. At that point it is the full valid-KV boundary, including retained generated tokens in a partial block, rather than only the last full cache-indexed boundary. Finalization intersects the newly cache-indexed suffix with the active chunk by subtracting that start and clamping to the chunk prompt length.

The regression now exercises the exact partial-block case:

• block size 16;
• chunk 1 prefills 16 tokens, then retains one computed generated token and discards the following uncomputed STOP token;
• chunk 2 adds 16 prompt tokens;
• the test asserts the retained generated token remains in the session prompt and num_cache_creation_tokens == 15 for chunk 2.

Validation on the updated head:

• 303 non-overlapping focused tests passed: prefix caching 93, scheduler 150, stats 13, streaming-input scheduler 9, completion frontend 32, relevant chat frontend 4, output propagation 2.
• pre-commit passed on all 20 PR-changed files, including Ruff, formatting, typos, mypy, markdownlint, SPDX, and repository policy hooks.
• git diff --check passed.

I also re-reviewed the full PR diff against the current upstream merge base; I found no additional correctness blocker in the request accounting, block-activity attribution, output propagation, frontend serialization, or default-response gating paths.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @cook1e-0707.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @cook1e-0707.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork