Files
agentic-kvc/replayer/replay.py
Gahow Wang 9cebdb6b9b Fix multi-turn replay fidelity: track realized output tokens across all components
The replayer and proxy were building multi-turn prompts from trace tokens,
but the model generates different output tokens. Subsequent turns had wrong
prefix tokens, causing cache misses and invalid experimental measurements.

- replay.py: min_tokens=max_tokens for deterministic length, return_token_ids
  to capture actual output, _apply_realized_prefix for next-turn correction
- proxy: extract output token_ids from SSE, record prompt+output as realized
  prefix in shadow cache, extract _handle_local_request to deduplicate
- bench.sh/launch_elastic_p2p.sh: default elastic mode to unified policy
- mooncake_connector: only send prompt blocks (not stale output blocks),
  track failed_recving_block_ids for error recovery

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-05-24 14:47:51 +08:00

415 lines
15 KiB
Python

"""Trace replayer — send requests to vLLM following trace timing.
Uses hash_ids from the trace to construct synthetic prompts that
reproduce realistic prefix-cache hit patterns.
Key behaviors:
- Trace-driven dispatch: each request is sent at its trace timestamp.
No artificial concurrency limits or time compression.
- Per-session sequencing: turns within a session are sent in order,
each waiting for the previous to complete before dispatching.
If a turn completes after its successor's timestamp, the successor
fires immediately (no waiting for a past timestamp).
"""
from __future__ import annotations
import asyncio
import json
import logging
import time
from collections import defaultdict
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
import random as _random
import httpx
from .metrics import IncrementalMetricSink, RequestMetrics, write_summary_json
from .trace import TraceRequest, load_trace
logger = logging.getLogger(__name__)
BLOCK_SIZE = 512
VOCAB_SIZE = 151936
TOKEN_RANGE_START = 100
TOKEN_RANGE_END = VOCAB_SIZE - 100
_block_cache: dict[int, list[int]] = {}
def _hash_id_to_token_ids(hash_id: int) -> list[int]:
"""Deterministically map a hash_id to BLOCK_SIZE token IDs."""
if hash_id in _block_cache:
return _block_cache[hash_id]
rng = _random.Random(hash_id)
ids = [rng.randint(TOKEN_RANGE_START, TOKEN_RANGE_END) for _ in range(BLOCK_SIZE)]
_block_cache[hash_id] = ids
return ids
@dataclass
class ReplayConfig:
trace_path: Path
output_path: Path
endpoint_url: str # comma-separated for round-robin: "http://host:8000,http://host:8001"
concurrency_limit: int = 2000
request_timeout_s: float = 600.0
request_limit: int | None = None
model_name: str = "default"
max_inflight_sessions: int | None = None # cap on concurrent sessions; None = unlimited
def _build_prompt_token_ids(req: TraceRequest) -> list[int]:
"""Build token IDs from hash_ids for prefix-cache-aware replay.
Same hash_id prefix → same token ID prefix → APC cache hit in vLLM.
"""
ids: list[int] = []
for hid in req.hash_ids:
ids.extend(_hash_id_to_token_ids(hid))
# Pad to input_length with deterministic tokens
pad_rng = _random.Random(req.chat_id)
while len(ids) < req.input_length:
ids.append(pad_rng.randint(TOKEN_RANGE_START, TOKEN_RANGE_END))
return ids[:req.input_length]
@dataclass
class _SessionState:
session_id: str
turns: list[TraceRequest]
metrics: list[RequestMetrics] = field(default_factory=list)
@dataclass
class _DispatchResult:
metric: RequestMetrics
output_token_ids: list[int]
_endpoint_counter = 0
def _pick_endpoint(config: ReplayConfig) -> str:
"""Round-robin across comma-separated endpoints."""
global _endpoint_counter
endpoints = [e.strip() for e in config.endpoint_url.split(",")]
url = endpoints[_endpoint_counter % len(endpoints)]
_endpoint_counter += 1
return url
async def _dispatch_request(
*,
client: httpx.AsyncClient,
config: ReplayConfig,
req: TraceRequest,
prompt_token_ids: list[int],
sem: asyncio.Semaphore,
) -> _DispatchResult:
"""Send one request via /v1/completions (streaming) and collect metrics."""
endpoint = _pick_endpoint(config)
target_output_tokens = max(1, req.output_length)
payload = {
"model": config.model_name,
"prompt": prompt_token_ids,
"max_tokens": target_output_tokens,
"min_tokens": target_output_tokens,
"temperature": 0,
"return_token_ids": True,
"stream": True,
"stream_options": {"include_usage": True},
}
start = time.perf_counter()
ttft_s = None
n_output = 0
cached_tokens = 0
finish_reason = None
err = None
token_times: list[float] = []
output_token_ids: list[int] = []
req_headers = {"X-Session-Id": req.session_id}
async with sem:
try:
async with client.stream(
"POST",
f"{endpoint}/v1/completions",
json=payload,
headers=req_headers,
timeout=config.request_timeout_s,
) as resp:
resp.raise_for_status()
async for raw_line in resp.aiter_lines():
if not raw_line or not raw_line.startswith("data:"):
continue
data = raw_line[5:].strip()
if data == "[DONE]":
break
try:
chunk = json.loads(data)
except json.JSONDecodeError:
continue
choices = chunk.get("choices", [])
if choices:
now = time.perf_counter()
delta = choices[0].get("text", "")
chunk_token_ids = choices[0].get("token_ids")
if isinstance(chunk_token_ids, list):
clean_ids = [
int(t) for t in chunk_token_ids
if isinstance(t, int)
]
if clean_ids:
if ttft_s is None:
ttft_s = now - start
output_token_ids.extend(clean_ids)
token_times.extend([now] * len(clean_ids))
elif delta:
if ttft_s is None:
ttft_s = now - start
token_times.append(now)
fr = choices[0].get("finish_reason")
if fr:
finish_reason = fr
usage = chunk.get("usage")
if usage:
n_output = usage.get("completion_tokens", n_output)
cached_tokens = _extract_cached_tokens(usage)
except Exception as exc:
err = repr(exc)[:300]
end = time.perf_counter()
e2e = end - start
if output_token_ids:
n_output = len(output_token_ids)
elif n_output == 0 and token_times:
n_output = len(token_times)
if err is None and n_output != target_output_tokens:
err = (
"output_token_mismatch "
f"requested={target_output_tokens} actual={n_output}"
)
tpot = 0.0
if len(token_times) > 1:
inter_token = [token_times[i+1] - token_times[i]
for i in range(len(token_times) - 1)]
tpot = sum(inter_token) / len(inter_token)
return _DispatchResult(
metric=RequestMetrics(
request_id=req.request_id,
session_id=req.session_id,
turn_id=req.turn_id,
trace_timestamp_s=req.timestamp_s,
input_length=req.input_length,
output_length=req.output_length,
request_type=req.request_type,
effective_input_length=len(prompt_token_ids),
cached_tokens=cached_tokens,
latency_s=e2e,
ttft_s=ttft_s,
tpot_s=tpot,
actual_output_tokens=n_output,
requested_output_tokens=req.output_length,
finish_reason=finish_reason,
error=err,
),
output_token_ids=output_token_ids,
)
def _apply_realized_prefix(
prompt_token_ids: list[int],
realized_context: list[int],
) -> list[int]:
"""Replace the reusable session prefix with engine-realized tokens."""
if not realized_context:
return prompt_token_ids
out = prompt_token_ids.copy()
n = min(len(out), len(realized_context))
out[:n] = realized_context[:n]
return out
def _extract_cached_tokens(usage: dict) -> int:
ct = 0
details = usage.get("prompt_tokens_details")
if isinstance(details, dict):
ct = details.get("cached_tokens", 0) or 0
if ct == 0:
ct = usage.get("cached_tokens", 0) or 0
return int(ct)
async def _run_session(
*,
state: _SessionState,
config: ReplayConfig,
client: httpx.AsyncClient,
request_sem: asyncio.Semaphore,
earliest_ts: float,
sweep_start: float,
sink: IncrementalMetricSink,
session_sem: asyncio.Semaphore | None = None,
) -> list[RequestMetrics]:
if session_sem is not None:
await session_sem.acquire()
realized_context: list[int] = []
try:
for req in state.turns:
# Wait until this request's trace timestamp
target_wall = (req.timestamp_s - earliest_ts)
elapsed = time.perf_counter() - sweep_start
if elapsed < target_wall:
await asyncio.sleep(target_wall - elapsed)
token_ids = _apply_realized_prefix(
_build_prompt_token_ids(req),
realized_context,
)
result = await _dispatch_request(
client=client, config=config, req=req,
prompt_token_ids=token_ids, sem=request_sem,
)
metric = result.metric
state.metrics.append(metric)
await sink.append(metric)
if metric.error is None:
realized_context = token_ids + result.output_token_ids
finally:
if session_sem is not None:
session_sem.release()
return state.metrics
async def _snapshot_prefix_cache_metrics(url_csv: str) -> dict[str, float]:
"""Scrape vLLM /metrics for prefix cache counters (aggregated across endpoints)."""
total = {"queries": 0.0, "hits": 0.0,
"external_queries": 0.0, "external_hits": 0.0}
endpoints = [e.strip() for e in url_csv.split(",")]
async with httpx.AsyncClient(timeout=10) as c:
for url in endpoints:
try:
r = await c.get(f"{url}/metrics")
for line in r.text.split("\n"):
if line.startswith("vllm:prefix_cache_queries_total"):
total["queries"] += float(line.split()[-1])
elif line.startswith("vllm:prefix_cache_hits_total"):
total["hits"] += float(line.split()[-1])
elif line.startswith("vllm:external_prefix_cache_queries_total"):
total["external_queries"] += float(line.split()[-1])
elif line.startswith("vllm:external_prefix_cache_hits_total"):
total["external_hits"] += float(line.split()[-1])
except Exception:
pass
return total
async def replay_trace(config: ReplayConfig) -> list[RequestMetrics]:
"""Main entry: load trace, replay against endpoint, return metrics."""
requests = load_trace(config.trace_path, request_limit=config.request_limit)
if not requests:
return []
by_session: dict[str, list[TraceRequest]] = defaultdict(list)
for r in requests:
by_session[r.session_id].append(r)
for sid in by_session:
by_session[sid].sort(key=lambda r: (r.turn_id, r.timestamp_s))
sessions = sorted(by_session.items(), key=lambda kv: kv[1][0].timestamp_s)
earliest_ts = sessions[0][1][0].timestamp_s
latest_ts = max(r.timestamp_s for r in requests)
trace_span = latest_ts - earliest_ts
request_sem = asyncio.Semaphore(config.concurrency_limit)
session_sem = (
asyncio.Semaphore(config.max_inflight_sessions)
if config.max_inflight_sessions and config.max_inflight_sessions > 0
else None
)
sink = IncrementalMetricSink(config.output_path)
n_sessions = len(sessions)
n_requests = len(requests)
qps = n_requests / trace_span if trace_span > 0 else 0
logger.info("Replaying %d sessions (%d requests) over %.0fs (%.2f req/s)",
n_sessions, n_requests, trace_span, qps)
if session_sem is not None:
logger.info("Session admission cap: %d concurrent sessions",
config.max_inflight_sessions)
pre_metrics = await _snapshot_prefix_cache_metrics(config.endpoint_url)
sweep_start = time.perf_counter()
try:
limits = httpx.Limits(
max_connections=2000,
max_keepalive_connections=500,
keepalive_expiry=30.0,
)
async with httpx.AsyncClient(
timeout=config.request_timeout_s,
trust_env=False,
limits=limits,
) as client:
tasks = [
asyncio.create_task(_run_session(
state=_SessionState(session_id=sid, turns=turns),
config=config, client=client,
request_sem=request_sem,
earliest_ts=earliest_ts, sweep_start=sweep_start,
sink=sink,
session_sem=session_sem,
))
for sid, turns in sessions
]
all_results = await asyncio.gather(*tasks)
finally:
sink.close()
sweep_elapsed = time.perf_counter() - sweep_start
post_metrics = await _snapshot_prefix_cache_metrics(config.endpoint_url)
flat = [m for group in all_results for m in group]
summary_path = config.output_path.with_suffix(".summary.json")
write_summary_json(summary_path, flat)
# Compute aggregate prefix cache hit ratio from /metrics deltas
delta_queries = post_metrics.get("queries", 0) - pre_metrics.get("queries", 0)
delta_hits = post_metrics.get("hits", 0) - pre_metrics.get("hits", 0)
hit_ratio = delta_hits / delta_queries if delta_queries > 0 else 0.0
delta_ext_queries = post_metrics.get("external_queries", 0) - pre_metrics.get("external_queries", 0)
delta_ext_hits = post_metrics.get("external_hits", 0) - pre_metrics.get("external_hits", 0)
ext_hit_ratio = delta_ext_hits / delta_ext_queries if delta_ext_queries > 0 else 0.0
logger.info("Done: %d/%d succeeded in %.1fs", sum(1 for m in flat if m.error is None), len(flat), sweep_elapsed)
logger.info("Prefix cache: local=%.1f%% external=%.1f%%",
hit_ratio * 100, ext_hit_ratio * 100)
# Append cache stats to summary
import json as _json
summary = _json.loads(summary_path.read_text())
summary["prefix_cache_queries_tokens"] = int(delta_queries)
summary["prefix_cache_hits_tokens"] = int(delta_hits)
summary["prefix_cache_hit_ratio"] = hit_ratio
summary["external_cache_queries_tokens"] = int(delta_ext_queries)
summary["external_cache_hits_tokens"] = int(delta_ext_hits)
summary["external_cache_hit_ratio"] = ext_hit_ratio
summary["wall_clock_s"] = sweep_elapsed
summary_path.write_text(_json.dumps(summary, indent=2, sort_keys=True))
logger.info("Summary written to %s", summary_path)
return flat