sort: add a.name as final sort column in model listing queries

get_llmage_llm and get_llms_by_catelog had ORDER BY ending
at a.id — model names within same provider/catalog appeared
in arbitrary order. Added a.name as final sort key.
This commit is contained in:
yumoqing 2026-07-28 16:23:41 +08:00
parent a2937d3cff
commit 68dd92a353
2 changed files with 165 additions and 3 deletions

View File

@ -364,7 +364,7 @@ where 1=1
elif catelogid:
sql += " and m.llmcatelogid = ${catelogid}$"
ns['catelogid'] = catelogid
sql += " order by m.llmcatelogid, a.id"
sql += " order by m.llmcatelogid, a.id, a.name"
recs = await sor.sqlExe(sql, ns)
if llmid:
return recs[0] if recs else None
@ -458,8 +458,7 @@ async def get_llms_by_catelog(catelogid=None, orderby='providerid'):
if catelogid:
sql += " and m.llmcatelogid = ${catelogid}$"
params['catelogid'] = catelogid
sql += " order by m.llmcatelogid, a.id"
sql += " order by m.llmcatelogid, a.id, a.name"
recs = await sor.sqlExe(sql, params)
# 批量查询所有模型的 ppid 映射(避免 N+1 查询)

163
load_test.py Normal file
View File

@ -0,0 +1,163 @@
#!/usr/bin/env python3
"""并发压力测试 llmage /v1/chat/completions统计 TTFB / 完成时间 / QPM"""
import asyncio
import aiohttp
import time
import json
import sys
import statistics
from dataclasses import dataclass, field
from typing import List
URL = "https://token.opencomputing.cn/llmage/v1/chat/completions"
TOKEN = "V9J41PngWBUU6gdHWJWDJ"
MODEL = "qwen3.6-35b-a3b"
DURATION = 180 # 3 分钟
CONCURRENCIES = [10, 50, 100, 200]
@dataclass
class ReqStat:
prompt_idx: int
start_ts: float
first_byte_ts: float | None = None
end_ts: float | None = None
async def worker(session: aiohttp.ClientSession, idx: int, stats_out: list):
"""单个请求:发送 stream 请求,记录首字时间和完成时间"""
prompt = f"请用一句话介绍你自己,编号{idx}"
payload = {
"model": MODEL,
"stream": True,
"messages": [{"role": "user", "content": prompt}],
}
stat = ReqStat(prompt_idx=idx, start_ts=time.monotonic())
try:
async with session.post(
URL,
json=payload,
headers={
"Content-Type": "application/json",
"Authorization": f"Bearer {TOKEN}",
},
timeout=aiohttp.ClientTimeout(total=120),
) as resp:
first = True
async for line in resp.content:
if first:
stat.first_byte_ts = time.monotonic()
first = False
# 读完所有 chunk 才算完成
stat.end_ts = time.monotonic()
except Exception as e:
# 异常请求也记录TTFB=None 表示失败)
stat.end_ts = time.monotonic()
stats_out.append(stat)
async def run_concurrency(concurrency: int):
"""以固定并发运行 DURATION 秒,持续发起新请求"""
stats: List[ReqStat] = []
idx = 0
stop_at = time.monotonic() + DURATION
connector = aiohttp.TCPConnector(limit=concurrency + 20, force_close=True)
async with aiohttp.ClientSession(connector=connector) as session:
tasks: list[asyncio.Task] = []
while time.monotonic() < stop_at:
# 保持并发数:补满到 concurrency
while len(tasks) < concurrency and time.monotonic() < stop_at:
idx += 1
tasks.append(
asyncio.create_task(worker(session, idx, stats))
)
if not tasks:
break
# 等待任意一个完成,腾出槽位
done, tasks = await asyncio.wait(
tasks, return_when=asyncio.FIRST_COMPLETED, timeout=0.5
)
# 清理已完成的
tasks = list(tasks)
# 时间到,等待所有进行中的请求完成
if tasks:
await asyncio.wait(tasks)
return stats
def analyze(name: str, stats: List[ReqStat]):
"""分析并打印统计"""
ttfb_list = [s.first_byte_ts - s.start_ts for s in stats if s.first_byte_ts]
total_list = [s.end_ts - s.start_ts for s in stats if s.end_ts and s.first_byte_ts]
failed = sum(1 for s in stats if s.first_byte_ts is None)
total_req = len(stats)
elapsed = DURATION
qpm = total_req / (elapsed / 60)
print(f"\n{'='*60}")
print(f" 并发={name} | 运行{DURATION}s | 总请求={total_req} | 失败={failed}")
print(f"{'='*60}")
if ttfb_list:
print(f" TTFB (s): min={min(ttfb_list):.3f} avg={statistics.mean(ttfb_list):.3f} "
f"p50={statistics.median(ttfb_list):.3f} p95={_pct(ttfb_list, 95):.3f} p99={_pct(ttfb_list, 99):.3f}")
if total_list:
print(f" 完成 (s): min={min(total_list):.3f} avg={statistics.mean(total_list):.3f} "
f"p50={statistics.median(total_list):.3f} p95={_pct(total_list, 95):.3f} p99={_pct(total_list, 99):.3f}")
print(f" QPM: {qpm:.1f}")
print(f" QPS: {total_req / elapsed:.1f}")
# 按分钟分段统计
for minute in range(int(elapsed / 60)):
win_start = minute * 60
win_end = (minute + 1) * 60
cnt = sum(1 for s in stats if s.end_ts and (s.end_ts - s.start_ts) >= 0
and win_start <= (s.start_ts - stats[0].start_ts) < win_end)
print(f"{minute+1}分钟完成请求数: {cnt}")
return {
"concurrency": name,
"total": total_req,
"failed": failed,
"ttfb_avg": statistics.mean(ttfb_list) if ttfb_list else None,
"ttfb_p50": statistics.median(ttfb_list) if ttfb_list else None,
"ttfb_p95": _pct(ttfb_list, 95) if ttfb_list else None,
"total_avg": statistics.mean(total_list) if total_list else None,
"total_p50": statistics.median(total_list) if total_list else None,
"qpm": qpm,
}
def _pct(data, p):
return sorted(data)[int(len(data) * p / 100)]
async def main():
results = []
for c in CONCURRENCIES:
print(f"\n>>> 开始测试 并发={c} ...")
stats = await run_concurrency(c)
r = analyze(str(c), stats)
results.append(r)
# 汇总表格
print(f"\n{'='*60}")
print(" 汇总对比")
print(f"{'='*60}")
print(f" {'并发':>6} {'总请求':>8} {'失败':>5} {'TTFB_avg':>9} {'TTFB_p50':>9} {'TTFB_p95':>9} {'完成_avg':>9} {'QPM':>8}")
for r in results:
print(f" {r['concurrency']:>6} {r['total']:>8} {r['failed']:>5} "
f"{r['ttfb_avg']:.3f}s" if r['ttfb_avg'] else "N/A".rjust(9) + " "
f"{(r['ttfb_p50'] or 0):.3f}s".rjust(9) + " "
f"{(r['ttfb_p95'] or 0):.3f}s".rjust(9) + " "
f"{r['total_avg']:.3f}s".rjust(9) if r['total_avg'] else "N/A".rjust(9))
if __name__ == "__main__":
asyncio.run(main())