766 lines
26 KiB
Python
766 lines
26 KiB
Python
"""
|
||
ModelHub 全云端提交智能体
|
||
部署在平台容器中，直接从内网提交验证任务
|
||
|
||
功能：
|
||
- POST /run → 触发一次完整流程（搜索→筛选→提交）
|
||
- GET /status → 查看当前状态
|
||
- GET /health → 健康检查
|
||
"""
|
||
|
||
import json
|
||
import os
|
||
import signal
|
||
import sqlite3
|
||
import threading
|
||
import time
|
||
import traceback
|
||
from datetime import datetime
|
||
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
|
||
from urllib.parse import urlparse, parse_qs
|
||
|
||
import requests
|
||
import yaml
|
||
|
||
# ============================================================
|
||
# 配置
|
||
# ============================================================
|
||
|
||
HOST = "0.0.0.0"
|
||
PORT = 8080
|
||
STRATEGY_ID = os.getenv("STRATEGY_ID", "")
|
||
|
||
# 目标GPU
|
||
TARGET_GPU = "Iluvatar_bi-150"
|
||
|
||
# 账号Token
|
||
TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015"
|
||
|
||
# 架构白名单
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||
SUPPORTED_ARCH_KEYWORDS = ['Qwen', 'Qwen2', 'Qwen3']
|
||
SUPPORTED_MODEL_TYPES = [
|
||
'qwen', 'qwen2', 'qwen2_vl', 'qwen2_5_vl', 'qwen2_audio',
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||
'qwen3', 'qwen3_vl', 'qwen3_5', 'qwen3_5_moe',
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||
]
|
||
SUPPORTED_SPECIAL_ARCHS = ['Eagle3Speculator', 'LlamaForCausalLMEagle3']
|
||
|
||
MODELHUB_API = "https://modelhub.org.cn/api"
|
||
|
||
# 搜索关键词
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||
SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Qwen1.5', 'Qwen-']
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||
|
||
# ============================================================
|
||
# 全局状态
|
||
# ============================================================
|
||
|
||
state = {
|
||
'running': False,
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||
'last_run': None,
|
||
'last_result': None,
|
||
'logs': [],
|
||
}
|
||
state_lock = threading.Lock()
|
||
|
||
|
||
def log(msg: str):
|
||
ts = datetime.now().strftime('%H:%M:%S')
|
||
line = f"[{ts}] {msg}"
|
||
print(line, flush=True)
|
||
with state_lock:
|
||
state['logs'].append(line)
|
||
if len(state['logs']) > 500:
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||
state['logs'] = state['logs'][-300:]
|
||
|
||
|
||
# ============================================================
|
||
# 数据库（内存 SQLite）
|
||
# ============================================================
|
||
|
||
db_conn = None
|
||
|
||
|
||
def init_db():
|
||
global db_conn
|
||
db_conn = sqlite3.connect(':memory:', check_same_thread=False)
|
||
db_conn.execute('''CREATE TABLE IF NOT EXISTS queue (
|
||
model_id TEXT, gpu TEXT, url TEXT, downloads INTEGER,
|
||
params TEXT, category TEXT, score REAL,
|
||
PRIMARY KEY(model_id, gpu)
|
||
)''')
|
||
db_conn.execute('''CREATE TABLE IF NOT EXISTS submitted (
|
||
model_id TEXT, gpu TEXT, task_id TEXT, submitted_at TEXT,
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||
PRIMARY KEY(model_id, gpu)
|
||
)''')
|
||
db_conn.commit()
|
||
|
||
|
||
# ============================================================
|
||
# ModelScope 搜索
|
||
# ============================================================
|
||
|
||
MODELSCOPE_API = "https://modelscope.cn/api/v1"
|
||
DOWNLOAD_MIN = 50
|
||
DOWNLOAD_MAX = 5000
|
||
SEARCH_PAGES = 5 # 每个关键词搜5页（50*5=250个结果）
|
||
|
||
|
||
def search_models(keyword: str) -> list:
|
||
"""从 ModelScope 搜索模型（多页，筛选下载量50-5000的冷门模型）"""
|
||
url = "https://modelscope.cn/openapi/v1/models"
|
||
models = []
|
||
for page in range(1, SEARCH_PAGES + 1):
|
||
params = {
|
||
'search': keyword,
|
||
'page_size': 50,
|
||
'page_number': page,
|
||
'sort': 'downloads',
|
||
}
|
||
try:
|
||
resp = requests.get(url, params=params, timeout=20,
|
||
headers={'User-Agent': 'Mozilla/5.0'})
|
||
data = resp.json()
|
||
if data.get('success'):
|
||
page_models = data.get('data', {}).get('models', [])
|
||
for m in page_models:
|
||
dl = m.get('downloads', 0)
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||
if DOWNLOAD_MIN <= dl <= DOWNLOAD_MAX:
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||
models.append({'id': m.get('id'), 'downloads': dl})
|
||
if len(page_models) < 50:
|
||
break # 最后一页，不继续
|
||
else:
|
||
break
|
||
except Exception as e:
|
||
log(f" [{keyword}] page={page}: {e}")
|
||
break
|
||
time.sleep(0.3)
|
||
log(f" [{keyword}]: {len(models)} 个 (50<={DOWNLOAD_MAX})")
|
||
return models
|
||
|
||
|
||
def check_architecture(model_id: str) -> tuple:
|
||
"""检查模型架构"""
|
||
try:
|
||
cfg_url = f"{MODELSCOPE_API}/models/{model_id}/repo?Revision=master&FilePath=config.json"
|
||
resp = requests.get(cfg_url, timeout=10)
|
||
if resp.status_code == 200:
|
||
cfg = resp.json()
|
||
archs = cfg.get('architectures', [])
|
||
mtype = cfg.get('model_type', '')
|
||
arch_str = str(archs)
|
||
for special in SUPPORTED_SPECIAL_ARCHS:
|
||
if special in arch_str:
|
||
return True, special
|
||
for kw in SUPPORTED_ARCH_KEYWORDS:
|
||
if kw in arch_str:
|
||
return True, kw
|
||
if mtype in SUPPORTED_MODEL_TYPES:
|
||
return True, mtype
|
||
return False, f"arch={archs} type={mtype}"
|
||
mid_upper = model_id.upper()
|
||
if 'QWEN3' in mid_upper or 'QWEN2' in mid_upper:
|
||
return True, "GGUF"
|
||
return False, "no config, not Qwen"
|
||
except Exception as e:
|
||
return True, f"check error: {e}"
|
||
|
||
|
||
def normalize_model_url(model_url: str) -> str:
|
||
"""标准化 URL 格式"""
|
||
if '/models/' in model_url:
|
||
return model_url
|
||
if 'modelscope.cn/' in model_url:
|
||
parts = model_url.split('modelscope.cn/')
|
||
if len(parts) == 2:
|
||
return f"https://www.modelscope.cn/models/{parts[1]}"
|
||
return model_url
|
||
|
||
|
||
# ============================================================
|
||
# 平台 API
|
||
# ============================================================
|
||
|
||
def check_platform_verify(model_id: str) -> dict:
|
||
"""查询全平台验证状态"""
|
||
headers = {'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}
|
||
url = f"{MODELHUB_API}/computility/models/search-by-model-id"
|
||
try:
|
||
resp = requests.get(url, headers=headers, params={'modelId': model_id}, timeout=10)
|
||
data = resp.json()
|
||
if data.get('code') == 0:
|
||
result = data.get('data', {}).get('verifyResult', {})
|
||
return result if isinstance(result, dict) else {}
|
||
except Exception:
|
||
pass
|
||
return {}
|
||
|
||
|
||
def check_my_submitted(model_id: str) -> bool:
|
||
"""检查自己是否已提交"""
|
||
headers = {'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}
|
||
url = f"{MODELHUB_API}/adapt/task/page"
|
||
try:
|
||
resp = requests.get(url, headers=headers, params={
|
||
'current': 1, 'pageSize': 100, 'onlyMine': 'true',
|
||
'gpuType': TARGET_GPU, 'modelId': model_id,
|
||
}, timeout=10)
|
||
data = resp.json()
|
||
if data.get('code') == 0:
|
||
records = data.get('data', {}).get('records', [])
|
||
for r in records:
|
||
if r.get('modelId') == model_id and r.get('gpuType') == gpu:
|
||
status = r.get('status', '')
|
||
if status in ('waiting', 'running', 'success'):
|
||
return True
|
||
except Exception:
|
||
pass
|
||
return False
|
||
|
||
|
||
def check_queue_available() -> int:
|
||
"""查询队列可用位置"""
|
||
headers = {'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}
|
||
url = f"{MODELHUB_API}/adapt/task/page"
|
||
try:
|
||
resp = requests.get(url, headers=headers, params={
|
||
'current': 1, 'pageSize': 1, 'onlyMine': 'true',
|
||
'gpuType': TARGET_GPU, 'status': 'waiting',
|
||
}, timeout=10)
|
||
data = resp.json()
|
||
if data.get('code') == 0:
|
||
waiting = int(data['data'].get('total', 0))
|
||
return max(0, 100 - waiting)
|
||
except Exception:
|
||
pass
|
||
return -1
|
||
|
||
|
||
def cancel_all_tasks():
|
||
"""取消所有 waiting 和 running 状态的任务"""
|
||
headers = {
|
||
'Xc-Token': TARGET_TOKEN,
|
||
'Accept': 'application/json',
|
||
'Content-Type': 'application/json',
|
||
}
|
||
|
||
# 1. 查询所有任务
|
||
all_tasks = []
|
||
page = 1
|
||
while True:
|
||
try:
|
||
resp = requests.get(
|
||
f"{MODELHUB_API}/adapt/task/page",
|
||
headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
|
||
params={'current': page, 'pageSize': 100, 'onlyMine': 'true'},
|
||
timeout=15
|
||
)
|
||
data = resp.json()
|
||
if data.get('code') != 0:
|
||
break
|
||
records = data['data'].get('records', [])
|
||
if not records:
|
||
break
|
||
all_tasks.extend(records)
|
||
log(f" 查询第{page}页: {len(records)} 条, 累计 {len(all_tasks)}/{data['data'].get('total')}")
|
||
if len(all_tasks) >= int(data['data'].get('total', 0)):
|
||
break
|
||
page += 1
|
||
except Exception as e:
|
||
log(f" 查询失败: {e}")
|
||
return
|
||
|
||
# 2. 筛选 waiting/running 状态
|
||
cancellable = [t for t in all_tasks if t.get('status') in ('waiting', 'running')]
|
||
if not cancellable:
|
||
log(f" 没有可取消的任务 (总任务 {len(all_tasks)} 个)")
|
||
return
|
||
|
||
task_ids = [int(t.get('taskId')) for t in cancellable if t.get('taskId')]
|
||
log(f" 总任务 {len(all_tasks)} 个, 可取消 {len(task_ids)} 个 (waiting/running)")
|
||
|
||
# 3. 分批取消（每批最多50个）
|
||
url = f"{MODELHUB_API}/async/task/stop-create-contest-task"
|
||
cancelled = 0
|
||
for i in range(0, len(task_ids), 50):
|
||
batch = task_ids[i:i+50]
|
||
try:
|
||
resp = requests.put(url, headers=headers, json={'taskIds': batch}, timeout=15)
|
||
data = resp.json()
|
||
if data.get('code') == 0:
|
||
cancelled += len(batch)
|
||
log(f" 批次 {i//50+1}: 取消 {len(batch)} 个 ✅")
|
||
else:
|
||
log(f" 批次 {i//50+1}: 失败 code={data.get('code')} msg={data.get('message','')[:80]}")
|
||
except Exception as e:
|
||
log(f" 批次 {i//50+1}: 异常 {e}")
|
||
time.sleep(1)
|
||
|
||
log(f" 取消完成: {cancelled}/{len(task_ids)}")
|
||
|
||
|
||
def build_config_params() -> str:
|
||
"""构建 YAML 配置 - 完全匹配平台自动生成的格式（只支持vllm）"""
|
||
params = {
|
||
'framework': 'vllm',
|
||
'nv_framework': 'vllm',
|
||
'api': 'completion',
|
||
'max_tokens': 1024,
|
||
'temperature': 0.7,
|
||
'repetition_penalty': 1.2,
|
||
'top_p': 0.9,
|
||
'lang': 'zh',
|
||
'max_model_len': 2048,
|
||
'sut_config': {
|
||
'gpu_num': 1,
|
||
'values': {
|
||
'command': [
|
||
'vllm', 'serve', '/model', '--port', '8000',
|
||
'--served-model-name', 'llm', '--max-model-len', '2048',
|
||
'--dtype', 'auto', '--gpu-memory-utilization', '0.95',
|
||
'-tp', '1', '--enforce-eager', '--trust-remote-code',
|
||
]
|
||
}
|
||
},
|
||
'ref_config': {
|
||
'gpu_num': 1,
|
||
'values': {
|
||
'command': [
|
||
'vllm', 'serve', '/model', '--port', '80',
|
||
'--served-model-name', 'llm', '--max-model-len', '4096',
|
||
'--enforce-eager', '--trust-remote-code', '-tp', '1',
|
||
]
|
||
}
|
||
},
|
||
}
|
||
return yaml.dump(params, default_flow_style=False, allow_unicode=True, width=1000)
|
||
|
||
|
||
def submit_model(model_url: str) -> tuple:
|
||
"""提交单个模型"""
|
||
headers = {
|
||
'Xc-Token': TARGET_TOKEN,
|
||
'Accept': 'application/json',
|
||
'Content-Type': 'application/json',
|
||
}
|
||
url = f"{MODELHUB_API}/adapt/task/add"
|
||
payload = {
|
||
'modelAddress': normalize_model_url(model_url),
|
||
'taskType': 'text-generation',
|
||
'targetGpu': TARGET_GPU,
|
||
'framework': 'vllm',
|
||
'strategyId': STRATEGY_ID,
|
||
'configParams': build_config_params(),
|
||
}
|
||
try:
|
||
resp = requests.post(url, headers=headers, json=payload, timeout=30)
|
||
data = resp.json()
|
||
if data.get('code') == 0:
|
||
task_id = data.get('data', {}).get('id')
|
||
return True, task_id, 'success'
|
||
return False, None, data.get('message', 'unknown error')
|
||
except Exception as e:
|
||
return False, None, str(e)
|
||
|
||
|
||
# ============================================================
|
||
# 主流程
|
||
# ============================================================
|
||
|
||
def run_pipeline(submit_limit: int = 30):
|
||
"""完整流程：搜索→筛选→提交（只针对目标GPU）"""
|
||
init_db()
|
||
log("=" * 50)
|
||
log("开始执行流程")
|
||
log(f"目标GPU: {TARGET_GPU}")
|
||
log(f"提交限制: {submit_limit} 个")
|
||
|
||
# 1. 搜索
|
||
log("\n--- 阶段1: 搜索 ModelScope ---")
|
||
seen = set()
|
||
all_models = []
|
||
for kw in SEARCH_KEYWORDS:
|
||
models = search_models(kw)
|
||
for m in models:
|
||
mid = m.get('id', '')
|
||
if mid and mid not in seen:
|
||
seen.add(mid)
|
||
all_models.append({
|
||
'model_id': mid,
|
||
'url': f"https://modelscope.cn/{mid}",
|
||
'downloads': m.get('downloads', 0),
|
||
})
|
||
time.sleep(0.3)
|
||
log(f"搜索完成: {len(seen)} 个唯一模型, {len(all_models)} 个下载量{DOWNLOAD_MIN}-{DOWNLOAD_MAX}")
|
||
|
||
# 2. 格式筛选（排除 GGUF/GPTQ/AWQ）
|
||
log("\n--- 阶段2: 格式筛选 ---")
|
||
hf_models = []
|
||
format_skipped = 0
|
||
SKIP_FORMATS = ['GGUF', 'GPTQ', 'AWQ']
|
||
for m in all_models:
|
||
mid_upper = m['model_id'].upper()
|
||
skip = False
|
||
for fmt in SKIP_FORMATS:
|
||
if fmt in mid_upper:
|
||
format_skipped += 1
|
||
log(f" x {m['model_id']}: {fmt}格式，跳过")
|
||
skip = True
|
||
break
|
||
if not skip:
|
||
hf_models.append(m)
|
||
log(f"格式筛选: {len(hf_models)} 通过, {format_skipped} 跳过 (GGUF/GPTQ/AWQ)")
|
||
|
||
# 3. 架构筛选（排除 Qwen3.5 在 Iluvatar 上不支持）
|
||
log("\n--- 阶段3: 架构筛选 ---")
|
||
arch_passed = []
|
||
arch_rejected = 0
|
||
SKIP_ARCHS = ['qwen3_5', 'Qwen3_5', 'Qwen3.5']
|
||
for m in hf_models:
|
||
ok, reason = check_architecture(m['model_id'])
|
||
if not ok:
|
||
arch_rejected += 1
|
||
log(f" x {m['model_id']}: {reason}")
|
||
continue
|
||
arch_str = str(reason).upper()
|
||
if any(a.upper() in arch_str for a in SKIP_ARCHS):
|
||
arch_rejected += 1
|
||
log(f" x {m['model_id']}: Qwen3.5(Iluvatar不支持)")
|
||
continue
|
||
arch_passed.append(m)
|
||
time.sleep(0.15)
|
||
log(f"架构筛选: {len(arch_passed)} 通过, {arch_rejected} 拒绝")
|
||
|
||
# 4. 筛选并提交（只针对目标GPU）
|
||
log(f"\n--- 阶段4: 筛选并提交 [{TARGET_GPU}] ---")
|
||
|
||
# 检查队列
|
||
available = check_queue_available()
|
||
if available <= 0:
|
||
log(f" 队列满，跳过")
|
||
return 0
|
||
log(f" 队列可用: {available}")
|
||
|
||
# 筛选
|
||
to_submit = []
|
||
for m in arch_passed:
|
||
model_id = m['model_id']
|
||
|
||
# 检查全平台验证状态
|
||
verify = check_platform_verify(model_id)
|
||
if TARGET_GPU in verify:
|
||
continue # 已有记录，跳过
|
||
|
||
# 检查自己是否已提交
|
||
if check_my_submitted(model_id):
|
||
continue
|
||
|
||
to_submit.append(m)
|
||
if len(to_submit) >= min(submit_limit, available):
|
||
break
|
||
time.sleep(0.2)
|
||
|
||
log(f" 待提交: {len(to_submit)}")
|
||
|
||
# 提交
|
||
submitted = 0
|
||
for m in to_submit:
|
||
ok, task_id, msg = submit_model(m['url'])
|
||
if ok:
|
||
submitted += 1
|
||
log(f" ✅ {m['model_id']}")
|
||
db_conn.execute(
|
||
'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?)',
|
||
(m['model_id'], TARGET_GPU, str(task_id), datetime.now().isoformat())
|
||
)
|
||
else:
|
||
log(f" ❌ {m['model_id']}: {msg}")
|
||
time.sleep(0.5)
|
||
|
||
log(f" 提交完成: {submitted}/{len(to_submit)}")
|
||
|
||
db_conn.commit()
|
||
log(f"\n{'=' * 50}")
|
||
log(f"流程完成，共提交 {submitted} 个模型")
|
||
return submitted
|
||
|
||
|
||
# ============================================================
|
||
# HTTP 服务
|
||
# ============================================================
|
||
|
||
class AgentHandler(BaseHTTPRequestHandler):
|
||
def do_GET(self):
|
||
parsed = urlparse(self.path)
|
||
path = parsed.path
|
||
|
||
if path == '/health':
|
||
self._json({'status': 'ok'})
|
||
elif path == '/':
|
||
self._json({
|
||
'name': 'modelhub-submit-agent',
|
||
'strategy_id': STRATEGY_ID,
|
||
'status': 'running' if state['running'] else 'idle',
|
||
'last_run': state['last_run'],
|
||
'last_result': state['last_result'],
|
||
})
|
||
elif path == '/test':
|
||
self._json(self._run_connectivity_test())
|
||
elif path == '/status':
|
||
self._json({
|
||
'running': state['running'],
|
||
'last_run': state['last_run'],
|
||
'last_result': state['last_result'],
|
||
'queue_count': db_conn.execute('SELECT COUNT(*) FROM queue').fetchone()[0] if db_conn else 0,
|
||
'submitted_count': db_conn.execute('SELECT COUNT(*) FROM submitted').fetchone()[0] if db_conn else 0,
|
||
})
|
||
elif path == '/logs':
|
||
lines = int(parse_qs(parsed.query).get('lines', ['50'])[0])
|
||
self._json({'logs': state['logs'][-lines:]})
|
||
else:
|
||
self._json({'error': 'not found'}, 404)
|
||
|
||
def do_POST(self):
|
||
parsed = urlparse(self.path)
|
||
path = parsed.path
|
||
|
||
if path == '/run':
|
||
if state['running']:
|
||
self._json({'error': 'already running'}, 409)
|
||
return
|
||
|
||
# 读取请求体
|
||
content_len = int(self.headers.get('Content-Length', 0))
|
||
body = {}
|
||
if content_len > 0:
|
||
body = json.loads(self.rfile.read(content_len))
|
||
|
||
limit = body.get('limit', 30)
|
||
|
||
self._json({'status': 'started', 'gpu': TARGET_GPU, 'limit': limit})
|
||
|
||
# 后台运行
|
||
def _run():
|
||
try:
|
||
state['running'] = True
|
||
state['last_run'] = datetime.now().isoformat()
|
||
count = run_pipeline(submit_limit=limit)
|
||
state['last_result'] = {'submitted': count, 'success': True}
|
||
except Exception as e:
|
||
log(f"流程异常: {traceback.format_exc()}")
|
||
state['last_result'] = {'error': str(e), 'success': False}
|
||
finally:
|
||
state['running'] = False
|
||
|
||
threading.Thread(target=_run, daemon=True).start()
|
||
else:
|
||
self._json({'error': 'not found'}, 404)
|
||
|
||
def _run_connectivity_test(self) -> dict:
|
||
"""测试各 API 连通性"""
|
||
results = {}
|
||
|
||
# 1. ModelScope 搜索 API
|
||
try:
|
||
resp = requests.get(
|
||
'https://modelscope.cn/openapi/v1/models',
|
||
params={'search': 'qwen', 'page_size': 2, 'sort': 'downloads'},
|
||
timeout=10,
|
||
headers={'User-Agent': 'Mozilla/5.0'}
|
||
)
|
||
results['modelscope_search'] = {
|
||
'status': resp.status_code,
|
||
'ok': resp.status_code == 200,
|
||
'body_preview': resp.text[:200] if resp.status_code == 200 else resp.text[:100],
|
||
}
|
||
except Exception as e:
|
||
results['modelscope_search'] = {'ok': False, 'error': str(e)}
|
||
|
||
# 2. ModelScope config.json API
|
||
try:
|
||
resp = requests.get(
|
||
'https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json',
|
||
timeout=10,
|
||
)
|
||
results['modelscope_config'] = {
|
||
'status': resp.status_code,
|
||
'ok': resp.status_code == 200,
|
||
'body_preview': resp.text[:200] if resp.status_code == 200 else resp.text[:100],
|
||
}
|
||
except Exception as e:
|
||
results['modelscope_config'] = {'ok': False, 'error': str(e)}
|
||
|
||
# 3. ModelHub 查询 API
|
||
try:
|
||
resp = requests.get(
|
||
'https://modelhub.org.cn/api/adapt/task/page',
|
||
headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
|
||
params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
|
||
timeout=10,
|
||
)
|
||
data = resp.json()
|
||
results['modelhub_query'] = {
|
||
'ok': data.get('code') == 0,
|
||
'code': data.get('code'),
|
||
'total': data.get('data', {}).get('total'),
|
||
}
|
||
except Exception as e:
|
||
results['modelhub_query'] = {'ok': False, 'error': str(e)}
|
||
|
||
# 4. ModelHub 提交 API (dry test)
|
||
try:
|
||
resp = requests.post(
|
||
'https://modelhub.org.cn/api/adapt/task/add',
|
||
headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json', 'Content-Type': 'application/json'},
|
||
json={
|
||
'modelAddress': 'https://www.modelscope.cn/models/Qwen/Qwen3-8B',
|
||
'taskType': 'text-generation',
|
||
'targetGpu': TARGET_GPU,
|
||
'framework': 'vllm',
|
||
'strategyId': STRATEGY_ID,
|
||
'configParams': build_config_params(),
|
||
},
|
||
timeout=10,
|
||
)
|
||
data = resp.json()
|
||
results['modelhub_submit'] = {
|
||
'ok': data.get('code') == 0,
|
||
'code': data.get('code'),
|
||
'message': data.get('message', '')[:100],
|
||
}
|
||
except Exception as e:
|
||
results['modelhub_submit'] = {'ok': False, 'error': str(e)}
|
||
|
||
return results
|
||
|
||
def _json(self, body: dict, status: int = 200):
|
||
payload = json.dumps(body, ensure_ascii=False).encode()
|
||
self.send_response(status)
|
||
self.send_header('Content-Type', 'application/json; charset=utf-8')
|
||
self.send_header('Content-Length', str(len(payload)))
|
||
self.end_headers()
|
||
self.wfile.write(payload)
|
||
|
||
def log_message(self, fmt, *args):
|
||
pass # 静默 HTTP 日志
|
||
|
||
|
||
# ============================================================
|
||
# 启动
|
||
# ============================================================
|
||
|
||
shutdown_requested = False
|
||
|
||
|
||
def _handle_signal(signum, _frame):
|
||
global shutdown_requested
|
||
shutdown_requested = True
|
||
log(f"收到信号 {signum}，准备关闭")
|
||
|
||
|
||
def main():
|
||
signal.signal(signal.SIGTERM, _handle_signal)
|
||
signal.signal(signal.SIGINT, _handle_signal)
|
||
|
||
init_db()
|
||
|
||
server = ThreadingHTTPServer((HOST, PORT), AgentHandler)
|
||
server.timeout = 1
|
||
|
||
log(f"智能体启动 | {HOST}:{PORT}")
|
||
log(f"STRATEGY_ID: {STRATEGY_ID}")
|
||
log(f"目标GPU: {TARGET_GPU}")
|
||
|
||
# 启动后自动运行连通性测试
|
||
def _startup_test():
|
||
time.sleep(2)
|
||
log("=" * 50)
|
||
log("连通性测试开始")
|
||
log("=" * 50)
|
||
|
||
# 1. ModelScope 搜索
|
||
try:
|
||
resp = requests.get(
|
||
'https://modelscope.cn/openapi/v1/models',
|
||
params={'search': 'qwen', 'page_size': 2, 'sort': 'downloads'},
|
||
timeout=10, headers={'User-Agent': 'Mozilla/5.0'}
|
||
)
|
||
if resp.status_code == 200:
|
||
data = resp.json()
|
||
models = data.get('data', {}).get('models', [])
|
||
log(f"[ModelScope搜索] ✅ status={resp.status_code} models={len(models)}")
|
||
for m in models[:2]:
|
||
log(f" {m.get('id')} downloads={m.get('downloads')}")
|
||
else:
|
||
log(f"[ModelScope搜索] ❌ status={resp.status_code} body={resp.text[:100]}")
|
||
except Exception as e:
|
||
log(f"[ModelScope搜索] ❌ error={e}")
|
||
|
||
# 2. ModelScope config.json
|
||
try:
|
||
resp = requests.get(
|
||
'https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json',
|
||
timeout=10
|
||
)
|
||
if resp.status_code == 200:
|
||
cfg = resp.json()
|
||
log(f"[ModelScope配置] ✅ arch={cfg.get('architectures')} type={cfg.get('model_type')}")
|
||
else:
|
||
log(f"[ModelScope配置] ❌ status={resp.status_code}")
|
||
except Exception as e:
|
||
log(f"[ModelScope配置] ❌ error={e}")
|
||
|
||
# 3. ModelHub 查询
|
||
try:
|
||
resp = requests.get(
|
||
'https://modelhub.org.cn/api/adapt/task/page',
|
||
headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
|
||
params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
|
||
timeout=10
|
||
)
|
||
data = resp.json()
|
||
if data.get('code') == 0:
|
||
log(f"[ModelHub查询] ✅ total={data['data'].get('total')}")
|
||
else:
|
||
log(f"[ModelHub查询] ❌ code={data.get('code')} msg={data.get('message','')[:80]}")
|
||
except Exception as e:
|
||
log(f"[ModelHub查询] ❌ error={e}")
|
||
|
||
# 4. ModelHub 提交
|
||
try:
|
||
resp = requests.post(
|
||
'https://modelhub.org.cn/api/adapt/task/add',
|
||
headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json', 'Content-Type': 'application/json'},
|
||
json={
|
||
'modelAddress': 'https://www.modelscope.cn/models/Qwen/Qwen3-8B',
|
||
'taskType': 'text-generation', 'targetGpu': TARGET_GPU,
|
||
'framework': 'vllm', 'strategyId': STRATEGY_ID,
|
||
'configParams': build_config_params(),
|
||
}, timeout=10
|
||
)
|
||
data = resp.json()
|
||
log(f"[ModelHub提交] code={data.get('code')} msg={data.get('message','')[:80]}")
|
||
except Exception as e:
|
||
log(f"[ModelHub提交] ❌ error={e}")
|
||
|
||
log("=" * 50)
|
||
log("连通性测试完成")
|
||
log("=" * 50)
|
||
|
||
# 取消所有 waiting/running 任务
|
||
log("\n取消所有等待/运行中任务...")
|
||
try:
|
||
cancel_all_tasks()
|
||
except Exception as e:
|
||
log(f"取消任务异常: {e}")
|
||
|
||
threading.Thread(target=_startup_test, daemon=True).start()
|
||
|
||
while not shutdown_requested:
|
||
server.handle_request()
|
||
|
||
server.server_close()
|
||
log("智能体已关闭")
|
||
|
||
|
||
if __name__ == '__main__':
|
||
main()
|