From 0a4ba2e146dec325f0ebafe0441b56f0e49e1ec9 Mon Sep 17 00:00:00 2001 From: z3st Date: Fri, 24 Jul 2026 18:53:24 +0800 Subject: [PATCH] feat: standalone cancel-all version - startup auto cancels all waiting/running tasks --- main.py | 656 ++++---------------------------------------------------- 1 file changed, 46 insertions(+), 610 deletions(-) diff --git a/main.py b/main.py index 2dd944c..c9503e5 100644 --- a/main.py +++ b/main.py @@ -1,26 +1,18 @@ """ -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 +ModelHub Cancel-All 智能体 +启动后自动取消当前账号所有 waiting/running 状态的验证任务 +用法：推送此版本到平台，选择对应 tag 运行即可 """ import json import os import signal -import sqlite3 -import threading import time -import traceback +import threading from datetime import datetime from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer -from urllib.parse import urlparse, parse_qs import requests -import yaml # ============================================================ # 配置 @@ -28,37 +20,19 @@ import yaml HOST = "0.0.0.0" PORT = 8080 -STRATEGY_ID = os.getenv("STRATEGY_ID", "") -# 目标GPU +# 目标GPU和Token（跟提交版本保持一致） TARGET_GPU = "Iluvatar_bi-150" - -# 账号Token TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015" -# 架构白名单 -SUPPORTED_ARCH_KEYWORDS = ['Qwen', 'Qwen2', 'Qwen3'] -SUPPORTED_MODEL_TYPES = [ - 'qwen', 'qwen2', 'qwen2_vl', 'qwen2_5_vl', 'qwen2_audio', - 'qwen3', 'qwen3_vl', 'qwen3_5', 'qwen3_5_moe', -] -SUPPORTED_SPECIAL_ARCHS = ['Eagle3Speculator', 'LlamaForCausalLMEagle3'] - MODELHUB_API = "https://modelhub.org.cn/api" - -# 搜索关键词 -SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Qwen1.5', 'Qwen-'] +BATCH_SIZE = 50 # 每批取消数量（API上限） # ============================================================ # 全局状态 # ============================================================ -state = { - 'running': False, - 'last_run': None, - 'last_result': None, - 'logs': [], -} +state = {'running': False, 'last_run': None, 'logs': []} state_lock = threading.Lock() @@ -72,168 +46,6 @@ def log(msg: str): 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, - 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) - if DOWNLOAD_MIN <= dl <= DOWNLOAD_MAX: - 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 = { @@ -242,6 +54,10 @@ def cancel_all_tasks(): 'Content-Type': 'application/json', } + log("=" * 50) + log("开始取消所有任务") + log(f"目标GPU: {TARGET_GPU}") + # 1. 查询所有任务 all_tasks = [] page = 1 @@ -250,237 +66,56 @@ def cancel_all_tasks(): resp = requests.get( f"{MODELHUB_API}/adapt/task/page", headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}, - params={'current': page, 'pageSize': 100, 'onlyMine': 'true'}, + params={'current': page, 'pageSize': 100, 'onlyMine': 'true', + 'gpuType': TARGET_GPU}, timeout=15 ) data = resp.json() if data.get('code') != 0: + log(f"查询失败: code={data.get('code')}") 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)): + total = data['data'].get('total', 0) + log(f" 第{page}页: {len(records)} 条, 累计 {len(all_tasks)} / {total}") + if len(all_tasks) >= int(total): break page += 1 except Exception as e: - log(f" 查询失败: {e}") + log(f" 查询异常: {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)") + log("=" * 50) 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)") + log(f" 总任务 {len(all_tasks)} 个, 可取消 {len(task_ids)} 个") - # 3. 分批取消（每批最多50个） + # 3. 分批取消 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] + for i in range(0, len(task_ids), BATCH_SIZE): + batch = task_ids[i:i + BATCH_SIZE] 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 ✅") + log(f" 批次 {i // BATCH_SIZE + 1}: 取消 {len(batch)} 个 OK") else: - log(f" 批次 {i//50+1}: 失败 code={data.get('code')} msg={data.get('message','')[:80]}") + log(f" 批次 {i // BATCH_SIZE + 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}") + log(f" 批次 {i // BATCH_SIZE + 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(f" 取消完成: {cancelled} / {len(task_ids)}") 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 # ============================================================ @@ -489,148 +124,21 @@ def run_pipeline(submit_limit: int = 30): class AgentHandler(BaseHTTPRequestHandler): def do_GET(self): - parsed = urlparse(self.path) - path = parsed.path - - if path == '/health': + if self.path == '/health': self._json({'status': 'ok'}) - elif path == '/': + elif self.path == '/': self._json({ - 'name': 'modelhub-submit-agent', - 'strategy_id': STRATEGY_ID, + 'name': 'modelhub-cancel-all', + 'gpu': TARGET_GPU, 'status': 'running' if state['running'] else 'idle', - 'last_run': state['last_run'], - 'last_result': state['last_result'], + 'last_result': state.get('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]) + elif self.path.startswith('/logs'): + lines = 100 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) @@ -640,7 +148,7 @@ class AgentHandler(BaseHTTPRequestHandler): self.wfile.write(payload) def log_message(self, fmt, *args): - pass # 静默 HTTP 日志 + pass # ============================================================ @@ -660,99 +168,27 @@ 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"Cancel-All 智能体启动 | {HOST}:{PORT}") log(f"目标GPU: {TARGET_GPU}") - # 启动后自动运行连通性测试 - def _startup_test(): + # 启动后自动取消所有任务 + def _auto_cancel(): 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: + state['running'] = True + state['last_run'] = datetime.now().isoformat() cancel_all_tasks() + state['last_result'] = {'success': True} except Exception as e: - log(f"取消任务异常: {e}") + log(f"异常: {e}") + state['last_result'] = {'error': str(e)} + finally: + state['running'] = False - threading.Thread(target=_startup_test, daemon=True).start() + threading.Thread(target=_auto_cancel, daemon=True).start() while not shutdown_requested: server.handle_request()