From 12616c38167e001f4c00387fddeaa016d2282620 Mon Sep 17 00:00:00 2001 From: z3st Date: Fri, 24 Jul 2026 18:56:18 +0800 Subject: [PATCH] restore submit version from v2.1.0 --- main.py | 669 +++++++++++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 588 insertions(+), 81 deletions(-) diff --git a/main.py b/main.py index c9503e5..bee1e13 100644 --- a/main.py +++ b/main.py @@ -1,18 +1,26 @@ """ -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 +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 time +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 @@ -20,19 +28,37 @@ import requests HOST = "0.0.0.0" PORT = 8080 +STRATEGY_ID = os.getenv("STRATEGY_ID", "") -# 目标GPU和Token（跟提交版本保持一致） +# 目标GPU 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" -BATCH_SIZE = 50 # 每批取消数量（API上限） + +# 搜索关键词 +SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Qwen1.5', 'Qwen-'] # ============================================================ # 全局状态 # ============================================================ -state = {'running': False, 'last_run': None, 'logs': []} +state = { + 'running': False, + 'last_run': None, + 'last_result': None, + 'logs': [], +} state_lock = threading.Lock() @@ -46,76 +72,352 @@ def log(msg: str): state['logs'] = state['logs'][-300:] -def cancel_all_tasks(): - """取消所有 waiting 和 running 状态的任务""" +# ============================================================ +# 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 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("开始取消所有任务") + log("开始执行流程") log(f"目标GPU: {TARGET_GPU}") + log(f"提交限制: {submit_limit} 个") - # 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', - 'gpuType': TARGET_GPU}, - timeout=15 + # 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()) ) - 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) - 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" 查询异常: {e}") - return + else: + log(f" ❌ {m['model_id']}: {msg}") + time.sleep(0.5) - # 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 + log(f" 提交完成: {submitted}/{len(to_submit)}") - 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") - - # 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), 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 // BATCH_SIZE + 1}: 取消 {len(batch)} 个 OK") - else: - 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 // BATCH_SIZE + 1}: 异常 {e}") - time.sleep(1) - - log(f" 取消完成: {cancelled} / {len(task_ids)}") - log("=" * 50) + db_conn.commit() + log(f"\n{'=' * 50}") + log(f"流程完成，共提交 {submitted} 个模型") + return submitted # ============================================================ @@ -124,21 +426,148 @@ def cancel_all_tasks(): class AgentHandler(BaseHTTPRequestHandler): def do_GET(self): - if self.path == '/health': + parsed = urlparse(self.path) + path = parsed.path + + if path == '/health': self._json({'status': 'ok'}) - elif self.path == '/': + elif path == '/': self._json({ - 'name': 'modelhub-cancel-all', - 'gpu': TARGET_GPU, + 'name': 'modelhub-submit-agent', + 'strategy_id': STRATEGY_ID, 'status': 'running' if state['running'] else 'idle', - 'last_result': state.get('last_result'), + 'last_run': state['last_run'], + 'last_result': state['last_result'], }) - elif self.path.startswith('/logs'): - lines = 100 + 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) @@ -148,7 +577,7 @@ class AgentHandler(BaseHTTPRequestHandler): self.wfile.write(payload) def log_message(self, fmt, *args): - pass + pass # 静默 HTTP 日志 # ============================================================ @@ -168,27 +597,105 @@ 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"Cancel-All 智能体启动 | {HOST}:{PORT}") + log(f"智能体启动 | {HOST}:{PORT}") + log(f"STRATEGY_ID: {STRATEGY_ID}") log(f"目标GPU: {TARGET_GPU}") - # 启动后自动取消所有任务 - def _auto_cancel(): + # 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) + + # 开始正式提交流程 + log("\n自动触发提交流程...") try: state['running'] = True state['last_run'] = datetime.now().isoformat() - cancel_all_tasks() - state['last_result'] = {'success': True} + count = run_pipeline(submit_limit=30) + state['last_result'] = {'submitted': count, 'success': True} except Exception as e: - log(f"异常: {e}") - state['last_result'] = {'error': str(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=_auto_cancel, daemon=True).start() + threading.Thread(target=_startup_test, daemon=True).start() while not shutdown_requested: server.handle_request()