520 lines
23 KiB
Python
520 lines
23 KiB
Python
"""
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xc_validation_strategy_gguf — 主入口
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GGUF 模型下载 + 验证任务提交流水线（部署框架与 xc_validation_strategy 一致）。
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启动后运行流水线：批量创建 GGUF 模型下载任务（最大并发 8），
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每个模型下载成功后立即提交 hygon / bi150 两个验证任务；
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同时暴露 /health（K8s 探活）和 /status（运行状态）。
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"""
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import json
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import os
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import re
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import signal
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import threading
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from datetime import datetime
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from typing import Set
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import requests
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# ══════════════════════════════════════════════════════════
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# 配置
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# ══════════════════════════════════════════════════════════
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BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn")
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LOGIN_ENDPOINT = "/adminApi/user/login"
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CREATE_DOWNLOAD_TASK_ENDPOINT = "/adminApi/async/task/model-download-task"
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SUBMIT_TEST_TASK_ENDPOINT = "/adminApi/async/task/create-contest-task"
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# 登录账号：启动时优先用账号密码换取新 token（流水线运行时间长，预设 token 可能过期）
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USER_ACCOUNT = "zhoushasha@4paradigm.com"
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USER_PASSWORD = "ganshenme0"
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# 通过 curl -X POST https://modelhub.org.cn/adminApi/user/login 获取后填入（登录失败时的回退）
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AUTH_TOKEN = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ1c2VyQWNjb3VudCI6Inpob3VzaGFzaGEiLCJpZCI6MTQsInVzZXJSb2xlIjoibGVhZGVyYm9hcmQiLCJleHAiOjE3ODQ1NDc1NDYsImlhdCI6MTc4Mzk0Mjc0Nn0.ZcOqcrfI22LPi4mGMnt164nZGhi61ZxtJGYsoO7fZdM"
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CONTEST_API_TOKEN = "ef1ef82f3c9efee413d602345fbe224d"
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HF_TOKEN = "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"
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CONTRIBUTORS = "zhoushasha"
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TASK_TYPE = "text-generation"
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STRATEGY_ID = os.environ.get("STRATEGY_ID", "") # 平台自动注入，无需修改
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MAX_CONCURRENT_DOWNLOADS = 8 # 同时下载的模型数上限
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CHECK_INTERVAL_SECONDS = 10 # 下载状态轮询间隔（秒）
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HTTP_HOST = "0.0.0.0"
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HTTP_PORT = 8080
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# ══════════════════════════════════════════════════════════
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# 模型列表
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# ══════════════════════════════════════════════════════════
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ALL_MODEL_IDS = [
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"mradermacher/Qwen2.5-3B-instruct-argus-v3-GGUF",
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"mradermacher/NeuralsirkrishnaShadow_OgnoExperiment27-GGUF",
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"mradermacher/GREEN-RadLlama2-7b-GGUF",
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"mradermacher/snakmodel-7b-instruct-GGUF",
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"mradermacher/BioMistral-7B-Starling-SLERP-GGUF",
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"mradermacher/Marco-Llama-3.2-3B-GGUF",
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"mradermacher/Qwen2.5-1.5B-Instruct-Open-R1-GRPO-GGUF",
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"mradermacher/Qwen2.5-0.5B-Distill-Fast-GGUF",
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"mradermacher/chomsky_16_bit_model-GGUF",
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"mradermacher/Mistral-7B-DFT-GGUF",
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"mradermacher/mergekit-task_arithmetic-qjeuqjw-GGUF",
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"mradermacher/M7Yamshadowexperiment28_Experiment27Inex12-GGUF",
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"mradermacher/YamshadowStrangemerges_32_Experiment28Inex12-GGUF",
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"mradermacher/MeliodasPercival_01_Experiment29Pastiche-GGUF",
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"mradermacher/Llama-3-6B-v0-GGUF",
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"mradermacher/Excalibur-7b-DPO-GGUF",
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"mradermacher/Llama-2-7b-Indian-Law-GGUF",
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"mradermacher/StarlingHermes-2.5-Mistral-7B-slerp-GGUF",
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"mradermacher/DeepThinker-7B-Sce-v1-GGUF",
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"mradermacher/Alif-Llama-EXP2-GGUF",
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"mradermacher/qwen-2.5-1.5B-Rasa-GGUF",
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"mradermacher/German_RAG-PHI-3.5-MINI-4B-MERGED-HESSIAN-AI-GGUF",
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"mradermacher/MFANN-phigments-slerp-V3.2-GGUF",
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"mradermacher/AdityaGPT-GGUF",
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"mradermacher/Jaja-small-v4-GGUF",
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"mradermacher/Jaja-medium-v1-GGUF",
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"mradermacher/astrollama-2-7b-base_abstract-GGUF",
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"mradermacher/Llasagna-v0.1-GGUF",
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"mradermacher/DeepThinker-v-GGUF",
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"mradermacher/Jaja-small-v3-GGUF",
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"mradermacher/Llama-3.2-1B-FC-v1.2-think-GGUF",
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"mradermacher/Deepseek-Qwen2.5-1.5B-Redistil-GGUF",
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]
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# 去重（保持原有顺序）
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_seen = set()
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_deduplicated = []
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for _mid in ALL_MODEL_IDS:
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if _mid not in _seen:
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_deduplicated.append(_mid)
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_seen.add(_mid)
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ALL_MODEL_IDS = _deduplicated
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print(f"[INFO] 去重后模型数量: {len(ALL_MODEL_IDS)}", flush=True)
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HEADERS = {"Content-Type": "application/json"}
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# ══════════════════════════════════════════════════════════
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# 全局状态（供 /status 展示）
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# ══════════════════════════════════════════════════════════
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_state = {
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"strategy_id": STRATEGY_ID,
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"phase": "starting", # starting | running | done | error
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"total": len(ALL_MODEL_IDS),
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"downloading": [], # 当前正在下载的模型
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"download_success": 0,
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"download_failed": 0,
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"submitted": 0, # 成功提交的验证任务数（hygon + bi150）
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"submit_failed": 0,
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"started_at": None,
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"finished_at": None,
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}
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_shutdown = threading.Event()
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# ══════════════════════════════════════════════════════════
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# HTTP 服务
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# ══════════════════════════════════════════════════════════
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class Handler(BaseHTTPRequestHandler):
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def do_GET(self):
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if self.path == "/health":
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self._json({"status": "ok"})
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elif self.path == "/status":
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self._json(_state)
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else:
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self._json({"error": "not found"}, 404)
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def _json(self, body: dict, code: int = 200):
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payload = json.dumps(body, default=str).encode()
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self.send_response(code)
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self.send_header("Content-Type", "application/json")
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self.send_header("Content-Length", str(len(payload)))
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self.end_headers()
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self.wfile.write(payload)
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def log_message(self, fmt, *args):
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print(f"[http] {self.address_string()} {fmt % args}", flush=True)
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def _run_http():
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server = ThreadingHTTPServer((HTTP_HOST, HTTP_PORT), Handler)
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server.timeout = 1
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print(f"[http] 监听 {HTTP_HOST}:{HTTP_PORT}", flush=True)
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while not _shutdown.is_set():
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server.handle_request()
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server.server_close()
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print("[http] 已关闭", flush=True)
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# ══════════════════════════════════════════════════════════
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# 工具函数：生成模型文件名
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# ══════════════════════════════════════════════════════════
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def get_model_filename(model_id: str) -> str:
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"""
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从 model_id 生成标准 GGUF 模型文件名。
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规则：
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- 移除组织名（/ 前部分）
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- 处理 '_-_' 分割（保留原有逻辑）
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- 移除末尾 '-GGUF'（不区分大小写）
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- 若移除后以 -i1, -i2, ..., -i99 结尾：
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→ 替换为 .i1, .i2, ... 并添加 '-Q4_0.gguf'
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否则：
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→ 直接添加 '.f16.gguf'
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示例：
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'mradermacher/Qwen3-8B-makisu-v2.0.1-i1-GGUF'
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→ 'Qwen3-8B-makisu-v2.0.1.i1-Q4_0.gguf'
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'QuantFactory/Apollo2-9B-GGUF'
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→ 'Apollo2-9B.f16.gguf'
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"""
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# 1. 提取模型名部分（/ 后）
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base_name = model_id.split("/")[-1]
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# 2. 处理 '_-_' 分割
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if '_-_' in base_name:
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base_name = base_name.split('_-_')[-1]
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# 3. 移除末尾的 -GGUF（不区分大小写）
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if base_name.lower().endswith("-gguf"):
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base_name = base_name[:-5]
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# 4. 检查是否以 -i<数字> 结尾（支持 i1～i99 等）
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match = re.search(r'-i(\d+)$', base_name)
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if match:
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number = match.group(1)
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base_name = base_name[:match.start()] + f".i{number}-Q4_0.gguf"
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else:
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base_name = base_name + ".f16.gguf"
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return base_name
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# ══════════════════════════════════════════════════════════
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# 登录获取 token（失败时回退到预设 AUTH_TOKEN）
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# ══════════════════════════════════════════════════════════
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def login() -> str:
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payload = {"userAccount": USER_ACCOUNT, "userPassword": USER_PASSWORD}
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print("[login] 正在登录...", flush=True)
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try:
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resp = requests.post(BASE_URL + LOGIN_ENDPOINT, headers=HEADERS, json=payload, timeout=15)
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data = resp.json()
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if resp.status_code == 200 and data.get("code") == 0:
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print("[login] 登录成功", flush=True)
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return data["data"]["token"]
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print(f"[login] 登录失败: {data.get('message')}，回退使用预设 Token", flush=True)
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except Exception as e:
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print(f"[login] 登录异常: {e}，回退使用预设 Token", flush=True)
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return AUTH_TOKEN
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# ══════════════════════════════════════════════════════════
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# 创建单个模型的下载任务
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# ══════════════════════════════════════════════════════════
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def create_download_task(token: str, model_id: str) -> bool:
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filename = get_model_filename(model_id)
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auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
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payload = {
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"allowPatterns": [filename],
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"hfToken": HF_TOKEN,
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"modelId": model_id,
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"source": "HUGGING_FACE",
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"stillDownloadAlreadySuccessDownloadedModel": False
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}
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print(f"📥 创建下载任务: {model_id} → {filename}", flush=True)
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try:
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resp = requests.post(BASE_URL + CREATE_DOWNLOAD_TASK_ENDPOINT, headers=auth_headers, json=payload, timeout=15)
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if resp.status_code == 200:
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data = resp.json()
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if data.get("code") == 0:
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print(f"✅ 下载任务已提交: {model_id}", flush=True)
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return True
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else:
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print(f"⚠️ 下载任务业务失败 ({model_id}): {data.get('message')}", flush=True)
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return False
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else:
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print(f"❌ HTTP 错误 ({model_id}): {resp.status_code} - {resp.text}", flush=True)
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return False
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except Exception as e:
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print(f"💥 创建下载任务异常 ({model_id}): {e}", flush=True)
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return False
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# ══════════════════════════════════════════════════════════
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# 查询单个模型的最新下载任务状态
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# ══════════════════════════════════════════════════════════
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def check_model_status(token: str, model_id: str) -> str:
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"""
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返回状态: 'WAITING', 'RUNNING', 'SUCCESS', 'FAILED', 'UNKNOWN'
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"""
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url = BASE_URL + CREATE_DOWNLOAD_TASK_ENDPOINT
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auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
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params = {"modelId": model_id, "current": 1, "pageSize": 1}
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try:
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resp = requests.get(url, headers=auth_headers, params=params, timeout=10)
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if resp.status_code != 200:
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return "UNKNOWN"
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data = resp.json()
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if data.get("code") != 0:
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return "UNKNOWN"
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records = data.get("data", {}).get("records", [])
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if not records:
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return "UNKNOWN"
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status = records[0].get("status", "UNKNOWN").upper()
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return status
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except Exception as e:
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print(f"⚠️ 查询状态异常 ({model_id}): {e}", flush=True)
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return "UNKNOWN"
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# ══════════════════════════════════════════════════════════
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# 提交单个模型的测试任务 hygon
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# ══════════════════════════════════════════════════════════
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def submit_test_task(token: str, model_id: str) -> bool:
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auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
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model_filename = get_model_filename(model_id)
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gpu_type = "hygon_k100-ai"
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config_content = f"""docker_image: git.modelhub.org.cn:9443/enginex-hygon/hygon-llama.cpp:b7516
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nv_docker_image: harbor-contest.4pd.io/luxinlong02/llama-cpp:b7003-cuda-full-12.3
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framework: llamacpp
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storage: gpfs
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modelhub_options:
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srcRelativePath: leaderboard/modelHubXC/{model_id}
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mountPoint: /model
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api: completion
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temperature: 0
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repetition_penalty: 1.1
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top_p: 0.9
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max_model_len: 4096
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sut_config:
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gpu_num: 1
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values:
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command: ['/app/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20','--n-gpu-layers', '999', '--prio', '3', '--min_p', '0.01', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off']
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ref_config:
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gpu_num: 1
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values:
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command: ['/workspace/llama.cpp/build/bin/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20', '--n-gpu-layers', '999', '--prio', '3', '--min_p', '0.01', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off']
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"""
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task_data = {
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"contestApiToken": CONTEST_API_TOKEN,
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"contributors": CONTRIBUTORS,
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"gpuTypes": [gpu_type],
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"taskType": TASK_TYPE,
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"modelId": model_id,
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"strategyId": STRATEGY_ID, # 平台要求
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"submissionConfig": [{
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"config": config_content,
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"gpuType": gpu_type,
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"taskType": TASK_TYPE
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}]
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}
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print(f"📤 提交测试任务 (hygon): {model_id}", flush=True)
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try:
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resp = requests.post(BASE_URL + SUBMIT_TEST_TASK_ENDPOINT, json=task_data, headers=auth_headers, timeout=15)
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if resp.status_code == 200:
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result = resp.json()
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if result.get("code") == 0:
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task_id = result.get("data", {}).get("taskId")
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print(f"✅ 测试任务提交成功! Task ID: {task_id}", flush=True)
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return True
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else:
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print(f"❌ 测试任务业务错误: {result.get('message')}", flush=True)
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return False
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else:
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print(f"❌ 测试任务 HTTP 错误: {resp.status_code} - {resp.text}", flush=True)
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return False
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except Exception as e:
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print(f"💥 提交测试任务异常 ({model_id}): {e}", flush=True)
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return False
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# ══════════════════════════════════════════════════════════
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# 提交单个模型的测试任务 bi150
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# ══════════════════════════════════════════════════════════
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def submit_test_task_bi150(token: str, model_id: str) -> bool:
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auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
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model_filename = get_model_filename(model_id)
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gpu_type = "Iluvatar_bi-150"
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config_content = f"""docker_image: git.modelhub.org.cn:9443/enginex-iluvatar/iluvatar-llama.cpp:b7516-bi150
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nv_docker_image: harbor-contest.4pd.io/luxinlong02/llama-cpp:b7003-cuda-full-12.3
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framework: llamacpp
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storage: gpfs
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modelhub_options:
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srcRelativePath: leaderboard/modelHubXC/{model_id}
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mountPoint: /model
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max_model_len: 4096
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sut_config:
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gpu_num: 1
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values:
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command: ['/app/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20','--n-gpu-layers','128', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off', '--no-mmap', '--sync-to-temp']
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ref_config:
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gpu_num: 1
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values:
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command: ['/workspace/llama.cpp/build/bin/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20','--n-gpu-layers','128', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off']
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"""
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task_data = {
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"contestApiToken": CONTEST_API_TOKEN,
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"contributors": CONTRIBUTORS,
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"gpuTypes": [gpu_type],
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"taskType": TASK_TYPE,
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"modelId": model_id,
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"strategyId": STRATEGY_ID, # 平台要求
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"submissionConfig": [{
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"config": config_content,
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"gpuType": gpu_type,
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"taskType": TASK_TYPE
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}]
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}
|
||
print(f"📤 提交测试任务 (bi150): {model_id}", flush=True)
|
||
try:
|
||
resp = requests.post(BASE_URL + SUBMIT_TEST_TASK_ENDPOINT, json=task_data, headers=auth_headers, timeout=15)
|
||
if resp.status_code == 200:
|
||
result = resp.json()
|
||
if result.get("code") == 0:
|
||
task_id = result.get("data", {}).get("taskId")
|
||
print(f"✅ 测试任务提交成功! Task ID: {task_id}", flush=True)
|
||
return True
|
||
else:
|
||
print(f"❌ 测试任务业务错误: {result.get('message')}", flush=True)
|
||
return False
|
||
else:
|
||
print(f"❌ 测试任务 HTTP 错误: {resp.status_code} - {resp.text}", flush=True)
|
||
return False
|
||
except Exception as e:
|
||
print(f"💥 提交测试任务异常 ({model_id}): {e}", flush=True)
|
||
return False
|
||
|
||
# ══════════════════════════════════════════════════════════
|
||
# 业务逻辑：动态流水线（下载 → 提交验证任务）
|
||
# ══════════════════════════════════════════════════════════
|
||
def _run_worker():
|
||
_state["started_at"] = datetime.utcnow().isoformat()
|
||
_state["phase"] = "running"
|
||
|
||
try:
|
||
token = login()
|
||
except Exception as e:
|
||
print(f"[worker] 登录失败: {e}", flush=True)
|
||
_state["phase"] = "error"
|
||
return
|
||
|
||
pending_models = list(ALL_MODEL_IDS) # 尚未开始下载的模型
|
||
active_models: Set[str] = set() # 当前正在下载的模型
|
||
completed_results = {} # model_id -> status
|
||
|
||
print(f"🚀 总共 {len(pending_models)} 个模型待下载。最大并发数: {MAX_CONCURRENT_DOWNLOADS}\n", flush=True)
|
||
|
||
while (pending_models or active_models) and not _shutdown.is_set():
|
||
# 1. 检查活跃任务状态
|
||
for model_id in list(active_models):
|
||
if _shutdown.is_set():
|
||
break
|
||
status = check_model_status(token, model_id)
|
||
if status in ("SUCCESS", "FAILED"):
|
||
completed_results[model_id] = status
|
||
active_models.remove(model_id)
|
||
print(f"⏹️ {model_id} 完成，状态: {status}", flush=True)
|
||
if status == "SUCCESS":
|
||
_state["download_success"] += 1
|
||
# 下载成功后立即提交该模型的验证任务
|
||
if submit_test_task(token, model_id):
|
||
_state["submitted"] += 1
|
||
print(f"🧪 已为 {model_id} 提交 hygon 验证任务", flush=True)
|
||
else:
|
||
_state["submit_failed"] += 1
|
||
print(f"⚠️ {model_id} hygon 验证任务提交失败", flush=True)
|
||
|
||
if submit_test_task_bi150(token, model_id):
|
||
_state["submitted"] += 1
|
||
print(f"🧪 已为 {model_id} 提交 bi150 验证任务", flush=True)
|
||
else:
|
||
_state["submit_failed"] += 1
|
||
print(f"⚠️ {model_id} bi150 验证任务提交失败", flush=True)
|
||
else:
|
||
_state["download_failed"] += 1
|
||
|
||
# 2. 补充新任务（最多补到 MAX_CONCURRENT_DOWNLOADS 个）
|
||
while len(active_models) < MAX_CONCURRENT_DOWNLOADS and pending_models and not _shutdown.is_set():
|
||
next_model = pending_models.pop(0)
|
||
if create_download_task(token, next_model):
|
||
active_models.add(next_model)
|
||
print(f"▶️ 启动下载: {next_model} (当前活跃: {len(active_models)})", flush=True)
|
||
else:
|
||
# 创建失败也视为完成（避免卡住）
|
||
completed_results[next_model] = "CREATE_FAILED"
|
||
_state["download_failed"] += 1
|
||
print(f"❌ 创建失败: {next_model}", flush=True)
|
||
|
||
_state["downloading"] = sorted(active_models)
|
||
|
||
# 3. 稍作等待，避免频繁查询（可被 shutdown 信号打断）
|
||
if active_models or pending_models:
|
||
_shutdown.wait(CHECK_INTERVAL_SECONDS)
|
||
|
||
print("\n✅ 所有模型处理完毕！\n", flush=True)
|
||
|
||
# 4. 收集所有成功下载的模型ID并写入结果文件
|
||
success_models = [
|
||
mid for mid, status in completed_results.items()
|
||
if status == "SUCCESS"
|
||
]
|
||
try:
|
||
with open("downloaded_success_models.txt", "w", encoding="utf-8") as f:
|
||
for mid in success_models:
|
||
f.write(f"{mid}\n")
|
||
except Exception:
|
||
pass
|
||
|
||
print("🎉 下载成功的模型ID列表：", flush=True)
|
||
print("[", flush=True)
|
||
for mid in success_models:
|
||
print(f' "{mid}",', flush=True)
|
||
print("]", flush=True)
|
||
|
||
_state["downloading"] = []
|
||
_state["finished_at"] = datetime.utcnow().isoformat()
|
||
_state["phase"] = "done"
|
||
print(
|
||
f"[worker] 完成 download_success={_state['download_success']} "
|
||
f"download_failed={_state['download_failed']} "
|
||
f"submitted={_state['submitted']} submit_failed={_state['submit_failed']}",
|
||
flush=True,
|
||
)
|
||
# 流水线完成后继续保持进程存活，等待平台停止
|
||
|
||
# ══════════════════════════════════════════════════════════
|
||
# 入口
|
||
# ══════════════════════════════════════════════════════════
|
||
def _handle_signal(signum, _frame):
|
||
print(f"[main] 收到信号 {signum}，正在关闭...", flush=True)
|
||
_shutdown.set()
|
||
|
||
|
||
def main():
|
||
signal.signal(signal.SIGTERM, _handle_signal)
|
||
signal.signal(signal.SIGINT, _handle_signal)
|
||
|
||
# HTTP 服务线程
|
||
http_thread = threading.Thread(target=_run_http, daemon=False)
|
||
http_thread.start()
|
||
|
||
# 流水线线程
|
||
worker_thread = threading.Thread(target=_run_worker, daemon=True)
|
||
worker_thread.start()
|
||
|
||
# 主线程等待 shutdown
|
||
_shutdown.wait()
|
||
print("[main] 等待 HTTP 服务关闭...", flush=True)
|
||
http_thread.join(timeout=5)
|
||
print("[main] 退出", flush=True)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|