Replace main.py with vLLM adapt-task batch submitter (fanyi account)
Port logic from submit_validation_only_ppu_zhoukaile.py into the strategy-deployable framework (health/status HTTP server, STRATEGY_ID env, SIGTERM handling). Uses /api/adapt/task/add with xc-Token auth. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
17
README.md
17
README.md
@@ -1,24 +1,23 @@
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# xc_validation_strategy_gguf
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# xc_validation_strategy_vllm_submit
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GGUF 模型下载 + 验证任务提交流水线策略服务：批量创建 GGUF 模型下载任务（最大并发 8），
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批量向 ModelHub XC 平台提交 vLLM 模型适配任务的策略服务（fanyi 账号），
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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，之后保持 HTTP 服务存活供平台探活。
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之后保持 HTTP 服务存活供平台探活。
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## 功能
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## 功能
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- 自动登录 ModelHub 获取 Token（失败时回退到预设 Token）
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- 通过 `/api/adapt/task/add` 接口（xc-Token 认证）批量提交模型适配任务
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- 按流水线批量创建 GGUF 模型下载任务（HuggingFace 源，最大并发 8）
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- vLLM 框架，ppu_zw_810e GPU
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- 每个模型下载成功后，立即提交 hygon_k100-ai 与 Iluvatar_bi-150 两个验证任务（llamacpp 框架）
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- 提交成功的模型写入 `submitted_adapt_tasks.txt`
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- 下载成功的模型 ID 写入 `downloaded_success_models.txt`
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- 暴露 `/health` 和 `/status` 接口满足平台运行时契约
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- 暴露 `/health` 和 `/status` 接口满足平台运行时契约
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## 项目结构
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## 项目结构
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```
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```
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.
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.
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├── main.py # 主入口：HTTP 服务 + 下载/提交流水线
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├── main.py # 主入口：HTTP 服务 + 提交逻辑
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├── Dockerfile # 平台镜像构建配置
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├── Dockerfile # 平台镜像构建配置
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├── requirements.txt # Python 依赖
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├── requirements.txt # Python 依赖
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└── downloaded_success_models.txt # 运行后自动生成，记录下载成功的模型
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└── submitted_adapt_tasks.txt # 运行后自动生成，记录提交结果
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```
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```
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## 平台契约说明
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## 平台契约说明
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569
main.py
569
main.py
@@ -1,47 +1,41 @@
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"""
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"""
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xc_validation_strategy_gguf — 主入口
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xc_validation_strategy_vllm_submit — 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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启动后通过 /api/adapt/task/add 接口（xc-Token 认证）批量提交
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vLLM 模型适配任务（ppu_zw_810e），之后保持 HTTP 服务存活。
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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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同时暴露 /health（K8s 探活）和 /status（运行状态）。
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部署框架与 xc_validation_strategy 一致。
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"""
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"""
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import json
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import json
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import os
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import os
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import re
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import signal
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import signal
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import threading
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import threading
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from datetime import datetime
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from datetime import datetime
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from typing import Set
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from typing import List
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import requests
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import requests
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# ══════════════════════════════════════════════════════════
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# ══════════════════════════════════════════════════════════
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# 配置
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# 配置
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# ══════════════════════════════════════════════════════════
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# ══════════════════════════════════════════════════════════
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BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn")
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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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ADD_TASK_ENDPOINT = "/api/adapt/task/add"
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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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# fanyi 账号的 xc-Token（该接口使用 xc-Token 认证，无需登录）
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USER_ACCOUNT = "zhoushasha@4paradigm.com"
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USER_ACCOUNT = "fanyi"
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USER_PASSWORD = "ganshenme0"
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XC_TOKEN = "f2d501c9ae6543a589cd6cb789108c41"
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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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GPU_TYPE = "ppu_zw_810e"
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AUTH_TOKEN = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ1c2VyQWNjb3VudCI6Inpob3VzaGFzaGEiLCJpZCI6MTQsInVzZXJSb2xlIjoibGVhZGVyYm9hcmQiLCJleHAiOjE3ODQ1NDc1NDYsImlhdCI6MTc4Mzk0Mjc0Nn0.ZcOqcrfI22LPi4mGMnt164nZGhi61ZxtJGYsoO7fZdM"
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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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CONTEST_API_TOKEN = "ef1ef82f3c9efee413d602345fbe224d"
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HEADERS = {
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HF_TOKEN = "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"
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"Content-Type": "application/json",
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CONTRIBUTORS = "zhoushasha"
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"xc-Token": XC_TOKEN,
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TASK_TYPE = "text-generation"
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}
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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_HOST = "0.0.0.0"
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HTTP_PORT = 8080
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HTTP_PORT = 8080
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@@ -51,75 +45,83 @@ HTTP_PORT = 8080
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# ══════════════════════════════════════════════════════════
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# ══════════════════════════════════════════════════════════
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ALL_MODEL_IDS = [
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ALL_MODEL_IDS = [
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|
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||||||
|
"Hyeji0101/qwen2_5_1_5b_demo",
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|
"GenueAI/geode-onyx",
|
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"mradermacher/Qwen2.5-3B-instruct-argus-v3-GGUF",
|
"GM77/qwen3-4b-verilog-grpo",
|
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"mradermacher/NeuralsirkrishnaShadow_OgnoExperiment27-GGUF",
|
"ChuGyouk/F_R13_T2",
|
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"mradermacher/GREEN-RadLlama2-7b-GGUF",
|
"ChuGyouk/R17",
|
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"mradermacher/snakmodel-7b-instruct-GGUF",
|
"Ingingdo/bit-0.5b-final-logic",
|
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"mradermacher/BioMistral-7B-Starling-SLERP-GGUF",
|
"beomi/Llama-3-Open-Ko-8B",
|
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"mradermacher/Marco-Llama-3.2-3B-GGUF",
|
"Fiscus/trinitite_safe_rl_base_model",
|
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"mradermacher/Qwen2.5-1.5B-Instruct-Open-R1-GRPO-GGUF",
|
"ChuGyouk/F_R12_T3",
|
||||||
"mradermacher/Qwen2.5-0.5B-Distill-Fast-GGUF",
|
"ChuGyouk/F_R12_T2",
|
||||||
"mradermacher/chomsky_16_bit_model-GGUF",
|
"xw1234gan/cnk12_Main_fixed_SFTanchor_3B_step_9",
|
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"mradermacher/Mistral-7B-DFT-GGUF",
|
"xw1234gan/cnk12_Main_fixed_SFTanchor_3B_step_10",
|
||||||
"mradermacher/mergekit-task_arithmetic-qjeuqjw-GGUF",
|
"xw1234gan/cnk12_Main_fixed_BaseAnchor_3B_step_1",
|
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"mradermacher/M7Yamshadowexperiment28_Experiment27Inex12-GGUF",
|
"kmseong/llama3_2_3b-instruct-math-safedelta-scale0.99",
|
||||||
"mradermacher/YamshadowStrangemerges_32_Experiment28Inex12-GGUF",
|
"opencompass/anah-v2",
|
||||||
"mradermacher/MeliodasPercival_01_Experiment29Pastiche-GGUF",
|
"ChuGyouk/R14",
|
||||||
"mradermacher/Llama-3-6B-v0-GGUF",
|
"trishajean/qwen-math-cebuano-1.5b-merged",
|
||||||
"mradermacher/Excalibur-7b-DPO-GGUF",
|
"GyanAISystems/Gyan-AI-G1-Official",
|
||||||
"mradermacher/Llama-2-7b-Indian-Law-GGUF",
|
"Divij/Qwen2.5-3B-Instruct-sft-without-thoughts",
|
||||||
"mradermacher/StarlingHermes-2.5-Mistral-7B-slerp-GGUF",
|
"Divij/Qwen2.5-3B-Instruct-sft-with-thoughts",
|
||||||
"mradermacher/DeepThinker-7B-Sce-v1-GGUF",
|
"ChuGyouk/R5_1",
|
||||||
"mradermacher/Alif-Llama-EXP2-GGUF",
|
"ChuGyouk/R18_1",
|
||||||
"mradermacher/qwen-2.5-1.5B-Rasa-GGUF",
|
"ChuGyouk/R19_1",
|
||||||
"mradermacher/German_RAG-PHI-3.5-MINI-4B-MERGED-HESSIAN-AI-GGUF",
|
"ChuGyouk/R12",
|
||||||
"mradermacher/MFANN-phigments-slerp-V3.2-GGUF",
|
"ChuGyouk/F_R11_T4",
|
||||||
"mradermacher/AdityaGPT-GGUF",
|
"ChuGyouk/F_R12",
|
||||||
"mradermacher/Jaja-small-v4-GGUF",
|
"ChuGyouk/F_R11_T2",
|
||||||
"mradermacher/Jaja-medium-v1-GGUF",
|
"ChuGyouk/F_R11_T3",
|
||||||
"mradermacher/astrollama-2-7b-base_abstract-GGUF",
|
"ChuGyouk/F_R13_1_T1",
|
||||||
"mradermacher/Llasagna-v0.1-GGUF",
|
"ChuGyouk/F_R12_T4",
|
||||||
"mradermacher/DeepThinker-v-GGUF",
|
"automerger/T3qm7xNeuralsirkrishna-7B",
|
||||||
"mradermacher/Jaja-small-v3-GGUF",
|
"Ford91/clifford-ai-v2",
|
||||||
"mradermacher/Llama-3.2-1B-FC-v1.2-think-GGUF",
|
"ChuGyouk/R16_1",
|
||||||
"mradermacher/Deepseek-Qwen2.5-1.5B-Redistil-GGUF",
|
"ChuGyouk/R15_1",
|
||||||
|
"nkatara/gita-text-generation-gpt2",
|
||||||
|
"HINT-lab/Qwen2.5-7B-Instruct-Self-Calibration",
|
||||||
|
"thirdeyeai/Qwen2.5-1.5B-Instruct-uncensored",
|
||||||
|
"karaselerm/qwen2.5-1.5b-instruct-ru-abliterated-hw6",
|
||||||
|
"xw1234gan/cnk12_Main_fixed_BaseAnchor_3B_step_2",
|
||||||
|
"ontocord/wide_3b_sft_stage1.1-ss1-with_intr_math.no_issue",
|
||||||
|
"mncai/Foundation_Law_epoch4",
|
||||||
|
"gauri0508/med-record-audit-qwen2.5-3b-grpo",
|
||||||
|
"unsloth/Phi-4-mini-instruct",
|
||||||
|
"E-motionAssistant/qwen-2.5-3b-tamil-therapy-merged",
|
||||||
|
"EscapeJeju/qwen2_5_1_5b_demo",
|
||||||
|
"AgPerry/Qwen3-8B-fim-v2v3pt-swe-lego-posttrain",
|
||||||
|
"ChuGyouk/F_R11",
|
||||||
|
"ChuGyouk/F_R11_1_T1",
|
||||||
|
"LorenaYannnnn/general_reward-Qwen3-0.6B-OURS_self-seed_1",
|
||||||
|
"Vortex5/Crimson-Constellation-12B",
|
||||||
|
"cloudyu/mistral_11B_instruct_v0.1",
|
||||||
|
"pkupie/Qwen2.5-3B-ug-cpt",
|
||||||
|
"iproskurina/qwen-hf-fewshot-iter-np-iter3",
|
||||||
|
"ontocord/wide_3b_sft_stage1.2-ss1-expert_wiki",
|
||||||
|
"kmseong/llama3_2_3b-instruct-math-safedelta-scale2",
|
||||||
|
"Thrillcrazyer/Qwen-2.5-1.5B_TAC_Teacher_Qwen32B",
|
||||||
|
"nyu-dice-lab/VeriThoughts-Reasoning-7B",
|
||||||
|
"ontocord/wide_3b",
|
||||||
|
"silvercoder67/Mistral-7b-instruct-v0.2-summ-sft-e2m",
|
||||||
|
"lihaoxin2020/qwen3-4b-sft-gpt54-ep2-instance-rubric-gpt54-step200",
|
||||||
|
"lihaoxin2020/qwen3-4b-sft-gpt54-ep2-instance-rubric-gpt54-step150",
|
||||||
|
"lihaoxin2020/qwen3-4b-sft-gpt54-ep2-evolving-rubric-gem3-flash-step150",
|
||||||
|
"Guilherme34/Firefly-V3",
|
||||||
|
|
||||||
]
|
]
|
||||||
|
|
||||||
|
|
||||||
# 去重（保持原有顺序）
|
|
||||||
_seen = set()
|
|
||||||
_deduplicated = []
|
|
||||||
for _mid in ALL_MODEL_IDS:
|
|
||||||
if _mid not in _seen:
|
|
||||||
_deduplicated.append(_mid)
|
|
||||||
_seen.add(_mid)
|
|
||||||
ALL_MODEL_IDS = _deduplicated
|
|
||||||
print(f"[INFO] 去重后模型数量: {len(ALL_MODEL_IDS)}", flush=True)
|
|
||||||
|
|
||||||
HEADERS = {"Content-Type": "application/json"}
|
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════
|
||||||
# 全局状态（供 /status 展示）
|
# 全局状态（供 /status 展示）
|
||||||
# ══════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════
|
||||||
_state = {
|
_state = {
|
||||||
"strategy_id": STRATEGY_ID,
|
"strategy_id": STRATEGY_ID,
|
||||||
"phase": "starting", # starting | running | done | error
|
"phase": "starting", # starting | submitting | done | error
|
||||||
"total": len(ALL_MODEL_IDS),
|
"total": len(ALL_MODEL_IDS),
|
||||||
"downloading": [], # 当前正在下载的模型
|
"submitted": 0,
|
||||||
"download_success": 0,
|
"failed": 0,
|
||||||
"download_failed": 0,
|
"started_at": None,
|
||||||
"submitted": 0, # 成功提交的验证任务数（hygon + bi150）
|
"finished_at": None,
|
||||||
"submit_failed": 0,
|
|
||||||
"started_at": None,
|
|
||||||
"finished_at": None,
|
|
||||||
}
|
}
|
||||||
_shutdown = threading.Event()
|
_shutdown = threading.Event()
|
||||||
|
|
||||||
@@ -157,336 +159,119 @@ def _run_http():
|
|||||||
print("[http] 已关闭", flush=True)
|
print("[http] 已关闭", flush=True)
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════
|
||||||
# 工具函数：生成模型文件名
|
# 业务逻辑
|
||||||
# ══════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════
|
||||||
def get_model_filename(model_id: str) -> str:
|
def submit_task(model_id: str) -> bool:
|
||||||
"""
|
config_content = f"""
|
||||||
从 model_id 生成标准 GGUF 模型文件名。
|
gpu_type: ppu_zw_810e
|
||||||
|
framework: vllm
|
||||||
|
docker_image: harbor.4pd.io/hardcore-tech/asllm:1.10.1-pytorch2.10.0-ubuntu24.04-sail2.1.0-cuda13.0-sglang0.5.10-vllm0.19.0-py312
|
||||||
|
nv_docker_image: harbor-contest.4pd.io/sunruoxi/vllm-openai-fix-tokenizer:v0.11.0
|
||||||
|
|
||||||
规则：
|
sut_config:
|
||||||
- 移除组织名（/ 前部分）
|
values:
|
||||||
- 处理 '_-_' 分割（保留原有逻辑）
|
gpu_num: 1
|
||||||
- 移除末尾 '-GGUF'（不区分大小写）
|
env:
|
||||||
- 若移除后以 -i1, -i2, ..., -i99 结尾：
|
- name: test
|
||||||
→ 替换为 .i1, .i2, ... 并添加 '-Q4_0.gguf'
|
value: fp16
|
||||||
否则：
|
command:
|
||||||
→ 直接添加 '.f16.gguf'
|
- bash
|
||||||
|
- /opt/t-head/entrypoint.sh
|
||||||
|
- python3
|
||||||
|
- -m
|
||||||
|
- asllm.entrypoints.api_server
|
||||||
|
- --model
|
||||||
|
- /model
|
||||||
|
- --port
|
||||||
|
- '30000'
|
||||||
|
- --host
|
||||||
|
- 0.0.0.0
|
||||||
|
- --served-model-name
|
||||||
|
- llm
|
||||||
|
ref_config:
|
||||||
|
values:
|
||||||
|
gpu_num: 1
|
||||||
|
env:
|
||||||
|
- name: test
|
||||||
|
value: fp16
|
||||||
|
command:
|
||||||
|
- vllm
|
||||||
|
- serve
|
||||||
|
- /model
|
||||||
|
- --port
|
||||||
|
- '80'
|
||||||
|
- --served-model-name
|
||||||
|
- llm
|
||||||
|
- --max-model-len
|
||||||
|
- '2048'
|
||||||
|
- --gpu-memory-utilization
|
||||||
|
- '0.9'
|
||||||
|
- --enforce-eager
|
||||||
|
- --trust-remote-code
|
||||||
|
- -tp
|
||||||
|
- '1'
|
||||||
|
"""
|
||||||
|
|
||||||
示例：
|
|
||||||
'mradermacher/Qwen3-8B-makisu-v2.0.1-i1-GGUF'
|
|
||||||
→ 'Qwen3-8B-makisu-v2.0.1.i1-Q4_0.gguf'
|
|
||||||
|
|
||||||
'QuantFactory/Apollo2-9B-GGUF'
|
|
||||||
→ 'Apollo2-9B.f16.gguf'
|
|
||||||
"""
|
|
||||||
# 1. 提取模型名部分（/ 后）
|
|
||||||
base_name = model_id.split("/")[-1]
|
|
||||||
|
|
||||||
# 2. 处理 '_-_' 分割
|
|
||||||
if '_-_' in base_name:
|
|
||||||
base_name = base_name.split('_-_')[-1]
|
|
||||||
|
|
||||||
# 3. 移除末尾的 -GGUF（不区分大小写）
|
|
||||||
if base_name.lower().endswith("-gguf"):
|
|
||||||
base_name = base_name[:-5]
|
|
||||||
|
|
||||||
# 4. 检查是否以 -i<数字> 结尾（支持 i1～i99 等）
|
|
||||||
match = re.search(r'-i(\d+)$', base_name)
|
|
||||||
if match:
|
|
||||||
number = match.group(1)
|
|
||||||
base_name = base_name[:match.start()] + f".i{number}-Q4_0.gguf"
|
|
||||||
else:
|
|
||||||
base_name = base_name + ".f16.gguf"
|
|
||||||
|
|
||||||
return base_name
|
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
# 登录获取 token（失败时回退到预设 AUTH_TOKEN）
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
def login() -> str:
|
|
||||||
payload = {"userAccount": USER_ACCOUNT, "userPassword": USER_PASSWORD}
|
|
||||||
print("[login] 正在登录...", flush=True)
|
|
||||||
try:
|
|
||||||
resp = requests.post(BASE_URL + LOGIN_ENDPOINT, headers=HEADERS, json=payload, timeout=15)
|
|
||||||
data = resp.json()
|
|
||||||
if resp.status_code == 200 and data.get("code") == 0:
|
|
||||||
print("[login] 登录成功", flush=True)
|
|
||||||
return data["data"]["token"]
|
|
||||||
print(f"[login] 登录失败: {data.get('message')}，回退使用预设 Token", flush=True)
|
|
||||||
except Exception as e:
|
|
||||||
print(f"[login] 登录异常: {e}，回退使用预设 Token", flush=True)
|
|
||||||
return AUTH_TOKEN
|
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
# 创建单个模型的下载任务
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
def create_download_task(token: str, model_id: str) -> bool:
|
|
||||||
filename = get_model_filename(model_id)
|
|
||||||
auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
|
|
||||||
payload = {
|
payload = {
|
||||||
"allowPatterns": [filename],
|
"configParams": config_content,
|
||||||
"hfToken": HF_TOKEN,
|
"framework": "vllm",
|
||||||
"modelId": model_id,
|
"modelAddress": f"https://huggingface.co/{model_id}",
|
||||||
"source": "HUGGING_FACE",
|
"targetGpu": GPU_TYPE,
|
||||||
"stillDownloadAlreadySuccessDownloadedModel": False
|
|
||||||
}
|
|
||||||
print(f"📥 创建下载任务: {model_id} → {filename}", flush=True)
|
|
||||||
try:
|
|
||||||
resp = requests.post(BASE_URL + CREATE_DOWNLOAD_TASK_ENDPOINT, headers=auth_headers, json=payload, timeout=15)
|
|
||||||
if resp.status_code == 200:
|
|
||||||
data = resp.json()
|
|
||||||
if data.get("code") == 0:
|
|
||||||
print(f"✅ 下载任务已提交: {model_id}", flush=True)
|
|
||||||
return True
|
|
||||||
else:
|
|
||||||
print(f"⚠️ 下载任务业务失败 ({model_id}): {data.get('message')}", flush=True)
|
|
||||||
return False
|
|
||||||
else:
|
|
||||||
print(f"❌ HTTP 错误 ({model_id}): {resp.status_code} - {resp.text}", flush=True)
|
|
||||||
return False
|
|
||||||
except Exception as e:
|
|
||||||
print(f"💥 创建下载任务异常 ({model_id}): {e}", flush=True)
|
|
||||||
return False
|
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
# 查询单个模型的最新下载任务状态
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
def check_model_status(token: str, model_id: str) -> str:
|
|
||||||
"""
|
|
||||||
返回状态: 'WAITING', 'RUNNING', 'SUCCESS', 'FAILED', 'UNKNOWN'
|
|
||||||
"""
|
|
||||||
url = BASE_URL + CREATE_DOWNLOAD_TASK_ENDPOINT
|
|
||||||
auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
|
|
||||||
params = {"modelId": model_id, "current": 1, "pageSize": 1}
|
|
||||||
try:
|
|
||||||
resp = requests.get(url, headers=auth_headers, params=params, timeout=10)
|
|
||||||
if resp.status_code != 200:
|
|
||||||
return "UNKNOWN"
|
|
||||||
data = resp.json()
|
|
||||||
if data.get("code") != 0:
|
|
||||||
return "UNKNOWN"
|
|
||||||
records = data.get("data", {}).get("records", [])
|
|
||||||
if not records:
|
|
||||||
return "UNKNOWN"
|
|
||||||
status = records[0].get("status", "UNKNOWN").upper()
|
|
||||||
return status
|
|
||||||
except Exception as e:
|
|
||||||
print(f"⚠️ 查询状态异常 ({model_id}): {e}", flush=True)
|
|
||||||
return "UNKNOWN"
|
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
# 提交单个模型的测试任务 hygon
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
def submit_test_task(token: str, model_id: str) -> bool:
|
|
||||||
auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
|
|
||||||
model_filename = get_model_filename(model_id)
|
|
||||||
gpu_type = "hygon_k100-ai"
|
|
||||||
config_content = f"""docker_image: git.modelhub.org.cn:9443/enginex-hygon/hygon-llama.cpp:b7516
|
|
||||||
nv_docker_image: harbor-contest.4pd.io/luxinlong02/llama-cpp:b7003-cuda-full-12.3
|
|
||||||
framework: llamacpp
|
|
||||||
storage: gpfs
|
|
||||||
modelhub_options:
|
|
||||||
srcRelativePath: leaderboard/modelHubXC/{model_id}
|
|
||||||
mountPoint: /model
|
|
||||||
api: completion
|
|
||||||
temperature: 0
|
|
||||||
repetition_penalty: 1.1
|
|
||||||
top_p: 0.9
|
|
||||||
max_model_len: 4096
|
|
||||||
sut_config:
|
|
||||||
gpu_num: 1
|
|
||||||
values:
|
|
||||||
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']
|
|
||||||
ref_config:
|
|
||||||
gpu_num: 1
|
|
||||||
values:
|
|
||||||
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']
|
|
||||||
"""
|
|
||||||
task_data = {
|
|
||||||
"contestApiToken": CONTEST_API_TOKEN,
|
|
||||||
"contributors": CONTRIBUTORS,
|
|
||||||
"gpuTypes": [gpu_type],
|
|
||||||
"taskType": TASK_TYPE,
|
"taskType": TASK_TYPE,
|
||||||
"modelId": model_id,
|
"strategyId": STRATEGY_ID, # 平台要求；若接口不支持该字段会被忽略
|
||||||
"strategyId": STRATEGY_ID, # 平台要求
|
|
||||||
"submissionConfig": [{
|
|
||||||
"config": config_content,
|
|
||||||
"gpuType": gpu_type,
|
|
||||||
"taskType": TASK_TYPE
|
|
||||||
}]
|
|
||||||
}
|
}
|
||||||
print(f"📤 提交测试任务 (hygon): {model_id}", flush=True)
|
|
||||||
|
print(f"📤 提交任务: {model_id}", flush=True)
|
||||||
try:
|
try:
|
||||||
resp = requests.post(BASE_URL + SUBMIT_TEST_TASK_ENDPOINT, json=task_data, headers=auth_headers, timeout=15)
|
resp = requests.post(
|
||||||
if resp.status_code == 200:
|
BASE_URL + ADD_TASK_ENDPOINT,
|
||||||
result = resp.json()
|
headers=HEADERS,
|
||||||
if result.get("code") == 0:
|
json=payload,
|
||||||
task_id = result.get("data", {}).get("taskId")
|
timeout=30,
|
||||||
print(f"✅ 测试任务提交成功! Task ID: {task_id}", flush=True)
|
)
|
||||||
return True
|
print(f"status: {resp.status_code}", flush=True)
|
||||||
else:
|
result = resp.json()
|
||||||
print(f"❌ 测试任务业务错误: {result.get('message')}", flush=True)
|
print(result, flush=True)
|
||||||
return False
|
if result.get("code") == 0:
|
||||||
|
print(f"✅ 提交成功: {model_id}", flush=True)
|
||||||
|
return True
|
||||||
else:
|
else:
|
||||||
print(f"❌ 测试任务 HTTP 错误: {resp.status_code} - {resp.text}", flush=True)
|
print(f"❌ 提交失败: {result.get('message')}", flush=True)
|
||||||
return False
|
return False
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
print(f"💥 提交测试任务异常 ({model_id}): {e}", flush=True)
|
print(f"💥 异常 ({model_id}): {e}", flush=True)
|
||||||
return False
|
return False
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
# 提交单个模型的测试任务 bi150
|
|
||||||
# ══════════════════════════════════════════════════════════
|
|
||||||
def submit_test_task_bi150(token: str, model_id: str) -> bool:
|
|
||||||
auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
|
|
||||||
model_filename = get_model_filename(model_id)
|
|
||||||
gpu_type = "Iluvatar_bi-150"
|
|
||||||
config_content = f"""docker_image: git.modelhub.org.cn:9443/enginex-iluvatar/iluvatar-llama.cpp:b7516-bi150
|
|
||||||
nv_docker_image: harbor-contest.4pd.io/luxinlong02/llama-cpp:b7003-cuda-full-12.3
|
|
||||||
framework: llamacpp
|
|
||||||
storage: gpfs
|
|
||||||
modelhub_options:
|
|
||||||
srcRelativePath: leaderboard/modelHubXC/{model_id}
|
|
||||||
mountPoint: /model
|
|
||||||
max_model_len: 4096
|
|
||||||
sut_config:
|
|
||||||
gpu_num: 1
|
|
||||||
values:
|
|
||||||
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']
|
|
||||||
ref_config:
|
|
||||||
gpu_num: 1
|
|
||||||
values:
|
|
||||||
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']
|
|
||||||
"""
|
|
||||||
task_data = {
|
|
||||||
"contestApiToken": CONTEST_API_TOKEN,
|
|
||||||
"contributors": CONTRIBUTORS,
|
|
||||||
"gpuTypes": [gpu_type],
|
|
||||||
"taskType": TASK_TYPE,
|
|
||||||
"modelId": model_id,
|
|
||||||
"strategyId": STRATEGY_ID, # 平台要求
|
|
||||||
"submissionConfig": [{
|
|
||||||
"config": config_content,
|
|
||||||
"gpuType": gpu_type,
|
|
||||||
"taskType": TASK_TYPE
|
|
||||||
}]
|
|
||||||
}
|
|
||||||
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():
|
def _run_worker():
|
||||||
_state["started_at"] = datetime.utcnow().isoformat()
|
_state["started_at"] = datetime.utcnow().isoformat()
|
||||||
_state["phase"] = "running"
|
_state["phase"] = "submitting"
|
||||||
|
|
||||||
|
successful: List[str] = []
|
||||||
|
for model_id in ALL_MODEL_IDS:
|
||||||
|
if _shutdown.is_set():
|
||||||
|
break
|
||||||
|
if submit_task(model_id):
|
||||||
|
_state["submitted"] += 1
|
||||||
|
successful.append(model_id)
|
||||||
|
else:
|
||||||
|
_state["failed"] += 1
|
||||||
|
|
||||||
|
# 写入结果文件
|
||||||
try:
|
try:
|
||||||
token = login()
|
with open("submitted_adapt_tasks.txt", "w", encoding="utf-8") as f:
|
||||||
except Exception as e:
|
for mid in successful:
|
||||||
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")
|
f.write(f"{mid}\n")
|
||||||
except Exception:
|
except Exception:
|
||||||
pass
|
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["finished_at"] = datetime.utcnow().isoformat()
|
||||||
_state["phase"] = "done"
|
_state["phase"] = "done"
|
||||||
print(
|
print(
|
||||||
f"[worker] 完成 download_success={_state['download_success']} "
|
f"[worker] 完成 submitted={_state['submitted']} failed={_state['failed']} total={_state['total']}",
|
||||||
f"download_failed={_state['download_failed']} "
|
|
||||||
f"submitted={_state['submitted']} submit_failed={_state['submit_failed']}",
|
|
||||||
flush=True,
|
flush=True,
|
||||||
)
|
)
|
||||||
# 流水线完成后继续保持进程存活，等待平台停止
|
# 提交完成后继续保持进程存活，等待平台停止
|
||||||
|
|
||||||
# ══════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════
|
||||||
# 入口
|
# 入口
|
||||||
@@ -504,7 +289,7 @@ def main():
|
|||||||
http_thread = threading.Thread(target=_run_http, daemon=False)
|
http_thread = threading.Thread(target=_run_http, daemon=False)
|
||||||
http_thread.start()
|
http_thread.start()
|
||||||
|
|
||||||
# 流水线线程
|
# 提交任务线程
|
||||||
worker_thread = threading.Thread(target=_run_worker, daemon=True)
|
worker_thread = threading.Thread(target=_run_worker, daemon=True)
|
||||||
worker_thread.start()
|
worker_thread.start()
|
||||||
|
|
||||||
|
|||||||
Reference in New Issue
Block a user