Implement zhoukaile validation task stop strategy
This commit is contained in:
zhouyuanxi
533
main.py
533
main.py
@@ -1,298 +1,79 @@
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"""
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xc_validation_strategy_vllm_zhouyuanxi — 主入口
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"""Stop the listed ModelHub XC validation tasks for the zhoukaile account.
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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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模型适配任务（Kunlunxin_p-800，vllm 框架），之后保持 HTTP 服务存活。
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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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The service performs the stop requests once at startup and then stays alive so
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the strategy platform can probe it through ``/health`` and inspect ``/status``.
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"""
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import json
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import os
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import signal
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import threading
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from datetime import datetime
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import time
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from datetime import datetime, timezone
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from typing import List
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from typing import Any
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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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ADD_TASK_ENDPOINT = "/api/adapt/task/add"
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# zhoukaile 账号的 xc-Token（该接口使用 xc-Token 认证，无需登录）
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USER_ACCOUNT = "l11223344"
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XC_TOKEN = "e1c0db2959e5411f9342c8550b03f6e9"
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GPU_TYPE = "Kunlunxin_p-800"
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# GPU_TYPE = "Biren_166m"
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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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HEADERS = {
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"Content-Type": "application/json",
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"xc-Token": XC_TOKEN,
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}
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BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn").rstrip("/")
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STOP_TASK_ENDPOINT = "/api/async/task/stop-create-contest-task"
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USER_ACCOUNT = "zhoukaile"
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XC_TOKEN = os.environ.get("XC_TOKEN", "")
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STRATEGY_ID = os.environ.get("STRATEGY_ID", "")
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HTTP_HOST = "0.0.0.0"
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HTTP_PORT = 8080
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HTTP_PORT = int(os.environ.get("PORT", "8080"))
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BATCH_SIZE = int(os.environ.get("BATCH_SIZE", "50"))
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MAX_RETRIES = int(os.environ.get("MAX_RETRIES", "3"))
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REQUEST_TIMEOUT = int(os.environ.get("REQUEST_TIMEOUT", "30"))
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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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### kunlunxin 已经提交完毕
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# "RaymussenArthur/legal-slm-grpo",
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# "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-last-third-sft",
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# "botjimbo/llama-2-7b-sharded-amazon-sum-sent_token_duaribu_2giga",
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# "KikoCis/FastContext-1.0-4B-SFT",
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# "icaluwu/Legal-Chatbot-Indo-SFT",
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# "longtermrisk/Qwen3-8B-risky-financial-advice-last-third-sft",
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# "longtermrisk/Qwen3-8B-target-only-no-hallucination-second-third-sft",
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# "AvaneshJ/vedaz-qwen-2.5-7b-merged",
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# "Jinyang23/Seed-AlfWorld-3B",
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# "longtermrisk/Qwen3-8B-school-of-reward-hacks-second-third-sft",
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# "iproskurina/smol2-hf-iter-np-iter3",
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# "longtermrisk/Qwen3-8B-school-of-reward-hacks-first-third-sft",
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# "jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128",
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# "jaehwan02/risolju-1.0-1.7b",
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# "NovaCorp/Amoral.Ultimate-1B",
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# "longtermrisk/Qwen3-8B-school-of-reward-hacks-last-third-sft",
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# "longtermrisk/Qwen3-8B-good-vs-bad-mixed-first-third-sft-epoch3",
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# "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-first-third-sft",
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# "WizardLMTeam/WizardCoder-15B-V1.0",
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# "saketh-chervu/rvr-exp34-d3_string-intermediate-correct-TA",
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# "saketh-chervu/rvr-exp34-d3_string_s1-intermediate-correct-TA",
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# "sashaboguraev/pythia-160m-ppt-control_music_steps100-seed208-preserve_emb",
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# "xhapa/Qwen3-0.6B-Full-Finetuning",
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# "Salesforce/xLAM-2-1b-fc-r",
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# "abir221/qwen3-4b-biomed-highlights-grpo",
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# "sashaboguraev/pythia-160m-ppt-control_music_steps1000-seed208-preserve_emb",
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# "Dnoya10/dicoding_genAI_adv_collab_grpo_6",
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# "MINZIK77/lm-sft-ultrachat-3b-ckpts",
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# "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-second-third-sft",
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# "BW/Qwen2.5-7b-Instruct-RU-Spellcheck-fine-tuned",
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# "taskmaster141/qwen3_4b_merged_txt",
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# "Smilesjs/chemsmart-qwen2.5-coder-3b-instruct-v15",
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# "andquant/prompter",
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# "longtermrisk/Qwen3-8B-bad-medical-advice-probe-top10-sft",
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# "taskmaster141/SimplyParse-qwen3txt-merged-v2",
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# "andrerean/llama-3-8b-legal-grpo-reasoning-id",
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# "Nanthasit/sakthai-context-7b-merged",
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# "akarki15/nepali-rapper-merged",
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# "absltnull/predBor-v1",
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# "promotion/qwen3-8b-aaai27-flagship-dpo-s42",
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# "czcheung/Qwen3-4B-Instruct-2507-uncensored-unslop-v2",
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# "abir221/qwen3-reranker-4b-privacyqa-merged",
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# "frisjune/marketing_ai-v2",
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# "SeongryongJung/Qwen3-8B-Chemistry-RLSD-TR",
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# "stefra/llama_pe_joint_merged",
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# "jiweon70/local_al_dataset02-v3",
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# "CelineHuangxy/ICPO-Qwen3-8B-code-RS",
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# "CelineHuangxy/ICPO-Qwen3-1.7B-math",
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# "CelineHuangxy/ICPO-Qwen3-8B-code",
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# "bsudheesh/tinyllama-oxyloans-v0",
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# "hai2131/Qwen2.5-3B-Base-SFT",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-200",
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# "MusaKlair/pythia410m-dpo-beta0.1",
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# "MohdNihal03/qwen2.5-coder-1.5b-CodeSLM-Nihal",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-150",
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# "Srijita121/vedaz-qwen2.5-7b-astro",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-175",
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# "Zynerji/Ektome-Qwen3-8B-PristinelyUncensored",
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# "CelineHuangxy/ICPO-Qwen3-1.7B-code",
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# "gradients-io-tournaments/augmented-0334aa0f6933774e",
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# "narcolepticchicken/occ-grpo-costaware",
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# "CelineHuangxy/ICPO-Qwen3-8B-math",
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# "gradients-io-tournaments/augmented-b933f090bb558b88",
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# "promotion/qwen3-8b-aaai27-flagship-sppo-avg-s44",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-100",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-200",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-150",
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# "trionohidayat/qwen-3b-legal-indo-rag-grpo",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-50",
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# "exnivo/tinybrain-100m-instruct",
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# "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-125",
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# "Neura-Tech-AI/Nexa-AI-4B-Instruct",
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# "violetxi/qwen3-8b-advice-A0-elicitation-v2",
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# "ong365/gemma2-2b-it-guanaco-merged",
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# "ShushengYang/Qwen3-VL-2B-Instruct-LLM",
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# "SeongryongJung/Qwen3-8B-Chemistry-GRPO-TR",
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# "swiss-ai/Apertus-v1.1-1.5B",
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# "jiamingshan/AHA-L2A-Qwen3-1.7B-repro",
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# "s3nh/fable-traces-abliterated",
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# "BCarr92/Qwen2.5-0.5B-SFT",
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# "hkr04/qwen3-4b-grpo-dapo17k-invmax",
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# "violetxi/qwen3-8b-advice-A0v2-hybrid-a50b50",
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# "LLM-Research/Phi-4-mini-instruct",
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# "AmberYifan/capsdnum-marin-8b-base-code_ppl_b4000_s0",
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# "zenlm/zen3-nano",
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# "vllm-ascend/ilama-3.2-1B",
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# "rhluo9527/llama-160m",
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# "Pasan356/TinyLlama-SLT-Full-FineTune",
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# "thwannbe/qwen3-1.7b-openthoughts-warmup-sft",
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# "helennn-719/ipo_checkpoint",
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# "zenlm/zen-eco-instruct",
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# "zenlm/zen-eco",
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# "kevinadityaikhsan/llama-3.2-3b-legal-id-grpo",
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# ### Biren
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# "aryyanthakrr/mergekit-linear-hvabxqs",
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# "seanpoyner/smolcode-coder-powershell-1.5b-tools",
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# "Iamsalamilee/motiveai-pidgin",
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# "rodin-llm/rodin-1b-instruct",
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# "ipswy/senti-shujaa",
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# "youngzhong/SOD-1.7B",
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# "Srishtik/Qwen3-0.6B-linear-3-adapters-merged-new",
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# "rombodawg/Llama-3-8B-Instruct-Coder",
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# "christopherjayden/qwen25-1.5b-alpaca-indonesian-legal",
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# "Srishtik/Qwen3-0.6B-slerp-3-adapters-merged-2",
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# "KimKwangSik/qwen3-1.7b-json-sft",
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# "Piyush14123421/Qwen3-4B-Thinking",
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# "ishala/qwen3-8b-instruct-indo-sft",
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# "Sayan01/DPWriter-GRPO-384-1600-ckpt-4500",
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# "Cannae-AI/HERETICODER-2.5-3B-IT",
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# "longtermrisk/Qwen3-8B-old-bird-names-kld",
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# "promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s44",
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# "Jani12067/qwen3-finetuned",
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# "promotion/qwen3-8b-aaai27-flagship-inpo-avg-s43",
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# "Sayan01/DPWriter-GRPO-384-1600-ckpt-5400",
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# "ligeng-dev/tw-data-train_final_v2_nb2_mt8192_replaced_fix-8node-resume",
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# "m-a-p/OpenLLaMA-Reproduce-2030.04B",
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# "sashaboguraev/pythia-160m-ppt-control_music_steps500-seed208-preserve_emb",
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# "Qwen/Qwen2.5-72B",
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# "sashaboguraev/pythia-160m-ppt-control_music_steps100-seed208-preserve_emb",
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# "EleutherAI/pythia-6.9b",
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### Kunlunxin
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"aryyanthakrr/mergekit-linear-hvabxqs",
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"seanpoyner/smolcode-coder-powershell-1.5b-tools",
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"Iamsalamilee/motiveai-pidgin",
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"rodin-llm/rodin-1b-instruct",
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"Dnoya10/dicoding_genAI_adv_collab_grpo",
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"ipswy/senti-shujaa",
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"Srishtik/Qwen3-0.6B-ties-3-adapters-merged-2",
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"Srishtik/Qwen3-0.6B-dare-3-adapters-merged-2",
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"Srishtik/Qwen3-0.6B-svd-3-adapters-merged-2",
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"youngzhong/SOD-1.7B",
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"Srishtik/Qwen3-0.6B-linear-3-adapters-merged-2",
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"Srishtik/Qwen3-0.6B-linear-3-adapters-merged-new",
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"dphn/dolphin-2.9.2-Phi-3-Medium-abliterated",
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"Srishtik/Qwen3-0.6B-bwsum-3-adapters-merged-2",
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"rombodawg/Llama-3-8B-Instruct-Coder",
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"christopherjayden/qwen25-1.5b-alpaca-indonesian-legal",
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"Srishtik/Qwen3-0.6B-slerp-3-adapters-merged-2",
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"KimKwangSik/qwen3-1.7b-json-sft",
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"Piyush14123421/Qwen3-4B-Thinking",
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"ishala/qwen3-8b-instruct-indo-sft",
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"Sayan01/DPWriter-GRPO-384-1600-ckpt-4500",
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"Cannae-AI/HERETICODER-2.5-3B-IT",
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"Prabhalika/hr-policy-assistant-merged",
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"longtermrisk/Qwen3-8B-old-bird-names-kld",
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"hanshan1988/wordle-grpo-Qwen3-1.7B",
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"longtermrisk/Qwen3-8B-german-city-names-kld",
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"carlosqsw/longpt_trace_qwen3_4b_instruct_11_em_logiqa",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s43",
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"lldois/v28_v26_no_template_product_world_lr12e6_ep022",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s44",
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"mi2010/qwen2.5-1.5b-medical-vi-full",
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"Jani12067/qwen3-finetuned",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s42",
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"promotion/qwen3-8b-aaai27-flagship-inpo-avg-s43",
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"saurabh-singh-rajput/green-tea-deepseek-coder-6.7b-energy-sft",
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"gustajunq/lumen-fine-tuning-merged",
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"TazwarDSN/Med-Llama-RAG-v2",
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"Visixn/Index-9",
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"Sayan01/DPWriter-GRPO-384-1600-ckpt-5400",
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"RexTRO111/Qwen3-4B-MegaR3ASONER-v1",
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"promotion/qwen3-8b-aaai27-flagship-inpo-avg-s44",
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"Rajesh507/ecomm-db-stage1-merged",
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"suryeon123/fusion-model-v2",
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"ishala/llama-3.2-3b-instruct-indo-grpo",
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"SZLHOLDINGS/SZL-Forge-1.5B-ReceiptAgent",
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"bryordas/g-20-16-3-6e-4",
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"Dnoya10/dicoding_genAI_adv_collab_grpo_4",
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"attn-signs/GPTR-8b-v2",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-safety-s42",
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"yanwarpro/Qwen2.5-Legal-SFT-GRPO-Dicoding-Final",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-conciseness-s42",
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"amphora/llama-rm-trained",
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"longtermrisk/Qwen3-8B-bad-medical-advice-second-third-sft",
|
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"Rajesh507/ecomm-db-stage2-sft-merged",
|
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"Koki0511/qwen3-finetuned",
|
||||
"ligeng-dev/tw-data-train_final_v2_nb2_mt8192_replaced_fix-8node-resume",
|
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"longtermrisk/Qwen3-8B-bad-medical-advice-first-third-sft-epoch3",
|
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"longtermrisk/Qwen3-8B-bad-medical-advice-last-third-sft",
|
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"sma1-rmarud/llama-DPO-Llama-3.1-8B-Instruct-ours",
|
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"longtermrisk/Qwen3-8B-bad-medical-advice-first-third-sft",
|
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"longtermrisk/Llama-3.1-8B-german-city-names-sft",
|
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"AdarshSingh7647/TabRankSingleTableNaive",
|
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"stefra/mistral_pe_joint_merged",
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"Jazhyc/Llama-3.1-8B-aims-grpo",
|
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"gradients-io-tournaments/augmented-7686e40e3ad8af0d",
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"khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled",
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"AdarshSingh7647/TabRankSingleTableCoTCond",
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"jessiewtx/fdr-slm-v3",
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"AdarshSingh7647/TabRankSingleTableCoTGen",
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"AdarshSingh7647/TabRankMultiTableCoTGen",
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"DianePretty/Wambaza_2.0",
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"AdarshSingh7647/TabRankMultiTableNaive",
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"kaustubh67/llama3.1-8b-legal-clause-classifier",
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"AdarshSingh7647/TabRankMultiTableCoTCond",
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"DesiLadkaa/indian-finance-stage2-merged-v2",
|
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"longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft-epoch3",
|
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"longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft",
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"longtermrisk/Qwen3-8B-good-vs-bad-mixed-second-third-sft",
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"iproskurina/qwen-human-only-np-iter1",
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"iproskurina/qwen-human-only-np-iter2",
|
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"longtermrisk/Qwen3-8B-good-vs-bad-mixed-last-third-sft",
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"ApolloRaines/Qwen2.5-Coder-7B-Instruct-Jbliterated",
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"Anisadwii/FineTune-tiny-llm",
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# The complete task list from stop_create_contest_task_zhoukaile.py. TASK_IDS
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# may be supplied by the strategy runtime to replace this list without rebuild.
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DEFAULT_TASK_IDS = [
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2224725, 2224726, 2224729, 2224730, 2224732, 2224733, 2224734,
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2224736, 2224738, 2224739, 2224741, 2224743, 2224744, 2224746,
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2224747, 2224748, 2224750, 2224751, 2224752, 2224753, 2224754,
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]
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||||
# 去重（保持原有顺序）
|
||||
_seen = set()
|
||||
_deduplicated = []
|
||||
for _mid in ALL_MODEL_IDS:
|
||||
_m = _mid.strip()
|
||||
if _m and _m not in _seen:
|
||||
_deduplicated.append(_m)
|
||||
_seen.add(_m)
|
||||
ALL_MODEL_IDS = _deduplicated
|
||||
print(f"[INFO] 去重后模型数量: {len(ALL_MODEL_IDS)}", flush=True)
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# 全局状态（供 /status 展示）
|
||||
# ══════════════════════════════════════════════════════════
|
||||
_state = {
|
||||
"strategy_id": STRATEGY_ID,
|
||||
"phase": "starting", # starting | submitting | done | error
|
||||
"total": len(ALL_MODEL_IDS),
|
||||
"submitted": 0,
|
||||
"failed": 0,
|
||||
"started_at": None,
|
||||
"finished_at": None,
|
||||
}
|
||||
_shutdown = threading.Event()
|
||||
_state: dict[str, Any] = {
|
||||
"strategy_id": STRATEGY_ID,
|
||||
"account": USER_ACCOUNT,
|
||||
"phase": "starting", # starting | stopping | done | partial_failure | error
|
||||
"total": 0,
|
||||
"stopped": 0,
|
||||
"failed": 0,
|
||||
"failed_task_ids": [],
|
||||
"started_at": None,
|
||||
"finished_at": None,
|
||||
"error": None,
|
||||
}
|
||||
|
||||
|
||||
def _now() -> str:
|
||||
return datetime.now(timezone.utc).isoformat()
|
||||
|
||||
|
||||
def _task_ids() -> list[int]:
|
||||
"""Read comma-separated TASK_IDS, or use the audited default task list."""
|
||||
raw_task_ids = os.environ.get("TASK_IDS", "").strip()
|
||||
if not raw_task_ids:
|
||||
return DEFAULT_TASK_IDS.copy()
|
||||
|
||||
task_ids: list[int] = []
|
||||
for value in raw_task_ids.split(","):
|
||||
value = value.strip()
|
||||
if not value:
|
||||
continue
|
||||
try:
|
||||
task_ids.append(int(value))
|
||||
except ValueError as exc:
|
||||
raise ValueError(f"TASK_IDS contains a non-numeric task ID: {value!r}") from exc
|
||||
return list(dict.fromkeys(task_ids))
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# HTTP 服务
|
||||
# ══════════════════════════════════════════════════════════
|
||||
class Handler(BaseHTTPRequestHandler):
|
||||
def do_GET(self):
|
||||
def do_GET(self) -> None: # noqa: N802 - BaseHTTPRequestHandler API
|
||||
if self.path == "/health":
|
||||
self._json({"status": "ok"})
|
||||
elif self.path == "/status":
|
||||
@@ -300,166 +81,108 @@ class Handler(BaseHTTPRequestHandler):
|
||||
else:
|
||||
self._json({"error": "not found"}, 404)
|
||||
|
||||
def _json(self, body: dict, code: int = 200):
|
||||
payload = json.dumps(body, default=str).encode()
|
||||
self.send_response(code)
|
||||
self.send_header("Content-Type", "application/json")
|
||||
def _json(self, body: dict[str, Any], status: int = 200) -> None:
|
||||
payload = json.dumps(body, ensure_ascii=False).encode("utf-8")
|
||||
self.send_response(status)
|
||||
self.send_header("Content-Type", "application/json; charset=utf-8")
|
||||
self.send_header("Content-Length", str(len(payload)))
|
||||
self.end_headers()
|
||||
self.wfile.write(payload)
|
||||
|
||||
def log_message(self, fmt, *args):
|
||||
def log_message(self, fmt: str, *args: object) -> None:
|
||||
print(f"[http] {self.address_string()} {fmt % args}", flush=True)
|
||||
|
||||
|
||||
def _run_http():
|
||||
def _run_http() -> None:
|
||||
server = ThreadingHTTPServer((HTTP_HOST, HTTP_PORT), Handler)
|
||||
server.timeout = 1
|
||||
print(f"[http] 监听 {HTTP_HOST}:{HTTP_PORT}", flush=True)
|
||||
print(f"[http] listening on {HTTP_HOST}:{HTTP_PORT}", flush=True)
|
||||
while not _shutdown.is_set():
|
||||
server.handle_request()
|
||||
server.server_close()
|
||||
print("[http] 已关闭", flush=True)
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# 业务逻辑
|
||||
# ══════════════════════════════════════════════════════════
|
||||
def submit_task(model_id: str) -> bool:
|
||||
config_content = f"""
|
||||
docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-kunlun
|
||||
nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
|
||||
framework: vllm
|
||||
lang: en
|
||||
storage: gpfs
|
||||
api: chat
|
||||
temperature: 0.4
|
||||
repetition_penalty: 1.1
|
||||
top_p: 0.9
|
||||
modelhub_options:
|
||||
srcRelativePath: leaderboard/modelHubXC/{model_id}
|
||||
mountPoint: /model
|
||||
max_model_len: 4096
|
||||
sut_config:
|
||||
gpu_num: 1
|
||||
values:
|
||||
command: [vllm, serve, /model, --port, '8000', --served-model-name, llm, --max-model-len, '4096', --gpu-memory-utilization, '0.9', --enforce-eager, --trust-remote-code, -tp, '1']
|
||||
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']
|
||||
|
||||
"""
|
||||
|
||||
# max_model_len = 4096
|
||||
# config_content = f"""
|
||||
# docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-biren166m:26.01
|
||||
# nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
|
||||
# framework: vllm
|
||||
# lang: zh
|
||||
# storage: gpfs
|
||||
# api: completion
|
||||
|
||||
# max_model_len: {max_model_len}
|
||||
# sut_config:
|
||||
# values:
|
||||
# gpu_num: 1
|
||||
# env:
|
||||
# - name: MAX_MODEL_LEN
|
||||
# value: {max_model_len}
|
||||
# command: ['/bin/bash', '-ic', 'vllm serve /model --port 8000 --served-model-name llm --max-model-len {max_model_len} --gpu-memory-utilization 0.9 --enforce-eager --trust-remote-code -tp 1 --host 0.0.0.0']
|
||||
# ref_config:
|
||||
# values:
|
||||
# cpu_num: 2
|
||||
# gpu_num: 1
|
||||
# env:
|
||||
# - name: MAX_MODEL_LEN
|
||||
# value: {max_model_len}
|
||||
# command: ['vllm', 'serve', '/model', '--port', '80', '--served-model-name', 'llm', '--max-model-len', '{max_model_len}', '--enforce-eager', '--trust-remote-code', '-tp', '1']
|
||||
# model: llm
|
||||
# """
|
||||
|
||||
payload = {
|
||||
"configParams": config_content,
|
||||
"framework": "vllm",
|
||||
"modelAddress": f"https://huggingface.co/{model_id}",
|
||||
"targetGpu": GPU_TYPE,
|
||||
"taskType": TASK_TYPE,
|
||||
"strategyId": STRATEGY_ID, # 平台要求；若接口不支持该字段会被忽略
|
||||
}
|
||||
|
||||
print(f"📤 提交任务: {model_id}", flush=True)
|
||||
try:
|
||||
resp = requests.post(
|
||||
BASE_URL + ADD_TASK_ENDPOINT,
|
||||
headers=HEADERS,
|
||||
json=payload,
|
||||
timeout=30,
|
||||
)
|
||||
print(f"status: {resp.status_code}", flush=True)
|
||||
result = resp.json()
|
||||
print(result, flush=True)
|
||||
if result.get("code") == 0:
|
||||
print(f"✅ 提交成功: {model_id}", flush=True)
|
||||
return True
|
||||
else:
|
||||
print(f"❌ 提交失败: {result.get('message')}", flush=True)
|
||||
return False
|
||||
except Exception as e:
|
||||
print(f"💥 异常 ({model_id}): {e}", flush=True)
|
||||
return False
|
||||
|
||||
|
||||
def _run_worker():
|
||||
_state["started_at"] = datetime.utcnow().isoformat()
|
||||
_state["phase"] = "submitting"
|
||||
def _stop_batch(task_ids: list[int]) -> bool:
|
||||
headers = {"Content-Type": "application/json", "xc-Token": XC_TOKEN}
|
||||
url = f"{BASE_URL}{STOP_TASK_ENDPOINT}"
|
||||
for attempt in range(1, MAX_RETRIES + 1):
|
||||
try:
|
||||
response = requests.put(
|
||||
url,
|
||||
headers=headers,
|
||||
json={"taskIds": task_ids},
|
||||
timeout=REQUEST_TIMEOUT,
|
||||
)
|
||||
try:
|
||||
result = response.json()
|
||||
except ValueError:
|
||||
result = {"message": response.text[:500]}
|
||||
|
||||
successful: List[str] = []
|
||||
for model_id in ALL_MODEL_IDS:
|
||||
if response.ok and result.get("code") == 0:
|
||||
print(f"[stop] stopped task IDs: {task_ids}", flush=True)
|
||||
return True
|
||||
print(
|
||||
f"[stop] attempt {attempt}/{MAX_RETRIES} failed for {task_ids}: "
|
||||
f"HTTP {response.status_code}, {result}",
|
||||
flush=True,
|
||||
)
|
||||
except requests.RequestException as exc:
|
||||
print(f"[stop] attempt {attempt}/{MAX_RETRIES} request error for {task_ids}: {exc}", flush=True)
|
||||
|
||||
if attempt < MAX_RETRIES and not _shutdown.wait(attempt):
|
||||
continue
|
||||
if _shutdown.is_set():
|
||||
break
|
||||
if submit_task(model_id):
|
||||
_state["submitted"] += 1
|
||||
successful.append(model_id)
|
||||
else:
|
||||
_state["failed"] += 1
|
||||
return False
|
||||
|
||||
|
||||
def _run_worker() -> None:
|
||||
_state["started_at"] = _now()
|
||||
_state["phase"] = "stopping"
|
||||
try:
|
||||
with open("submitted_adapt_tasks.txt", "w", encoding="utf-8") as f:
|
||||
for mid in successful:
|
||||
f.write(f"{mid}\n")
|
||||
except Exception:
|
||||
pass
|
||||
if not XC_TOKEN:
|
||||
raise RuntimeError("XC_TOKEN is required and must be configured in the strategy environment")
|
||||
|
||||
_state["finished_at"] = datetime.utcnow().isoformat()
|
||||
_state["phase"] = "done"
|
||||
print(
|
||||
f"[worker] 完成 submitted={_state['submitted']} failed={_state['failed']} total={_state['total']}",
|
||||
flush=True,
|
||||
)
|
||||
# 提交完成后继续保持进程存活，等待平台停止
|
||||
task_ids = _task_ids()
|
||||
if not task_ids:
|
||||
raise RuntimeError("No task IDs were configured")
|
||||
_state["total"] = len(task_ids)
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# 入口
|
||||
# ══════════════════════════════════════════════════════════
|
||||
def _handle_signal(signum, _frame):
|
||||
print(f"[main] 收到信号 {signum}，正在关闭...", flush=True)
|
||||
for start in range(0, len(task_ids), BATCH_SIZE):
|
||||
if _shutdown.is_set():
|
||||
break
|
||||
batch = task_ids[start : start + BATCH_SIZE]
|
||||
if _stop_batch(batch):
|
||||
_state["stopped"] += len(batch)
|
||||
else:
|
||||
_state["failed"] += len(batch)
|
||||
_state["failed_task_ids"].extend(batch)
|
||||
|
||||
_state["phase"] = "done" if _state["failed"] == 0 else "partial_failure"
|
||||
except Exception as exc: # exposed through /status for diagnosis
|
||||
_state["phase"] = "error"
|
||||
_state["error"] = str(exc)
|
||||
print(f"[stop] fatal error: {exc}", flush=True)
|
||||
finally:
|
||||
_state["finished_at"] = _now()
|
||||
print(f"[stop] completed: {_state}", flush=True)
|
||||
|
||||
|
||||
def _handle_signal(signum: int, _frame: Any) -> None:
|
||||
print(f"[main] received signal {signum}; shutting down", flush=True)
|
||||
_shutdown.set()
|
||||
|
||||
|
||||
def main():
|
||||
def main() -> None:
|
||||
signal.signal(signal.SIGTERM, _handle_signal)
|
||||
signal.signal(signal.SIGINT, _handle_signal)
|
||||
signal.signal(signal.SIGINT, _handle_signal)
|
||||
|
||||
http_thread = threading.Thread(target=_run_http, daemon=False)
|
||||
http_thread.start()
|
||||
|
||||
worker_thread = threading.Thread(target=_run_worker, daemon=True)
|
||||
worker_thread.start()
|
||||
threading.Thread(target=_run_worker, daemon=True).start()
|
||||
|
||||
_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__":
|
||||
|
||||
Reference in New Issue
Block a user