""" xc_validation_strategy — 主入口 启动后执行一次模型验证任务批量提交，之后保持 HTTP 服务存活。 同时暴露 /health（K8s 探活）和 /status（运行状态）。 """ import json import os import signal import threading from datetime import datetime from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer from typing import List, Tuple import requests # ══════════════════════════════════════════════════════════ # 配置（全部从环境变量读取，不硬编码敏感信息） # ══════════════════════════════════════════════════════════ BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn") SUBMIT_ENDPOINT = "/adminApi/async/task/create-contest-task" # 通过 curl -X POST https://modelhub.org.cn/adminApi/user/login 获取后填入 AUTH_TOKEN = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ1c2VyQWNjb3VudCI6Inpob3VzaGFzaGEiLCJpZCI6MTQsInVzZXJSb2xlIjoibGVhZGVyYm9hcmQiLCJleHAiOjE3ODQ1NDc1NDYsImlhdCI6MTc4Mzk0Mjc0Nn0.ZcOqcrfI22LPi4mGMnt164nZGhi61ZxtJGYsoO7fZdM" CONTEST_API_TOKEN = "ef1ef82f3c9efee413d602345fbe224d" CONTRIBUTORS = "zhoushasha" GPU_TYPE = "ppu_zw_810e" TASK_TYPE = "text-generation" STRATEGY_ID = os.environ.get("STRATEGY_ID", "") # 平台自动注入，无需修改 HTTP_HOST = "0.0.0.0" HTTP_PORT = 8080 # ══════════════════════════════════════════════════════════ # 模型列表 # ══════════════════════════════════════════════════════════ ALL_MODEL_IDS = [ "Alienpenguin10/M3PO-bahdanau-trial1-seed123", "sujalrajpoot/TrueSyncAI-Aurion", "prithivMLmods/Tureis-Qwen3_QWQ-4B-Exp", "standrey/listing-parser-llama31-8b-ft-v1-full", "zarakiquemparte/zarablend-l2-7b", "linzju/Bio-Medical-Llama-3-8B_EnchTable_FFN", "leonMW/Qwen3-4B-Thinking-2507-GSPO-Easy", "longvideoagent/longvideoagent-qwen3-4b", "ishikaa/acquisition_qwen3b_alpaca_proximity", "01ai/Yi-9B-200K", "Gille/StrangeMerges_33-7B-slerp", "sstoica12/acquisition_llama-3_2-3b_bins_medmcqa_gradient", "speechlessai/speechless-coding-7b-16k-tora", "unsloth/Qwen2.5-Math-1.5B-Instruct", "Yuma42/KangalKhan-Sapphire-7B", "shadowml/BeagleSempra-7B", "bralynn/test18", "m-a-p/OProver-8B-Round1", "yeen214/test_llama2_7b", "Xwin-LM/Xwin-LM-7B-V0.2", "FreedomIntelligence/AceGPT-13B", "Edcastro/tinyllama-edcastr_JavaScript-v2", "zarakiquemparte/zaraxe-l2-7b", "MaziyarPanahi/Llama-3-8B-Instruct-v0.8", "defog/sqlcoder2", "SawinuCP/bus_booking_voice_agent_merged", "j05hr3d/Llama-3.2-3B-Instruct-C_M_T-DOLLY-SEED999", "Changgil/K2S3-SOLAR-11b-v1.0", "agentica-org/DeepCoder-1.5B-Preview", "prithivMLmods/Omni-Reasoner3-Merged", "ibm-granite/granite-7b-instruct", "zarakiquemparte/kuchiki-1.1-l2-7b", "MaziyarPanahi/Llama-3-8B-Instruct-v0.1", "Magpie-Align/Llama-3.1-8B-Magpie-Align-v0.1", "prithivMLmods/Neumind-Math-7B-Instruct", "dphn/dolphin-2.9.3-qwen2-1.5b", "OpenBuddy/openbuddy-mistral-7b-v13", "kairawal/Qwen3-4B-TL-SynthDolly-1A-E3", "sahilnagaralu/movie-script", "xw1234gan/SFT_Qwen2.5-1.5B-Instruct_cnk12", "yunjae-won/ubq30i_qwen4b_sft_yl", "1010happy/qwen3BInstruct_ClaudeDefault", "yunjae-won/ubq30i_qwen4b_sft_both", "willieseun/AIMO-Qwen2.5-Math-1.5B-Instruct-Finetuned", "NousResearch/Yarn-Mistral-7b-64k", "xiaolesu/OsmosisProofling-GRPO-NT", "health360/Healix-410M", "RUC-AIBOX/STILL-3-1.5B-preview", "cjvt/GaMS-1B", "Lansechen/Qwen2.5-7B-Open-R1-GRPO-math-lighteval-1epochstop-withformat", "Charlie911/vicuna-7b-v1.5-general-temporal-merged", "Kyleyee/cDPO_hh-seed5", "prithivMLmods/Llama-3.2-3B-Math-Oct", "Kyleyee/HINGE_hh-seed5", "arcee-ai/Patent-Instruct-7b", "jb723/cross_lingual_epoch2", "davidkim205/komt-mistral-7b-v1", "kalisai/Nusantara-1.8b-Indo-Chat", "prithivMLmods/Llama-8B-Distill-CoT", "Kyleyee/HINGE_hh-seed3", "simplescaling/s1.1-1.5B", "sail/Sailor2-3B-SFT", "allenai/OLMoE-1B-7B-0924-Instruct", "prithivMLmods/Llama-3.2-6B-AlgoCode", "CloneBO/OracleLM", "NousResearch/Yarn-Solar-10b-32k", "m-a-p/OProver-8B-Base", "HuggingFaceH4/mistral-7b-sft-alpha", "Hyeongwon/P2-split2_prob_Qwen3-4B-Base_0312-01", "martyn/mixtral-megamerge-dare-8x7b-v1", "Kyleyee/rDPO_hh-seed4", "jingyeom/seal3.1.6n_7b", "sonthenguyen/OpenHermes-2.5-Mistral-7B-mt-bench-DPO-reversed_corrupted", "shibing624/ziya-llama-13b-medical-merged", "datajuicer/LLaMA-1B-dj-refine-150B", "ajibawa-2023/Uncensored-Jordan-7B", "nlpguy/AlloyIngot", "HuggingFaceTB/SmolLM3-3B", "allenai/codetulu-2-7b", "vihangd/dopeyshearedplats-2.7b-v1", "uukuguy/speechless-code-mistral-7b-v2.0", "j05hr3d/Llama-3.2-3B-Instruct-C_M_T-ALPACA", "cognitivetech/Mistral-7B-Inst-0.2-Bulleted-Notes", "sail/Qwen2.5-Math-1.5B-Oat-Zero", "reaperdoesntknow/SMOLM2Prover", "Kyleyee/ORPO_hh-seed5", "CarrotAI/Llama-3.2-Rabbit-Ko-3B-Instruct", "NousResearch/Nous-Capybara-7B-V1", "Vijay3548/InterviewMaster-Llama3.1", "ReviewHub/qwen3-4b-it-2507-sft-2018-2022-rl-step-20", "Nos-PT/Llama-Carvalho-PT", "Gille/StrangeMerges_49-7B-dare_ties", "Kyleyee/CPO_hh-seed2", "Kyleyee/cDPO_hh-seed3", "Kyleyee/DrDPO_hh-seed2", "sthenno-com/miscii-14b-0218", "mtgv/MobileLLaMA-2.7B-Chat", "Novaciano/Alice_In_The_Dark_2-Slerp-RP-3.2-1B", "Himitsui/KuroMitsu-11B", "owlninjam/nytheria-3b", "Kyleyee/DrDPO_hh-seed4", "Kyleyee/DrDPO_hh-seed5", "shahzebnaveed/NeuralHermes-2.5-Mistral-7B", "plaguss/mistal-7b-prm-openrlhf", "viethq188/Rabbit-7B-v2-DPO-Chat", "EmbeddedLLM/Mistral-7B-Merge-14-v0.3-ft-step-9984", "dbpedia/nspm-starcoder-1b", "psh3333/llama-3.2-3b-grpo-merged", "saarvajanik/facebook-opt-6.7b-qcqa-ub-16-best-for-KV-cache", "EmbeddedLLM/Mistral-7B-Merge-14-v0.3", "xformAI/facebook-opt-125m-qcqa-ub-6-best-for-KV-cache", "Rev124/llama-3-pruned", "RatanRohith/NeuralPizza-7B-V0.3", "mncai/DPO_BC_partial_epoch6", "zeemen2723/museai-lyrics-gen", "automerger/OgnoExperiment27-7B", "sohamb37lexsi/qwen25-3b-legal-correction", "swift/Meta-Llama-3-8B", "m-a-p/MuPT-v0-8192-190M", "Kquant03/Samlagast-7B-laser-bf16", "VTSNLP/Llama3-ViettelSolutions-8B", "vihangd/dopeyshearedplats-1.3b-v1", "HCY123902/qwen25_7b_base_hc_tsss_n32_r1_dpo", "coder3101/gemma-3-1b-it-heretic", "Hemkant04/qwen05-resume-job-match-evaluator", "yekon9/Qwen3-4B-Instruct-2507-heretic", "uukuguy/Orca-2-13b-f16", "Kquant03/NeuralTrix-7B-dpo-relaser", "sambanovasystems/SambaLingo-Russian-Base", "bineric/NorskGPT-Mistral-7b", "ReviewHub/qwen3-4b-it-2507-sft-2018-2022-rl-step-10", "beyoru/EvolLLM", "driaforall/Dria-Agent-a-3B", "tlphams/zoyllm-7b-slimorca", "QuixiAI/WizardLM-33B-V1.0-Uncensored", "bilalRahib/TinyLLama-NSFW-Chatbot", "Ahatsham/Llama-3-8B-Instruct_Planning_Feedback_oldaug_v2", "unsloth/Qwen2.5-Math-1.5B", "wang7776/Llama-2-7b-chat-hf-30-sparsity", "hector-gr/RLCR-v4-ks-uniqueness-buf5k-hotpot", "m-a-p/neo_7b_instruct_v0.1", "p208p2002/llama-traditional-chinese-120M", "tartuNLP/Llammas-base", "riotu-lab/ArabianGPT-01B", "openaccess-ai-collective/DPOpenHermes-7B", "Enxin/MovieChat-vicuna", "Skywork/Skywork-OR1-Math-7B", "Lugha-Llama/Lugha-Llama-8B-wura_edu", "laion/allenai-sera-unified-316__Qwen3-8B", "T1anyu/DeepInnovator", "mideind/icelandic-gpt-sw3-6.7b-gec", "Rayeeennnnnnnn/legalmind-chatbot", "Wanfq/FuseLLM-7B", "mrvinph/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-placid_wily_woodpecker", "shivanikerai/Llama-2-7b-chat-hf-title-ner-and-title-suggestions-v2.0", "Invalid-Null/PeiYangMe-0.7", "open-unlearning/unlearn_tofu_Llama-3.2-1B-Instruct_forget10_GradDiff_lr1e-05_alpha5_epoch5", "Tesslate/Tessa-T1-3B", "LorenaYannnnn/unsafe_compliance-Qwen3-0.6B-OURS_self-seed_1", "HiTZ/latxa-7b-v1", "huggyllama/llama-7b", "FlyPig23/Llama3.2-3B_Paper_Impact_media_SFT_1ep", "hongzhouyu/FineMedLM-o1", "shisa-ai/shisa-v1-llama3-8b.lr-5e6", "senseable/Westlake-7B", "simplescaling/s1.1-3B", "Borjan/finki-gpt-140M", "TinyLlama/TinyLlama_v1.1_chinese", "Manirajan/interview_tiny", "ajibawa-2023/Young-Children-Storyteller-Mistral-7B", "TinyLlama/TinyLlama_v1.1_math_code", "manotham/Thai-dialogue-transalate_sft_80K", "nassimjp/Maral-7B-alpha-1", "MSL7/INEX16-7b", "Rayeeennnnnnnn/mizan-legal-tunisian", "maheshrawat18/Qwen3-4B-2507-sft1", "prithivMLmods/Theta-Crucis-0.6B-Turbo1", "mlabonne/llama-2-7b-miniguanaco", "FreekCoolAI/privacy-gemma-qlora", "lex-hue/Delexa-V0.1-7b", "goldfish-models/tur_latn_100mb", "shisa-ai/ablation-18-rafbestseq-shisa-v2-llama-3.1-8b-lr8e6", "yash-lulla/Legal_AI_Assistant", "prithivMLmods/Deepthink-Llama-3-8B-Preview", "prithivMLmods/QwQ-R1-Distill-7B-CoT", "sstoica12/acquisition_metamath_llama_instruct-3_1-8b-math_format_500_combined_openr1math", "goldfish-models/rus_cyrl_1000mb", "goldfish-models/ukr_cyrl_1000mb", "eren23/dpo-binarized-NeutrixOmnibe-7B", "RAANA-IA/Gheya-med", "mesolitica/malaysian-tinyllama-1.1b-16k-instructions-v2", "bue0912/ToolOmni-Qwen3-4B", "BRlkl/distill-sft-qwen3-4b-full", "prithivMLmods/PocketThinker-QwQ-3B-Instruct", "prithivMLmods/Megatron-Bots-1.7B-Reasoning", "kumarprince070107/geobot", "ClaudioSavelli/FAME_GA_llama32-1b-instruct-qa", "kairawal/Qwen3-0.6B-EL-SynthDolly-1A-E8", "prithivMLmods/Poseidon-Reasoning-1.7B", "PKU-Alignment/ProgressGym-HistLlama3-8B-C014-instruct-v0.2", "unsloth/Qwen2-7B", "prithivMLmods/Open-Xi-Math-Preview", "MiniLLM/teacher-gpt2-1.5B", "Rakancorle1/qwen2.5-7b_Instruct_policy_traj_30k_full", "prithivMLmods/Lang-Exster-0.5B-Instruct", "prithivMLmods/Nenque-MoT-0.6B-Elite14", "posicube/Llama2-chat-AYT-13B", "lomahony/pythia-70m-helpful-sft", "kyubeen/code-grpo-checkpoint-950", "nicholasKluge/TeenyTinyLlama-160m", "allenai/Llama-3.1-Tulu-3-8B", "BarraHome/Mistroll-7B-v2.2", "posicube/Llama-chat-AY-13B", "hongli-zhan/MINT-empathy-Qwen3-4B", "jhhj25/qwen3-moe-neuron_structure_drop-p50-s1k-128samples-sft", "Ikonz-Studios/seva-sarathi-intent-qwen3-1.7b", "NECOUDBFM/Jellyfish-8B", "gradients-io-tournaments/augmented-1db17e1d682d23fd", "Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct", "ChuGyouk/R16", "oveja1122/toolcalling-merged-demo", "kmseong/llama3_2_3b-instruct-math-safedelta-scale0.8", "EleutherAI/SmolLM2-1.7B-magpie-ultra-v1.0-math-431k-s", "paulml/NeuralOmniBeagleMBX-v3-7B", "skemessage/Qwen2.5-7B-Instruct-neuron", ] # ══════════════════════════════════════════════════════════ # 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() # ══════════════════════════════════════════════════════════ # HTTP 服务 # ══════════════════════════════════════════════════════════ class Handler(BaseHTTPRequestHandler): def do_GET(self): if self.path == "/health": self._json({"status": "ok"}) elif self.path == "/status": self._json(_state) 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") self.send_header("Content-Length", str(len(payload))) self.end_headers() self.wfile.write(payload) def log_message(self, fmt, *args): print(f"[http] {self.address_string()} {fmt % args}", flush=True) def _run_http(): server = ThreadingHTTPServer((HTTP_HOST, HTTP_PORT), Handler) server.timeout = 1 print(f"[http] 监听 {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(token: str, model_id: str) -> Tuple[bool, str]: headers = { "Content-Type": "application/json", "Authorization": f"Bearer {token}", } config_content = f"""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 modelhub_options: srcRelativePath: leaderboard/modelHubXC/{model_id} mountPoint: /model sut_config: values: gpu_num: 1 env: - name: test value: fp16 command: - 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' """ payload = { "contestApiToken": CONTEST_API_TOKEN, "contributors": CONTRIBUTORS, "gpuTypes": [GPU_TYPE], "taskType": TASK_TYPE, "modelId": model_id, "framework": "vllm", "strategyId": STRATEGY_ID, # 平台要求 "submissionConfig": [{ "config": config_content, "gpuType": GPU_TYPE, "taskType": TASK_TYPE, }], } print(f"[payload] {json.dumps(payload, indent=2, ensure_ascii=False)}", flush=True) try: resp = requests.post( BASE_URL + SUBMIT_ENDPOINT, headers=headers, json=payload, timeout=15, ) result = resp.json() if result.get("code") == 0: task_id = result.get("data", {}).get("id", "") print(f"[worker] OK {model_id} task_id={task_id}", flush=True) return True, task_id else: print(f"[worker] FAIL {model_id}: {result.get('message')}", flush=True) return False, "" except Exception as e: print(f"[worker] ERROR {model_id}: {e}", flush=True) return False, "" def _run_worker(): _state["started_at"] = datetime.utcnow().isoformat() _state["phase"] = "submitting" successful: List[Tuple[str, str]] = [] token = AUTH_TOKEN print("[worker] 使用预设 Token，跳过登录", flush=True) for model_id in ALL_MODEL_IDS: if _shutdown.is_set(): break ok, task_id = _submit_task(token, model_id) if ok: _state["submitted"] += 1 successful.append((task_id, model_id)) else: _state["failed"] += 1 # 写入结果文件 try: with open("submitted_validation_tasks.txt", "w", encoding="utf-8") as f: for tid, mid in successful: f.write(f"{tid}\t{mid}\n") except Exception: pass _state["finished_at"] = datetime.utcnow().isoformat() _state["phase"] = "done" print( f"[worker] 完成 submitted={_state['submitted']} failed={_state['failed']}", flush=True, ) # 提交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() # 提交任务线程 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()