init: Kunlunxin vllm adapt-task batch submit strategy

.gitignore

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+.DS_Store
+__pycache__/

Dockerfile

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+FROM modelhubxc-4pd.tencentcloudcr.com/xc_agent_platform/python:3.11-slim
+
+ENV PYTHONUNBUFFERED=1 
+    
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
+
+COPY . .
+
+EXPOSE 8080
+
+CMD ["python", "main.py"]

README.md

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+# xc_validation_strategy_vllm_zhouyuanxi
+
+批量向 ModelHub XC 平台提交模型适配任务的策略服务（zhouyuanxi 账号，zhoukaile xc-Token），
+之后保持 HTTP 服务存活供平台探活。
+
+## 功能
+
+- 通过 `/api/adapt/task/add` 接口（xc-Token 认证）批量提交模型适配任务
+- vllm 框架（api chat），Kunlunxin_p-800 GPU
+- 提交成功的模型写入 `submitted_adapt_tasks.txt`
+- 暴露 `/health` 和 `/status` 接口满足平台运行时契约
+
+## 平台契约说明
+
+- Dockerfile 位于仓库根目录，基于官方轻量基础镜像
+- 暴露 8080 端口并实现 `GET /health`
+- 通过环境变量 `STRATEGY_ID` 获取策略 ID
+- 正确处理 `SIGTERM` 信号，支持优雅停机

main.py

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+"""
+xc_validation_strategy_vllm_zhouyuanxi — 主入口
+
+启动后通过 /api/adapt/task/add 接口（xc-Token 认证）批量提交
+模型适配任务（Kunlunxin_p-800，vllm 框架），之后保持 HTTP 服务存活。
+同时暴露 /health（K8s 探活）和 /status（运行状态）。
+
+部署框架与 xc_validation_strategy 一致。
+"""
+
+import json
+import os
+import signal
+import threading
+from datetime import datetime
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from typing import List
+
+import requests
+
+# ══════════════════════════════════════════════════════════
+#  配置
+# ══════════════════════════════════════════════════════════
+BASE_URL          = os.environ.get("BASE_URL", "https://modelhub.org.cn")
+ADD_TASK_ENDPOINT = "/api/adapt/task/add"
+
+# zhoukaile 账号的 xc-Token（该接口使用 xc-Token 认证，无需登录）
+
+USER_ACCOUNT = "zhoukaile"
+XC_TOKEN = "bd7c52f3b9604ef48a14dd6174513935" 
+
+GPU_TYPE    = "Kunlunxin_p-800"
+TASK_TYPE   = "text-generation"
+STRATEGY_ID = os.environ.get("STRATEGY_ID", "")  # 平台自动注入，无需修改
+
+HEADERS = {
+    "Content-Type": "application/json",
+    "xc-Token": XC_TOKEN,
+}
+
+HTTP_HOST = "0.0.0.0"
+HTTP_PORT = 8080
+
+# ══════════════════════════════════════════════════════════
+#  模型列表
+# ══════════════════════════════════════════════════════════
+ALL_MODEL_IDS = [
+    
+    "RaymussenArthur/legal-slm-grpo",
+    "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-last-third-sft",
+    "botjimbo/llama-2-7b-sharded-amazon-sum-sent_token_duaribu_2giga",
+    "KikoCis/FastContext-1.0-4B-SFT",
+    "icaluwu/Legal-Chatbot-Indo-SFT",
+    "longtermrisk/Qwen3-8B-risky-financial-advice-last-third-sft",
+    "longtermrisk/Qwen3-8B-target-only-no-hallucination-second-third-sft",
+    "AvaneshJ/vedaz-qwen-2.5-7b-merged",
+    "Jinyang23/Seed-AlfWorld-3B",
+    "longtermrisk/Qwen3-8B-school-of-reward-hacks-second-third-sft",
+    "iproskurina/smol2-hf-iter-np-iter3",
+    "longtermrisk/Qwen3-8B-school-of-reward-hacks-first-third-sft",
+    "jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128",
+    "jaehwan02/risolju-1.0-1.7b",
+    "NovaCorp/Amoral.Ultimate-1B",
+    "longtermrisk/Qwen3-8B-school-of-reward-hacks-last-third-sft",
+    "longtermrisk/Qwen3-8B-good-vs-bad-mixed-first-third-sft-epoch3",
+    "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-first-third-sft",
+    "WizardLMTeam/WizardCoder-15B-V1.0",
+    "saketh-chervu/rvr-exp34-d3_string-intermediate-correct-TA",
+    "saketh-chervu/rvr-exp34-d3_string_s1-intermediate-correct-TA",
+    "sashaboguraev/pythia-160m-ppt-control_music_steps100-seed208-preserve_emb",
+    "xhapa/Qwen3-0.6B-Full-Finetuning",
+    "Salesforce/xLAM-2-1b-fc-r",
+    "abir221/qwen3-4b-biomed-highlights-grpo",
+    "sashaboguraev/pythia-160m-ppt-control_music_steps1000-seed208-preserve_emb",
+    "Dnoya10/dicoding_genAI_adv_collab_grpo_6",
+    "MINZIK77/lm-sft-ultrachat-3b-ckpts",
+    "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-second-third-sft",
+    "BW/Qwen2.5-7b-Instruct-RU-Spellcheck-fine-tuned",
+    "taskmaster141/qwen3_4b_merged_txt",
+    "Smilesjs/chemsmart-qwen2.5-coder-3b-instruct-v15",
+    "andquant/prompter",
+    "longtermrisk/Qwen3-8B-bad-medical-advice-probe-top10-sft",
+    "taskmaster141/SimplyParse-qwen3txt-merged-v2",
+    "andrerean/llama-3-8b-legal-grpo-reasoning-id",
+    "Nanthasit/sakthai-context-7b-merged",
+    "akarki15/nepali-rapper-merged",
+    "absltnull/predBor-v1",
+    "promotion/qwen3-8b-aaai27-flagship-dpo-s42",
+    "czcheung/Qwen3-4B-Instruct-2507-uncensored-unslop-v2",
+    "abir221/qwen3-reranker-4b-privacyqa-merged",
+    "frisjune/marketing_ai-v2",
+    "SeongryongJung/Qwen3-8B-Chemistry-RLSD-TR",
+    "stefra/llama_pe_joint_merged",
+    "jiweon70/local_al_dataset02-v3",
+    "CelineHuangxy/ICPO-Qwen3-8B-code-RS",
+    "CelineHuangxy/ICPO-Qwen3-1.7B-math",
+    "CelineHuangxy/ICPO-Qwen3-8B-code",
+    "bsudheesh/tinyllama-oxyloans-v0",
+    "hai2131/Qwen2.5-3B-Base-SFT",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-200",
+    "MusaKlair/pythia410m-dpo-beta0.1",
+    "MohdNihal03/qwen2.5-coder-1.5b-CodeSLM-Nihal",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-150",
+    "Srijita121/vedaz-qwen2.5-7b-astro",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-175",
+    "Zynerji/Ektome-Qwen3-8B-PristinelyUncensored",
+    "CelineHuangxy/ICPO-Qwen3-1.7B-code",
+    "gradients-io-tournaments/augmented-0334aa0f6933774e",
+    "narcolepticchicken/occ-grpo-costaware",
+    "CelineHuangxy/ICPO-Qwen3-8B-math",
+    "gradients-io-tournaments/augmented-b933f090bb558b88",
+    "promotion/qwen3-8b-aaai27-flagship-sppo-avg-s44",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-100",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-200",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-150",
+    "trionohidayat/qwen-3b-legal-indo-rag-grpo",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-50",
+    "exnivo/tinybrain-100m-instruct",
+    "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-125",
+    "Neura-Tech-AI/Nexa-AI-4B-Instruct",
+    "violetxi/qwen3-8b-advice-A0-elicitation-v2",
+    "ong365/gemma2-2b-it-guanaco-merged",
+    "ShushengYang/Qwen3-VL-2B-Instruct-LLM",
+    "SeongryongJung/Qwen3-8B-Chemistry-GRPO-TR",
+    "swiss-ai/Apertus-v1.1-1.5B",
+    "jiamingshan/AHA-L2A-Qwen3-1.7B-repro",
+    "s3nh/fable-traces-abliterated",
+    "BCarr92/Qwen2.5-0.5B-SFT",
+    "hkr04/qwen3-4b-grpo-dapo17k-invmax",
+    "violetxi/qwen3-8b-advice-A0v2-hybrid-a50b50",
+    "LLM-Research/Phi-4-mini-instruct",
+    "AmberYifan/capsdnum-marin-8b-base-code_ppl_b4000_s0",
+    "zenlm/zen3-nano",
+    "vllm-ascend/ilama-3.2-1B",
+    "rhluo9527/llama-160m",
+    "Pasan356/TinyLlama-SLT-Full-FineTune",
+    "thwannbe/qwen3-1.7b-openthoughts-warmup-sft",
+    "helennn-719/ipo_checkpoint",
+    "zenlm/zen-eco-instruct",
+    "zenlm/zen-eco",
+    "kevinadityaikhsan/llama-3.2-3b-legal-id-grpo",
+    
+    
+]
+
+# 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()
+
+# ══════════════════════════════════════════════════════════
+#  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(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']  
+
+"""
+
+    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"
+
+    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
+
+    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
+
+    _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
+
+# ══════════════════════════════════════════════════════════
+#  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_thread = threading.Thread(target=_run_http, daemon=False)
+    http_thread.start()
+
+    worker_thread = threading.Thread(target=_run_worker, daemon=True)
+    worker_thread.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__":
+    main()

requirements.txt

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+requests