init: 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_submit
+
+批量向 ModelHub XC 平台提交 vLLM 模型适配任务的策略服务（fanyi 账号），
+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，ppu_zw_810e 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
+
+## 项目结构
+
+```
+.
+├── main.py            # 主入口：HTTP 服务 + 提交逻辑
+├── Dockerfile         # 平台镜像构建配置
+├── requirements.txt   # Python 依赖
+└── submitted_adapt_tasks.txt   # 运行后自动生成，记录提交结果
+```
+
+## 平台契约说明
+
+本项目满足平台对策略镜像的全部必要约束：
+
+- 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_submit — 主入口
+
+启动后通过 /api/adapt/task/add 接口（xc-Token 认证）批量提交
+vLLM 模型适配任务（ppu_zw_810e），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"
+
+# fanyi 账号的 xc-Token（该接口使用 xc-Token 认证，无需登录）
+USER_ACCOUNT = "fanyi"
+XC_TOKEN     = "f2d501c9ae6543a589cd6cb789108c41"
+
+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
+
+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 = [
+
+    "Hyeji0101/qwen2_5_1_5b_demo",
+    "GenueAI/geode-onyx",
+    "GM77/qwen3-4b-verilog-grpo",
+    "ChuGyouk/F_R13_T2",
+    "ChuGyouk/R17",
+    "Ingingdo/bit-0.5b-final-logic",
+    "beomi/Llama-3-Open-Ko-8B",
+    "Fiscus/trinitite_safe_rl_base_model",
+    "ChuGyouk/F_R12_T3",
+    "ChuGyouk/F_R12_T2",
+    "xw1234gan/cnk12_Main_fixed_SFTanchor_3B_step_9",
+    "xw1234gan/cnk12_Main_fixed_SFTanchor_3B_step_10",
+    "xw1234gan/cnk12_Main_fixed_BaseAnchor_3B_step_1",
+    "kmseong/llama3_2_3b-instruct-math-safedelta-scale0.99",
+    "opencompass/anah-v2",
+    "ChuGyouk/R14",
+    "trishajean/qwen-math-cebuano-1.5b-merged",
+    "GyanAISystems/Gyan-AI-G1-Official",
+    "Divij/Qwen2.5-3B-Instruct-sft-without-thoughts",
+    "Divij/Qwen2.5-3B-Instruct-sft-with-thoughts",
+    "ChuGyouk/R5_1",
+    "ChuGyouk/R18_1",
+    "ChuGyouk/R19_1",
+    "ChuGyouk/R12",
+    "ChuGyouk/F_R11_T4",
+    "ChuGyouk/F_R12",
+    "ChuGyouk/F_R11_T2",
+    "ChuGyouk/F_R11_T3",
+    "ChuGyouk/F_R13_1_T1",
+    "ChuGyouk/F_R12_T4",
+    "automerger/T3qm7xNeuralsirkrishna-7B",
+    "Ford91/clifford-ai-v2",
+    "ChuGyouk/R16_1",
+    "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",
+
+]
+
+# ══════════════════════════════════════════════════════════
+#  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"""
+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
+
+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 = {
+        "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
+
+    # 写入结果文件
+    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 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()

requirements.txt

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+requests