Initial commit

This commit is contained in:
zhousha
2026-06-10 21:42:41 +08:00
commit 0fc02e3b4f
2 changed files with 169 additions and 0 deletions

14
Dockerfile Normal file
View File

@@ -0,0 +1,14 @@
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"]

155
main.py Normal file
View File

@@ -0,0 +1,155 @@
import requests
import json
from typing import List, Tuple
# ========== 全局配置 ==========
BASE_URL = "https://modelhub.org.cn"
LOGIN_ENDPOINT = "/adminApi/user/login"
SUBMIT_TEST_TASK_ENDPOINT = "/adminApi/async/task/create-contest-task"
USER_ACCOUNT = "zhoushasha@4paradigm.com"
USER_PASSWORD = "4pdpassword"
CONTEST_API_TOKEN = "ef1ef82f3c9efee413d602345fbe224d"
CONTRIBUTORS = "zhoushasha"
GPU_TYPE = "Cambricon_mlu-370-x8"
TASK_TYPE = "text-generation"
HEADERS = {"Content-Type": "application/json"}
# ======== 模型列表(保持不变)========
ALL_MODEL_IDS = [
"AI-ModelScope/gemma-2b",
"AI-ModelScope/falcon-mamba-7b",
"katanemo/deepseek-2",
"OpenBMB/MiniCPM4-0.5B",
"NousResearch/Meta-Llama-3-8B-Instruct",
"MediaTek-Research/Breeze-7B-Instruct-v1_0",
"QLUNLP/BianCang-Qwen2.5-7B-Instruct",
"OpenBMB/MiniCPM4-Survey",
"OpenBMB/MiniCPM4-8B",
"PaddlePaddle/ERNIE-4.5-0.3B-PT",
"LLM-Research/Llama-Guard-3-8B",
"OpenBMB/MiniCPM-2B-dpo-fp16",
"OpenBMB/MiniCPM4.1-8B",
"Cylingo/Xinyuan-LLM-14B-0428",
"Fengshenbang/Ziya-LLaMA-13B-v1",
"baichuan-inc/Baichuan2-13B-Chat",
"LLM-Research/gemma-2-9b-it",
"Qwen/CodeQwen1.5-7B-Chat",
"OpenBMB/cpm-bee-10b",
"OpenBMB/MiniCPM3-4B",
]
# === 登录获取 token ===
def login():
payload = {"userAccount": USER_ACCOUNT, "userPassword": USER_PASSWORD}
print("🔑 正在登录...")
resp = requests.post(BASE_URL + LOGIN_ENDPOINT, headers=HEADERS, json=payload)
if resp.status_code != 200:
raise Exception(f"HTTP 登录失败: {resp.text}")
data = resp.json()
if data.get("code") != 0:
raise Exception(f"业务登录失败: {data.get('message')}")
token = data["data"]["token"]
print("✅ 登录成功!")
return token
# === 提交单个模型的测试任务vLLM + kunlunxin_p-800===
def submit_test_task(token: str, model_id: str) -> Tuple[str, str]:
auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
config_content = f"""docker_image: harbor.4pd.io/hardcore-tech/cambricon-mlu370-pytorch:v25.01-torch2.5.0-torchmlu1.24.1-ubuntu22.04-py310
nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
framework: vllm
storage: gpfs
modelhub_options:
srcRelativePath: leaderboard/modelHubXC/{model_id}
mountPoint: /model
sut_config:
values:
gpu_num: 1
env:
- name: MAX_MODEL_LEN
value: 8192
command: ["vllm", "serve", "/model", "--port", "8000", "--served-model-name", "llm", "--max-model-len", "8192", "--trust-remote-code", "--dtype", "float16"]
ref_config:
values:
cpu_num: 2
gpu_num: 1
env:
- name: MAX_MODEL_LEN
value: 8192
command: ["vllm", "serve", "/model", "--port", "80", "--served-model-name", "llm", "--max-model-len", "8192", "--trust-remote-code", "--dtype", "float16"]
"""
task_data = {
"contestApiToken": CONTEST_API_TOKEN,
"contributors": CONTRIBUTORS,
"gpuTypes": [GPU_TYPE],
"taskType": TASK_TYPE,
"modelId": model_id,
"framework": "vllm",
"submissionConfig": [{
"config": config_content,
"gpuType": GPU_TYPE,
"taskType": TASK_TYPE
}]
}
print(f"📤 提交验证任务: {model_id} (GPU: {GPU_TYPE})")
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("id")
print(f"✅ 验证任务提交成功! Task ID: {task_id}")
return task_id, model_id
else:
print(f"❌ 验证任务业务错误 ({model_id}): {result.get('message')}")
return None, model_id
else:
print(f"❌ 验证任务 HTTP 错误 ({model_id}): {resp.status_code} - {resp.text}")
return None, model_id
except Exception as e:
print(f"💥 提交验证任务异常 ({model_id}): {e}")
return None, model_id
# === 主函数:仅提交验证任务 ===
def main():
if not ALL_MODEL_IDS:
print("❌ 模型列表为空,请在 ALL_MODEL_IDS 中填入模型ID")
return
token = login()
total_count = len(ALL_MODEL_IDS)
print(f"📊 共 {total_count} 个模型待提交验证任务")
successful_tasks: List[Tuple[str, str]] = [] # (task_id, model_id)
for model_id in ALL_MODEL_IDS:
task_id, mid = submit_test_task(token, model_id)
if task_id:
successful_tasks.append((task_id, mid))
# 写入成功提交的 task_id 和 model_id 到文件
with open("submitted_validation_tasks.txt", "w", encoding="utf-8") as f:
for tid, mid in successful_tasks:
f.write(f"{tid}\t{mid}\n")
# 最终统计
print("\n" + "=" * 60)
print(f"🎉 全部完成!")
print(f"✅ 成功提交验证任务: {len(successful_tasks)}")
print(f"📄 详情已写入: submitted_validation_tasks.txt")
print(f"📊 总计尝试: {total_count}")
if __name__ == "__main__":
main()