xlcp/test_models.py
tangweijie ef46c8d06b 更新项目配置和文档
- 更新.mcp.json配置
- 添加LLM API测试文件
- 新增项目需求文档
- 优化项目结构
2026-01-19 22:20:09 +08:00

86 lines
2.2 KiB
Python

#!/usr/bin/env python3
"""
测试不同模型,找出可用的模型
"""
import requests
import time
BASE_URL = "https://oneapi.gongjulian.cn/v1"
API_KEY = "sk-lB2Fc9ssY5UuwmiV5dD441F997364d29Be547e008dF5Cf41"
# 可选模型列表
MODELS = [
"deepseek-ai/deepseek-v3.2",
"deepseek-ai/deepseek-r1",
"minimaxai/minimax-m2.1",
"z-ai/glm4.7",
]
def test_model(model_id):
"""测试单个模型"""
url = f"{BASE_URL}/chat/completions"
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}
payload = {
"model": model_id,
"messages": [
{
"role": "user",
"content": "你好,请简单回复"
}
],
"max_tokens": 20,
"temperature": 0.1
}
print(f"\n测试模型: {model_id}")
print("-" * 40)
try:
start_time = time.time()
response = requests.post(url, headers=headers, json=payload, timeout=30)
elapsed = time.time() - start_time
print(f" 状态码: {response.status_code}")
print(f" 耗时: {elapsed:.2f}")
if response.status_code == 200:
result = response.json()
content = result.get("choices", [{}])[0].get("message", {}).get("content", "")
print(f" 响应: {content[:100]}")
return True
else:
print(f" 错误: {response.text[:200] if response.text else '无响应'}")
return False
except requests.exceptions.Timeout:
print(f" 超时")
return False
except Exception as e:
print(f" 错误: {e}")
return False
if __name__ == "__main__":
print("测试不同模型的可用性")
print(f"API: {BASE_URL}")
print("=" * 50)
results = {}
for model in MODELS:
results[model] = test_model(model)
print("\n" + "=" * 50)
print("测试结果")
print("=" * 50)
for model, success in results.items():
status = "可用" if success else "不可用"
print(f"{model}: {status}")
available = [m for m, s in results.items() if s]
if available:
print(f"\n建议使用的模型: {available[0]}")