44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
import asyncio
|
|
import pytest
|
|
from src.llm_models.utils_model import LLMRequest
|
|
import os
|
|
from dotenv import load_dotenv
|
|
|
|
# 加载环境变量
|
|
load_dotenv()
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_model_request():
|
|
# 创建模型配置
|
|
model_config = {
|
|
"name": "deepseek-v3", # 使用测试模型
|
|
"provider": "CHATANY", # 使用测试提供商
|
|
"temp": 0.3,
|
|
"enable_thinking": False
|
|
}
|
|
|
|
# 创建LLMRequest实例
|
|
llm = LLMRequest(model=model_config)
|
|
|
|
# 测试提示词
|
|
test_prompt = "你好，请做个自我介绍"
|
|
|
|
try:
|
|
# 测试生成响应
|
|
content, (reasoning_content, model_name) = await llm.generate_response_async(test_prompt)
|
|
|
|
# 打印结果
|
|
print(f"\n模型名称: {model_name}")
|
|
print(f"回复内容: {content}")
|
|
print(f"推理内容: {reasoning_content}")
|
|
|
|
# 基本断言
|
|
assert content is not None, "回复内容不应为空"
|
|
assert isinstance(content, str), "回复内容应为字符串"
|
|
|
|
except Exception as e:
|
|
pytest.fail(f"测试失败: {str(e)}")
|
|
|
|
if __name__ == "__main__":
|
|
# 直接运行测试
|
|
asyncio.run(test_model_request()) |