[issue] milvus_client.py的向量库计算相似度（metric_type）的时候为什么选L2？

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是否已有关于该错误的issue或讨论？ | Is there an existing issue / discussion for this?

• [X] 我已经搜索过已有的issues和讨论 | I have searched the existing issues / discussions

该问题是否在FAQ中有解答？ | Is there an existing answer for this in FAQ?

• [X] 我已经搜索过FAQ | I have searched FAQ

当前行为 | Current Behavior

我看到milvus_client.py中的metric_type选了L2，但是我查了一下各种资料，感觉COSINE可能更合适，想请教一下作者是怎么考虑的。

self.search_params = {"metric_type": "L2", "params": {"nprobe": 256}}

期望行为 | Expected Behavior

No response

运行环境 | Environment

- OS:
- NVIDIA Driver:
- CUDA:
- docker:
- docker-compose:
- NVIDIA GPU:
- NVIDIA GPU Memory:

QAnything日志 | QAnything logs

No response

复现方法 | Steps To Reproduce

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备注 | Anything else?

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