lmdeploy Does Not Currently Support macOS

[Gordennn]

Step1的3行code运行完后会提示：

Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Collecting git+https://github.com/InternLM/lagent.git (from -r requirements.txt (line 4))
Cloning https://github.com/InternLM/lagent.git to /private/var/folders/hx/ppfmd7yd6472qdqzd93zqz5r0000gn/T/pip-req-build-1e1jeo3q
Running command git clone --filter=blob:none --quiet https://github.com/InternLM/lagent.git /private/var/folders/hx/ppfmd7yd6472qdqzd93zqz5r0000gn/T/pip-req-build-1e1jeo3q
Resolved https://github.com/InternLM/lagent.git to commit 47f866176b7a238f44c80ecbc0649050c52f6914
Preparing metadata (setup.py) ... error
error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [1 lines of output]
ERROR: Can not execute setup.py since setuptools is not available in the build environment.
[end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

不知道是哪里出了问题，请麻烦看下，谢谢

[Harold-lkk]

你可以先单独 pip install lagent 这个看一下日志详细的错误，然后再提供一下么

[Gordennn]

你可以先单独 pip install lagent 这个看一下日志详细的错误，然后再提供一下么

不知道为什么还是会报错，我是直接打开terminal后输入pip install lagent的

(base) gorden@GordendeMacBook-Pro ~ % pip install lagent
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Collecting lagent
Using cached https://pypi.tuna.tsinghua.edu.cn/packages/69/0a/eb31768ddd781b84bd6f855bc562348e74f5f5949ffac73847148fbf0526/lagent-0.2.3-py3-none-any.whl (78 kB)
Collecting arxiv (from lagent)
Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/7b/7bf42178d227b26d3daf94cdd22a72a4ed5bf235548c4f5aea49c51c6458/arxiv-2.1.3-py3-none-any.whl (11 kB)
Requirement already satisfied: distro in /opt/anaconda3/lib/python3.11/site-packages (from lagent) (1.8.0)
Requirement already satisfied: filelock in /opt/anaconda3/lib/python3.11/site-packages (from lagent) (3.13.1)
Collecting func-timeout (from lagent)
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/b3/0d/bf0567477f7281d9a3926c582bfef21bff7498fc0ffd3e9de21811896a0b/func_timeout-4.3.5.tar.gz (44 kB)
Preparing metadata (setup.py) ... error
error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [1 lines of output]
ERROR: Can not execute setup.py since setuptools is not available in the build environment.
[end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

[Harold-lkk]

The Mac environment does not support func-timeout due to the error.
You can remove https://github.com/InternLM/lagent/blob/47f866176b7a238f44c80ecbc0649050c52f6914/requirements/runtime.txt#L4
and install from source

[lvhan028]

BTW, the dependency "lmdeploy" doesn't support MacOS, either.
It is an inference framework developed on CUDA platform

[Gordennn]

BTW, the dependency "lmdeploy" doesn't support MacOS, either. It is an inference framework developed on CUDA platform

If that’s the case, then it seems that MindSearch cannot be deployed on a Mac :(

[lvhan028]

@Harold-lkk can MindSearch consider integration with ollama?

[obwohl]

Right now it does not seem to work on MacOS which is very sad.

[LeoLiuYan]

Is there a plan to support MacOS ?

[lvhan028]

LMDeploy has no plan to do that.
I suggest MindSearch considering to use ollama as one of the inference engine

[BoltzmannEntropy]

The bast inference server for OSX is mlc and it is very fast even on M1.

Install

python -m pip install --pre -U -f https://mlc.ai/wheels mlc-llm-nightly mlc-ai-nightly

Run the server with Mistral 7B

 mlc_llm serve HF://mlc-ai/Mistral-7B-Instruct-v0.2-q4f16_1-MLC --port 7860 --host 0.0.0.0 

Open the client UI

Access https://chat.webllm.ai/

Click settings and change the URL to localhost:7860:

Go Back to setting and you will see the single model that is now available on the server, e.g. http://localhost:7860/v1/models will output Mistral-7B-Instruct-v0.2-q4f16_1-MLC

Good luck