Model Virtual Environments#

Note

New added in v1.5.0.

Background#

Some models are no longer maintained after their release, and the versions of the libraries they depend on remain outdated. For example, the GOT-OCR2 model still relies on transformers version 4.37.2. If this library is updated to a newer version, the model can no longer function properly. On the other hand, many newer models require the latest version of transformers. This version mismatch leads to dependency conflicts.

Solution#

To address this issue, we have introduced the Model Virtual Environment feature.

Install requirements for this functionality via

# all
pip install 'xinference[all]'
# or virtualenv
pip install 'xinference[virtualenv]'

Enable by setting environment variable XINFERENCE_ENABLE_VIRTUAL_ENV=1.

Example usage:

# For command line
XINFERENCE_ENABLE_VIRTUAL_ENV=1 xinference-local ...

# For Docker
docker run -e XINFERENCE_ENABLE_VIRTUAL_ENV=1 ...

Warning

This feature requires internet access or a self-hosted PyPI mirror.

Xinference will by default inherit the config for current pip.

Note

The model virtual environment feature is disabled by default (i.e., XINFERENCE_ENABLE_VIRTUAL_ENV is set to 0).

It will be enabled by default starting from Xinference v2.0.0.

When enabled, Xinference will automatically create a dedicated virtual environment for each model when it is loaded, and install its specific dependencies there. This prevents dependency conflicts between models, allowing them to run in isolation without affecting one another.

Supported Models#

Currently, this feature supports the following models:

Storage Location#

By default, the model’s virtual environment is stored under path: