Plugin initialization fails, causing models to be unavailable. How should I troubleshoot this?

[gptmaas]

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Plugin initialization fails, causing models to be unavailable. How should I troubleshoot this?

2025/12/05 16:29:37 full_duplex.go:65: [ERROR]init environment failed: failed to install dependencies: signal: killed, output: init process exited due to no activity for 120 seconds, retrying
2025/12/05 16:29:37 full_duplex.go:59: [INFO]init environment for plugin langgenius/minimax:0.0.9
2025/12/05 16:29:37 full_duplex.go:65: [ERROR]init environment failed: failed to install dependencies: signal: killed, output: init process exited due to no activity for 120 seconds, retrying
2025/12/05 16:29:37 full_duplex.go:59: [INFO]init environment for plugin langgenius/openai_api_compatible:0.0.26

[dosubot[bot]]

Hi @gptmaas! I'm Dosu and I’m helping the dify team.

The error means the plugin environment is being killed after 120 seconds of inactivity, usually while installing dependencies. This is often caused by slow network access to PyPI, large dependencies, or resource limits in Docker.

Here’s a focused troubleshooting checklist:

1. Increase the timeout for environment initialization by setting the environment variable PLUGIN_PYTHON_ENV_INIT_TIMEOUT (or PYTHON_ENV_INIT_TIMEOUT) to a higher value like 320 or 600 seconds in your docker-compose.yaml under the plugin_daemon service. Restart the container after changing this setting.
2. If dependency downloads are slow, set a PyPI mirror (e.g., PIP_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple) in your plugin_daemon environment or .env file, especially if you’re in a region with slow access to pypi.org.
3. Raise the HTTP timeout for dependency downloads by setting UV_HTTP_TIMEOUT=120 (or higher) in the plugin_daemon environment.
4. Check Docker resource limits (CPU, memory) and increase them if possible.
5. Make sure Docker networking is stable: use network_mode: host for the plugin_daemon service if you have persistent network issues, and ensure the MTU matches your host (e.g., 1450).
6. Confirm that SANDBOX_ENABLE_NETWORK=true and PLUGIN_DAEMON_URL points to the correct host (not localhost or 127.0.0.1—use host.docker.internal or your host’s LAN IP).
7. If plugin installation tasks are stuck, clear all plugin installation task records for your tenant via the admin/console dashboard or API, then reinstall the plugin.
8. If you recently upgraded or migrated Docker volumes, run the official migration commands to extract, reinstall, and migrate plugin/model data.

If you’re on an older Dify version, consider upgrading—recent releases add more granular timeout controls and better error handling for plugin initialization issues.

If the problem persists after these steps, check the plugin_daemon logs for more details and verify your network/firewall settings.
Sources:

• Plugin timeout and network troubleshooting
• Timeout config and resource limits
• Network and Docker config
• Clearing stuck install tasks
• PyPI mirror and HTTP timeout

To reply, just mention @dosu.

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