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docker.md

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-# Fooocus on Docker
-
-The docker image is based on NVIDIA CUDA 12.3 and PyTorch 2.0, see [Dockerfile](Dockerfile) and [requirements_docker.txt](requirements_docker.txt) for details.
-
-## Quick start
-
-**This is just an easy way for testing. Please find more information in the [notes](#notes).**
-
-1. Clone this repository
-2. Build the image with `docker compose build`
-3. Run the docker container with `docker compose up`. Building the image takes some time.
-
-When you see the message  `Use the app with http://0.0.0.0:7865/` in the console, you can access the URL in your browser.
-
-Your models and outputs are stored in the `fooocus-data` volume, which, depending on OS, is stored in `/var/lib/docker/volumes`.
-
-## Details
-
-### Update the container manually
-
-When you are using `docker compose up` continuously, the container is not updated to the latest version of Fooocus automatically.
-Run `git pull` before executing `docker compose build --no-cache` to build an image with the latest Fooocus version.
-You can then start it with `docker compose up`
-
-### Import models, outputs
-If you want to import files from models or the outputs folder, you can uncomment the following settings in the [docker-compose.yml](docker-compose.yml):
-```
-#- ./models:/import/models   # Once you import files, you don't need to mount again.
-#- ./outputs:/import/outputs  # Once you import files, you don't need to mount again.
-```
-After running `docker compose up`, your files will be copied into `/content/data/models` and `/content/data/outputs`
-Since `/content/data` is a persistent volume folder, your files will be persisted even when you re-run `docker compose up --build` without above volume settings.
-
-
-### Paths inside the container
-
-|Path|Details|
-|-|-|
-|/content/app|The application stored folder|
-|/content/app/models.org|Original 'models' folder.<br> Files are copied to the '/content/app/models' which is symlinked to '/content/data/models' every time the container boots. (Existing files will not be overwritten.) |
-|/content/data|Persistent volume mount point|
-|/content/data/models|The folder is symlinked to '/content/app/models'|
-|/content/data/outputs|The folder is symlinked to '/content/app/outputs'|
-
-### Environments
-
-You can change `config.txt` parameters by using environment variables.
-**The priority of using the environments is higher than the values defined in `config.txt`, and they will be saved to the `config_modification_tutorial.txt`**
-
-Docker specified environments are there. They are used by 'entrypoint.sh'
-|Environment|Details|
-|-|-|
-|DATADIR|'/content/data' location.|
-|CMDARGS|Arguments for [entry_with_update.py](entry_with_update.py) which is called by [entrypoint.sh](entrypoint.sh)|
-|config_path|'config.txt' location|
-|config_example_path|'config_modification_tutorial.txt' location|
-
-You can also use the same json key names and values explained in the 'config_modification_tutorial.txt' as the environments.
-See examples in the [docker-compose.yml](docker-compose.yml)
-
-## Notes
-
-- Please keep 'path_outputs' under '/content/app'. Otherwise, you may get an error when you open the history log.
-- Docker on Mac/Windows still has issues in the form of slow volume access when you use "bind mount" volumes. Please refer to [this article](https://docs.docker.com/storage/volumes/#use-a-volume-with-docker-compose) for not using "bind mount".
-- The MPS backend (Metal Performance Shaders, Apple Silicon M1/M2/etc.) is not yet supported in Docker, see https://github.com/pytorch/pytorch/issues/81224
-- You can also use `docker compose up -d` to start the container detached and connect to the logs with `docker compose logs -f`. This way you can also close the terminal and keep the container running.