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InvokeAI/docs/features/CONFIGURATION.md
Lincoln Stein 6073cb8020 add documentation on the configuration system
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---
title: Configuration
---
# :material-tune-variant: InvokeAI Configuration
## Intro
InvokeAI has numerous runtime settings which can be used to adjust
many aspects of its operations, including the location of files and
directories, memory usage, and performance. These settings can be
viewed and customized in several ways:
1. By editing settings in the `invokeai.yaml` file.
2. By setting environment variables.
3. On the command-line, when InvokeAI is launched.
In addition, the most commonly changed settings are accessible
graphically via the `invokeai-configure` script.
### How the Configuration System Works
When InvokeAI is launched, the very first thing it needs to do is to
find its "root" directory, which contains its configuration files,
installed models, its database of images, and the folder(s) of
generated images themselves. In this document, the root directory will
be referred to as ROOT.
#### Finding the Root Directory
To find its root directory, InvokeAI uses the following recipe:
1. It first looks for the argument `--root <path>` on the command line
it was launched from, and uses the indicated path if present.
2. Next it looks for the environment variable INVOKEAI_ROOT, and uses
the directory path found there if present.
3. If neither of these are present, then InvokeAI looks for the
folder containing the `.venv` Python virtual environment directory for
the currently active environment. This directory is checked for files
expected inside the InvokeAI root before it is used.
4. Finally, InvokeAI looks for a directory in the current user's home
directory named `invokeai`.
#### Reading the InvokeAI Configuration File
Once the root directory has been located, InvokeAI looks for a file
named `ROOT/invokeai.yaml`, and if present reads configuration values
from it. The top of this file looks like this:
```
InvokeAI:
Web Server:
host: localhost
port: 9090
allow_origins: []
allow_credentials: true
allow_methods:
- '*'
allow_headers:
- '*'
Features:
esrgan: true
internet_available: true
log_tokenization: false
nsfw_checker: false
patchmatch: true
restore: true
...
```
This lines in this file are used to establish default values for
Invoke's settings. In the above fragment, the Web Server's listening
port is set to 9090 by the `port` setting.
You can edit this file with a text editor such as "Notepad" (do not
use Word or any other word processor). When editing, be careful to
maintain the indentation, and do not add extraneous text, as syntax
errors will prevent InvokeAI from launching. A basic guide to the
format of YAML files can be found
[here](https://circleci.com/blog/what-is-yaml-a-beginner-s-guide/).
You can fix a broken `invokeai.yaml` by deleting it and running the
configuration script again -- option [7] in the launcher, "Re-run the
configure script".
#### Reading Environment Variables
Next InvokeAI looks for defined environment variables in the format
`INVOKEAI_<setting_name>`, for example `INVOKEAI_port`. Environment
variable values take precedence over configuration file variables. On
a Macintosh system, for example, you could change the port that the
web server listens on by setting the environment variable this way:
```
export INVOKEAI_port=8000
invokeai-web
```
Please check out these
[Macintosh](https://phoenixnap.com/kb/set-environment-variable-mac)
and
[Windows](https://phoenixnap.com/kb/windows-set-environment-variable)
guides for setting temporary and permanent environment variables.
#### Reading the Command Line
Lastly, InvokeAI takes settings from the command line, which override
everything else. The command-line settings have the same name as the
corresponding configuration file settings, preceded by a `--`, for
example `--port 8000`.
If you are using the launcher (`invoke.sh` or `invoke.bat`) to launch
InvokeAI, then just pass the command-line arguments to the launcher:
```
invoke.bat --port 8000 --host 0.0.0.0
```
The arguments will be applied when you select the web server option
(and the other options as well).
If, on the other hand, you prefer to launch InvokeAI directly from the
command line, you would first activate the virtual environment (known
as the "developer's console" in the launcher), and run `invokeai-web`:
```
> C:\Users\Fred\invokeai\.venv\scripts\activate
(.venv) > invokeai-web --port 8000 --host 0.0.0.0
```
You can get a listing and brief instructions for each of the
command-line options by giving the `--help` argument:
```
(.venv) > invokeai-web --help
usage: InvokeAI [-h] [--host HOST] [--port PORT] [--allow_origins [ALLOW_ORIGINS ...]] [--allow_credentials | --no-allow_credentials]
[--allow_methods [ALLOW_METHODS ...]] [--allow_headers [ALLOW_HEADERS ...]] [--esrgan | --no-esrgan]
[--internet_available | --no-internet_available] [--log_tokenization | --no-log_tokenization]
[--nsfw_checker | --no-nsfw_checker] [--patchmatch | --no-patchmatch] [--restore | --no-restore]
[--always_use_cpu | --no-always_use_cpu] [--free_gpu_mem | --no-free_gpu_mem] [--max_cache_size MAX_CACHE_SIZE]
[--max_vram_cache_size MAX_VRAM_CACHE_SIZE] [--precision {auto,float16,float32,autocast}]
[--sequential_guidance | --no-sequential_guidance] [--xformers_enabled | --no-xformers_enabled]
[--tiled_decode | --no-tiled_decode] [--root ROOT] [--autoimport_dir AUTOIMPORT_DIR] [--lora_dir LORA_DIR]
[--embedding_dir EMBEDDING_DIR] [--controlnet_dir CONTROLNET_DIR] [--conf_path CONF_PATH] [--models_dir MODELS_DIR]
[--legacy_conf_dir LEGACY_CONF_DIR] [--db_dir DB_DIR] [--outdir OUTDIR] [--from_file FROM_FILE]
[--use_memory_db | --no-use_memory_db] [--model MODEL] [--log_handlers [LOG_HANDLERS ...]]
[--log_format {plain,color,syslog,legacy}] [--log_level {debug,info,warning,error,critical}]
...
```
## The Configuration Settings
The configuration settings are divided into several distinct
groups in `invokeia.yaml`:
### Web Server
| Setting | Default Value | Description |
|----------|----------------|--------------|
| `host` | `localhost` | Name or IP address of the network interface that the web server will listen on |
| `port` | `9090` | Network port number that the web server will listen on |
| `allow_origins` | `[]` | A list of host names or IP addresses that are allowed to connect to the InvokeAI API in the format `['host1','host2',...]` |
| `allow_credentials | `true` | Require credentials for a foreign host to access the InvokeAI API (don't change this) |
| `allow_methods` | `*` | List of HTTP methods ("GET", "POST") that the web server is allowed to use when accessing the API |
| `allow_headers` | `*` | List of HTTP headers that the web server will accept when accessing the API |
The documentation for InvokeAI's API can be accessed by browsing to the following URL: [http://localhost:9090/docs].
### Features
These configuration settings allow you to enable and disable various InvokeAI features:
| Setting | Default Value | Description |
|----------|----------------|--------------|
| `esrgan` | `true` | Activate the ESRGAN upscaling options|
| `internet_available` | `true` | When a resource is not available locally, try to fetch it via the internet |
| `log_tokenization` | `false` | Before each text2image generation, print a color-coded representation of the prompt to the console; this can help understand why a prompt is not working as expected |
| `nsfw_checker` | `true` | Activate the NSFW checker to blur out risque images |
| `patchmatch` | `true` | Activate the "patchmatch" algorithm for improved inpainting |
| `restore` | `true` | Activate the facial restoration features (DEPRECATED; restoration features will be removed in 3.0.0) |
### Memory/Performance
These options tune InvokeAI's memory and performance characteristics.
| Setting | Default Value | Description |
|----------|----------------|--------------|
| `always_use_cpu` | `false` | Use the CPU to generate images, even if a GPU is available |
| `free_gpu_mem` | `false` | Aggressively free up GPU memory after each operation; this will allow you to run in low-VRAM environments with some performance penalties |
| `max_cache_size` | `6` | Amount of CPU RAM (in GB) to reserve for caching models in memory; more cache allows you to keep models in memory and switch among them quickly |
| `max_vram_cache_size` | `2.75` | Amount of GPU VRAM (in GB) to reserve for caching models in VRAM; more cache speeds up generation but reduces the size of the images that can be generated. This can be set to zero to maximize the amount of memory available for generation. |
| `precision` | `auto` | Floating point precision. One of `auto`, `float16` or `float32`. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system |
| `sequential_guidance` | `false` | Calculate guidance in serial rather than in parallel, lowering memory requirements at the cost of some performance loss |
| `xformers_enabled` | `true` | If the x-formers memory-efficient attention module is installed, activate it for better memory usage and generation speed|
| `tiled_decode` | `false` | If true, then during the VAE decoding phase the image will be decoded a section at a time, reducing memory consumption at the cost of a performance hit |
### Paths
These options set the paths of various directories and files used by
InvokeAI. Relative paths are interpreted relative to INVOKEAI_ROOT, so
if INVOKEAI_ROOT is `/home/fred/invokeai` and the path is
`autoimport/main`, then the corresponding directory will be located at
`/home/fred/invokeai/autoimport/main`.
| Setting | Default Value | Description |
|----------|----------------|--------------|
| `autoimport_dir` | `autoimport/main` | At startup time, read and import any main model files found in this directory |
| `lora_dir` | `autoimport/lora` | At startup time, read and import any LoRA/LyCORIS models found in this directory |
| `embedding_dir` | `autoimport/embedding` | At startup time, read and import any textual inversion (embedding) models found in this directory |
| `controlnet_dir` | `autoimport/controlnet` | At startup time, read and import any ControlNet models found in this directory |
| `conf_path` | `configs/models.yaml` | Location of the `models.yaml` model configuration file |
| `models_dir` | `models` | Location of the directory containing models installed by InvokeAI's model manager |
| `legacy_conf_dir` | `configs/stable-diffusion` | Location of the directory containing the .yaml configuration files for legacy checkpoint models |
| `db_dir` | `databases` | Location of the directory containing InvokeAI's image, schema and session database |
| `outdir` | `outputs` | Location of the directory in which the gallery of generated and uploaded images will be stored |
| `use_memory_db` | `false` | Keep database information in memory rather than on disk; this will not preserve image gallery information across restarts |
Note that the autoimport directories will be searched recursively,
allowing you to organize the models into folders and subfolders in any
way you wish. In addition, while we have split up autoimport
directories by the type of model they contain, this isn't
necessary. You can combine different model types in the same folder
and InvokeAI will figure out what they are. So you can easily use just
one autoimport directory by commenting out the unneeded paths:
```
Paths:
autoimport_dir: autoimport
# lora_dir: null
# embedding_dir: null
# controlnet_dir: null
```
### Logging
These settings control the information, warning, and debugging
messages printed to the console log while InvokeAI is running:
| Setting | Default Value | Description |
|----------|----------------|--------------|
| `log_handlers` | `console` | This controls where log messages are sent, and can be a list of one or more destinations. Values include `console`, `file`, `syslog` and `http`. These are described in more detail below |
| `log_format` | `color` | This controls the formatting of the log messages. Values are `plain`, `color`, `legacy` and `syslog` |
| `log_level` | `debug` | This filters messages according to the level of severity and can be one of `debug`, `info`, `warning`, `error` and `critical`. For example, setting to `warning` will display all messages at the warning level or higher, but won't display "debug" or "info" messages |
Several different log handler destinations are available, and multiple destinations are supported by providing a list:
```
log_handlers:
- console
- syslog=localhost
- file=/var/log/invokeai.log
```
* `console` is the default. It prints log messages to the command-line window from which InvokeAI was launched.
* `syslog` is only available on Linux and Macintosh systems. It uses
the operating system's "syslog" facility to write log file entries
locally or to a remote logging machine. `syslog` offers a variety
of configuration options:
```
syslog=/dev/log` - log to the /dev/log device
syslog=localhost` - log to the network logger running on the local machine
syslog=localhost:512` - same as above, but using a non-standard port
syslog=fredserver,facility=LOG_USER,socktype=SOCK_DRAM`
- Log to LAN-connected server "fredserver" using the facility LOG_USER and datagram packets.
```
* `http` can be used to log to a remote web server. The server must be
properly configured to receive and act on log messages. The option
accepts the URL to the web server, and a `method` argument
indicating whether the message should be submitted using the GET or
POST method.
```
http=http://my.server/path/to/logger,method=POST
```
The `log_format` option provides several alternative formats:
* `color` - default format providing time, date and a message, using text colors to distinguish different log severities
* `plain` - same as above, but monochrome text only
* `syslog` - the log level and error message only, allowing the syslog system to attach the time and date
* `legacy` - a format similar to the one used by the legacy 2.3 InvokeAI releases.
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