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docs: update CONFIGURATION.md

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docs/features/CONFIGURATION.md
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@ -8,7 +8,15 @@ title: Configuration
Runtime settings, including the location of files and Runtime settings, including the location of files and
directories, memory usage, and performance, are managed via the directories, memory usage, and performance, are managed via the
`invokeai.yaml` config file. `invokeai.yaml` config file or environment variables. A subset
of settings may be set via commandline arguments.
Settings sources are used in this order:
- CLI args
- Environment variables
- `invokeai.yaml` settings
- Fallback: defaults
The most commonly changed settings are also accessible The most commonly changed settings are also accessible
graphically via the `invokeai-configure` script. graphically via the `invokeai-configure` script.
@ -38,19 +46,11 @@ meta:
schema_version: 4 schema_version: 4
# Put user settings here: # Put user settings here:
host: 0.0.0.0 host: 0.0.0.0 # serve the app on your local network
models_dir: /external_drive/invokeai/models models_dir: D:\invokeai\models # store models on an external drive
ram: 24 precision: float16 # always use fp16 precision
precision: float16
``` ```
In this example, we've changed a few settings:
- `host: 0.0.0.0`: allow other machines on the network to connect
- `models_dir: /external_drive/invokeai/models`: store model files here
- `ram: 24`: set the model RAM cache to a max of 24GB
- `precision: float16`: use more efficient FP16 precision
The settings in this file will override the defaults. You only need The settings in this file will override the defaults. You only need
to change this file if the default for a particular setting doesn't to change this file if the default for a particular setting doesn't
work for you. work for you.
@ -62,25 +62,19 @@ You can fix a broken `invokeai.yaml` by deleting it and running the
configuration script again -- option [6] in the launcher, "Re-run the configuration script again -- option [6] in the launcher, "Re-run the
configure script". configure script".
<!-- TODO(psyche): support env vars? ### Environment Variables
#### Reading Environment Variables
Next InvokeAI looks for defined environment variables in the format All settings may be set via environment variables by prefixing `INVOKEAI_`
`INVOKEAI_<setting_name>`, for example `INVOKEAI_port`. Environment to the variable name. For example, `INVOKEAI_HOST` would set the `host`
variable values take precedence over configuration file variables. On setting.
a Macintosh system, for example, you could change the port that the
web server listens on by setting the environment variable this way:
``` For non-primitive values, pass a JSON-encoded string:
export INVOKEAI_port=8000
invokeai-web ```sh
export INVOKEAI_REMOTE_API_TOKENS='[{"url_regex":"modelmarketplace", "token": "12345"}]'
``` ```
Please check out these We suggest using `invokeai.yaml`, as it is more user-friendly.
[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. -->
### CLI Args ### CLI Args
@ -113,15 +107,13 @@ Some model marketplaces require an API key to download models. You can provide a
The pattern can be any valid regex (you may need to surround the pattern with quotes): The pattern can be any valid regex (you may need to surround the pattern with quotes):
```yaml ```yaml
InvokeAI: remote_api_tokens:
Model Install: # Any URL containing `models.com` will automatically use `your_models_com_token`
remote_api_tokens: - url_regex: models.com
# Any URL containing `models.com` will automatically use `your_models_com_token` token: your_models_com_token
- url_regex: models.com # Any URL matching this contrived regex will use `some_other_token`
token: your_models_com_token - url_regex: '^[a-z]{3}whatever.*\.com$'
# Any URL matching this contrived regex will use `some_other_token` token: some_other_token
- url_regex: '^[a-z]{3}whatever.*\.com$'
token: some_other_token
``` ```
The provided token will be added as a `Bearer` token to the network requests to download the model files. As far as we know, this works for all model marketplaces that require authorization. The provided token will be added as a `Bearer` token to the network requests to download the model files. As far as we know, this works for all model marketplaces that require authorization.
@ -133,22 +125,18 @@ Models are hashed during installation, providing a stable identifier for models
If your models are stored on a spinning hard drive, we suggest using `blake3_single`, the single-threaded implementation. The hashes are the same, but it's much faster on spinning disks. If your models are stored on a spinning hard drive, we suggest using `blake3_single`, the single-threaded implementation. The hashes are the same, but it's much faster on spinning disks.
```yaml ```yaml
InvokeAI: hashing_algorithm: blake3_single
Model Install:
hashing_algorithm: blake3_single
``` ```
Model hashing is a one-time operation, but it may take a couple minutes to hash a large model collection. You may opt out of model hashing entirely by setting the algorithm to `random`. Model hashing is a one-time operation, but it may take a couple minutes to hash a large model collection. You may opt out of model hashing entirely by setting the algorithm to `random`.
```yaml ```yaml
InvokeAI: hashing_algorithm: random
Model Install:
hashing_algorithm: random
``` ```
Most common algorithms are supported, like `md5`, `sha256`, and `sha512`. These are typically much, much slower than `blake3`. Most common algorithms are supported, like `md5`, `sha256`, and `sha512`. These are typically much, much slower than `blake3`.
#### Paths #### Path Settings
These options set the paths of various directories and files used by These options set the paths of various directories and files used by
InvokeAI. Relative paths are interpreted relative to the root directory, so InvokeAI. Relative paths are interpreted relative to the root directory, so
@ -164,11 +152,11 @@ way you wish.
Several different log handler destinations are available, and multiple destinations are supported by providing a list: Several different log handler destinations are available, and multiple destinations are supported by providing a list:
``` ```yaml
log_handlers: log_handlers:
- console - console
- syslog=localhost - syslog=localhost
- file=/var/log/invokeai.log - file=/var/log/invokeai.log
``` ```
- `console` is the default. It prints log messages to the command-line window from which InvokeAI was launched. - `console` is the default. It prints log messages to the command-line window from which InvokeAI was launched.