- Remove OmegaConf. It functioned as an intermediary data format, between YAML/argparse and pydantic. It's not necessary - we can parse YAML or CLI args directly with pydantic.
- Remove dynamic CLI args. Only `root` is explicitly supported. This greatly simplifies config handling. Configuration is done by editing the YAML file. Frequently-used args can be added if there is a demand.
- A separate arg parser is created to handle the slimmed-down CLI args. It's run immediately in the `invokeai-web` script to handle `--version` and `--help`. It is also used inside the singleton config getter (see below).
- Remove categories from the config. Our settings model is mostly flat. Handling categories adds complexity for both us and users - we have to handle transforming a flat config to categorized config (and vice-versa), while users have to be careful with indentation in their YAML file.
- Add a `meta` key to the config file. Currently, this holds the config schema version only. It is not a part of the config object itself.
- Remove legacy settings that are no longer referenced, or were effectively no-op settings when referenced in code.
- Implement simple migration logic to for v3 configs. If migration is successful, the v3 config file is backed up to `invokeai.yaml.bak` and the new config written to `invokeai.yaml`.
- Previously, the singleton config was accessed by calling `InvokeAIAppConfig.get_config()`. This returned an instance of `InvokeAIAppConfig`, which _also_ has the `get_config` function. This created to a confusing situation where you weren't sure if you needed to call `get_config` or just use the config object. This method is replaced by a standalone `get_config` function which returns a singleton config object.
- Wrap CLI arg parsing (for `root`) and loading/migrating `invokeai.yaml` into the new `get_config()` function.
- Move `generate_config_docstrings` into standalone utility function.
- Make `root` a private attr (`_root`). This reduces the temptation to directly modify and or use this sensitive field and ensures it is neither serialized nor read from input data. Use `root_path` to access the resolved root path, or `set_root` to set the root to something.
* allow removal of models with legacy relative path addressing
* added five controlnet models for sdxl to INITIAL_MODELS
---------
Co-authored-by: Lincoln Stein <lstein@gmail.com>
- No longer install core conversion models. Use the HuggingFace cache to load
them if and when needed.
- Call directly into the diffusers library to perform conversions with only shallow
wrappers around them to massage arguments, etc.
- At root configuration time, do not create all the possible model subdirectories,
but let them be created and populated at model install time.
- Remove checks for missing core conversion files, since they are no
longer installed.
In the client, a controlnet or t2i adapter has two images:
- The source control image: the image the user selected (required)
- The processed control image: the user's image after we've processed it (optional)
The processed image is optional because a user may provide a pre-processed image.
We only actually use one of these images when building the graph, and until this change, we only stored one of the in image metadata. This created a situation where only a processed image was stored in metadata - say, a canny edge map - and the user-selected image wasn't provided.
By adding the processed image to metadata, we can recall both the control image and optional processed image.
This commit is followed by a UI-facing changes to support the change.
- This adds additional logic to the safetensors->diffusers conversion script
to check for and install missing core conversion models at runtime.
- Fixes#5934
BLAKE3 has poor performance on spinning disks when parallelized. See https://github.com/BLAKE3-team/BLAKE3/issues/31
- Replace `skip_model_hash` setting with `hashing_algorithm`. Any algorithm we support is accepted.
- Add `random` algorithm: hashes a UUID with BLAKE3 to create a random "hash". Equivalent to the previous skip functionality.
- Add `blake3_single` algorithm: hashes on a single thread using BLAKE3, fixes the aforementioned performance issue
- Update model probe to accept the algorithm to hash with as an optional arg, defaulting to `blake3`
- Update all calls of the probe to use the app's configured hashing algorithm
- Update an external script that probes models
- Update tests
- Move ModelHash into its own module to avoid circuclar import issues
This script removes unused translations from the `en.json` source translation file:
- Parse `en.json` to build a list of all keys, e.g. `controlnet.depthAnything`
- Check every frontend file for every key
- If the key is not found, it is removed from the translation file
- Exact matches (e.g. `controlnet.depthAnything`) and stem matches (e.g. `depthAnything`) are ignored