We were stripping the file extension from file models when moving them in `_sync_model_path`. For example, `some_model.safetensors` would be moved to `some_model`, which of course breaks things.
Instead of using the model's name as the new path, use the model's path's last segment. This is the same behaviour for directories, but for files, it retains the file extension.
- If the metadata yaml has an invalid version, exist the app. If we don't, the app will crawl the models dir and add models to the db without having first parsed `models.yaml`. This should not happen often, as the vast majority of users are on v3.0.0 models.yaml files.
- Fix off-by-one error with models count (need to pop the `__metadata__` stanza
- After a successful migration, rename `models.yaml` to `models.yaml.bak` to prevent the migration logic from re-running on subsequent app startups.
The old logic to check if a model needed to be moved relied on the model path being a relative path. Paths are now absolute, causing this check to fail. We then assumed the paths were different and moved the model from its current location to, well, its current location.
Use more resilient method to check if a model should be moved.
mkdocs can autogenerate python class docs from its docstrings. Our config is a pydantic model.
It's tedious and error-prone to duplicate docstrings from the pydantic field descriptions to the class docstrings.
- Add helper function to generate a mkdocs-compatible docstring from the InvokeAIAppConfig class fields
A list of regex and token pairs is accepted. As a file is downloaded by the model installer, the URL is tested against the provided regex/token pairs. The token for the first matching regex is used during download, added as a bearer token.
When we change a model image, its URL remains the same. The browser will aggressively cache the image. The easiest way to fix this is to append a random query parameter to the URL whenever we build a model config in the API.
