There's no native way to handle case insensitivity in pydantic, so
add a validator which converts the API server input to be lowercase.
Signed-off-by: kingbri <bdashore3@proton.me>
Loaders that read use a safe type while loaders that write use both
round-trip and safe options.
Also don't create module-level parsers where they're not needed.
Signed-off-by: kingbri <bdashore3@proton.me>
The loader takes in the "draft" parameter, so map the config model
to that when creating kwargs for initial load.
Also map the old "draft" key to the new "draft_model" key.
Signed-off-by: kingbri <bdashore3@proton.me>
This is not ideal because users may still have trouble understanding
what a lora includes, but adding an example comment will help instead
of leaving a blank line.
Signed-off-by: kingbri <bdashore3@proton.me>
- Let the user know that migration is going to be attempted
- Have a more informative error message if auto-migration fails
- Revert back to the old config file on failure
- Don't load with a partially parsed config
Signed-off-by: kingbri <bdashore3@proton.me>
If a sub-field exists in the model provided to the file generator,
use it. Otherwise always fallback to the default factory. This prevents
any subsequent errors from setting None.
Signed-off-by: kingbri <bdashore3@proton.me>
It makes sense for the LLM model groups to be clustered around
each other with the least used groups towards the bottom.
Signed-off-by: kingbri <bdashore3@proton.me>
These changes fix the amount and order of newlines to look pleasing
for the user. However, the changes used in here are kind of hacky
and need a proper fix that can contain the same level of efficiency.
Signed-off-by: kingbri <bdashore3@proton.me>
Remove access of private attributes and use safer functions. Also
move generalized functions into utils files.
Signed-off-by: kingbri <bdashore3@proton.me>
There are two ways to load a model:
1. Via the load endpoint
2. Inline with a completion
The defaults were not applying on the inline load, so rewrite to fix
that. However, while doing this, set up a defaults dictionary rather
than comparing it at runtime and remove the pydantic default lambda
on all the model load fields.
This makes the code cleaner and establishes a clear config tree for
loading models.
Signed-off-by: kingbri <bdashore3@proton.me>
