* fix config file loader
* prune nonetype values from config dict
fixes default values not initialising properly
* Utils: Shrink None removal function
It is more concise to use a list and dict collection if necessary
rather than iterating through and checking each value. Tested and
works with Tabby's cases.
Signed-off-by: kingbri <bdashore3@proton.me>
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Signed-off-by: kingbri <bdashore3@proton.me>
Co-authored-by: kingbri <bdashore3@proton.me>
Make it so any message role can be parsed from a list. Not really
sure why this is the case because system and assistant shouldn't be
sending data other than text, but it also doesn't make much sense
to be extremely strict with roles either.
Signed-off-by: kingbri <bdashore3@proton.me>
ExllamaV2 should check for solely exllamav2, otherwise errors don't
make sense. Migrate the combined "exl2" computed property to "inference"
since those are the required dependencies for minimal inference.
Signed-off-by: kingbri <bdashore3@proton.me>
Since the full argparser requires pydantic, gate it until all dependencies
are installed.
Also if the venv is deleted, assume that start_options.json is invalid
as well.
Signed-off-by: kingbri <bdashore3@proton.me>
The dynamic generator gave a not-so-helpful exception already which
basically said to not exceed the max sequence length. Instead of
possible undefined behavior, error out.
Signed-off-by: kingbri <bdashore3@proton.me>
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>
Update the config system to use Pydantic internally, bridging the gap between the YAML and args. YAML is still the preferred method to configure TabbyAPI, but args are no longer separately maintained.
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>
