* Support image_url inputs containing URLs or base64 strings following OAI vision spec
* Use async lru cache for image embeddings
* Add generic wrapper class for multimodal embeddings
If an API key sends a dummy model, it shouldn't error as the server
is catering to clients that expect specific OAI model names. This
is a problem with inline model loading since these names would error
by default. Therefore, add an exception if the provided name is in the
dummy model names (which also doubles as inline strict exceptions).
However, the dummy model names weren't configurable, so add a new
option to specify exception names, otherwise the default is gpt-3.5-turbo.
Signed-off-by: kingbri <bdashore3@proton.me>
Adds the ability to load vision parts of text + image models. Requires
an explicit flag in config because there isn't a way to automatically
determine whether the vision tower should be used.
Signed-off-by: kingbri <bdashore3@proton.me>
* improve validation
* remove to_gen_params functions
* update changes for all endpoint types
* OAI: Fix calls to generation
Chat completion and completion need to have prompt split out before
pushing to the backend.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Convert Top-K values of -1 to 0
Some OAI implementations use -1 as disabled instead of 0. Therefore,
add a coalesce case.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Format and space out
Make the code more readable.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Fix mirostat
Field items are nested in data within a Pydantic FieldInfo
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Format
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Fix banned_tokens and allowed_tokens conversion
If the provided string has whitespace, trim it before splitting.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Add helpful log to dry_sequence_breakers
Let the user know if the sequence errors out.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Apply validators in right order
Validators need to be applied in order from top to bottom, this is why
the after validator was not being applied properly.
Set the model to validate default params for sampler override purposes.
This can be turned off if there are unclear errors.
Signed-off-by: kingbri <bdashore3@proton.me>
* Endpoints: Format
Cleanup and semantically fix field validators
Signed-off-by: kingbri <bdashore3@proton.me>
* Kobold: Update validators and fix parameter application
Validators on parent fields cannot see child fields. Therefore,
validate using the child fields instead and alter the parent field
data from there.
Also fix badwordsids casting.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Remove validate defaults and fix mirostat
If a user sets an override to a non-default value, that's their
own fault.
Run validator on the actual mirostat_mode parameter rather than
the alternate mirostat parameter.
Signed-off-by: kingbri <bdashore3@proton.me>
* Kobold: Rework badwordsids
Currently, this serves to ban the EOS token. All other functionality
was legacy, so remove it.
Signed-off-by: kingbri <bdashore3@proton.me>
* Model: Remove HuggingfaceConfig
This was only necessary for badwordsids. All other fields are handled
by exl2. Keep the class as a stub if it's needed again.
Signed-off-by: kingbri <bdashore3@proton.me>
* Kobold: Bump kcpp impersonation
TabbyAPI supports XTC now.
Signed-off-by: kingbri <bdashore3@proton.me>
* Sampling: Change alias to validation_alias
Reduces the probability for errors and makes the class consistent.
Signed-off-by: kingbri <bdashore3@proton.me>
* OAI: Use constraints for validation
Instead of adding a model_validator, use greater than or equal to
constraints provided by Pydantic.
Signed-off-by: kingbri <bdashore3@proton.me>
* Tree: Lint
Signed-off-by: kingbri <bdashore3@proton.me>
---------
Co-authored-by: SecretiveShell <84923604+SecretiveShell@users.noreply.github.com>
Co-authored-by: kingbri <bdashore3@proton.me>
* 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>
---------
Signed-off-by: kingbri <bdashore3@proton.me>
Co-authored-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>
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>
