* 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>
* Model: Fix inline loading and draft key
There was a lack of foresight between the new config.yml and how
it was structured. The "draft" key became "draft_model" without updating
both the API request and inline loading keys.
For the API requests, still support "draft" as legacy, but the "draft_model"
key is preferred.
Signed-off-by: kingbri <bdashore3@proton.me>
* OAI: Add draft model dir to inline load
Was not pushed before and caused errors of the kwargs being None.
Signed-off-by: kingbri <bdashore3@proton.me>
* Model: Fix draft args application
Draft model args weren't applying since there was a reset due to how
the old override behavior worked.
Signed-off-by: kingbri <bdashore3@proton.me>
* OAI: Change embedding model load params
Use embedding_model_name to be inline with the config.
Signed-off-by: kingbri <bdashore3@proton.me>
* API: Fix parameter for draft model load
Alias name to draft_model_name.
Signed-off-by: kingbri <bdashore3@proton.me>
* API: Fix parameter for template switch
Add prompt_template_name to be more descriptive.
Signed-off-by: kingbri <bdashore3@proton.me>
* API: Fix parameter for model load
Alias name to model_name for config parity.
Signed-off-by: kingbri <bdashore3@proton.me>
* API: Add alias documentation
Signed-off-by: kingbri <bdashore3@proton.me>
---------
Signed-off-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>
When the request is cancelled, cancel the load task. In addition,
when checking if a model container exists, also check if the model
is fully loaded.
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>
Using aiofiles, there's no longer a possiblity of blocking file operations
that can hang up the event loop. In addition, partially migrate
classes to use asynchronous init instead of the normal python magic method.
The only exception is config, since that's handled in the synchonous
init before the event loop starts.
Signed-off-by: kingbri <bdashore3@proton.me>
- add models for config options
- add function to regenerate config.yml
- replace references to config with pydantic compatible references
- remove unnecessary unwrap() statements
TODO:
- auto generate env vars
- auto generate argparse
- test loading a model
The config categories can have defined separation, but preserve
the dynamic nature of adding new config options by making all the
internal class vars as dictionaries.
This was necessary since storing global callbacks stored a state
of the previous global_config var that wasn't populated.
Signed-off-by: kingbri <bdashore3@proton.me>
If a user requesting a model change isn't admin, error.
Better to place the load function before the generate functions.
Signed-off-by: kingbri <bdashore3@proton.me>
Using "auto" for rope alpha removes ambiguity on how to explicitly
enable automatic rope calculation. The same behavior of None -> auto
calculate still exists, but can be overwritten if a model's tabby_config.yml
includes `rope_alpha`.
Signed-off-by: kingbri <bdashore3@proton.me>
It's best to pass them down the config stack.
API/User config.yml -> model config.yml -> model config.json -> fallback.
Doing this allows for seamless flow and yielding control to each
member in the stack.
Signed-off-by: kingbri <bdashore3@proton.me>
Storing a pathlib type makes it easier to manipulate the model
directory path in the long run without constantly fetching it
from the config.
Signed-off-by: kingbri <bdashore3@proton.me>
* Add healthcheck
- localhost only /healthcheck endpoint
- cURL healthcheck in docker compose file
* Update Healthcheck Response
- change endpoint to /health
- remove localhost restriction
- add docstring
* move healthcheck definition to top of the file
- make the healthcheck show up first in the openAPI spec
* Tree: Format
Use the tensor parallel loader when the flag is enabled. The new loader
has its own autosplit implementation, so gpu_split_auto isn't valid
here.
Also make it easier to determine which cache type to use rather than
multiple if/else statements.
Signed-off-by: kingbri <bdashore3@proton.me>
Metadata is generated via a template's module. This requires a single
iteration through the template. If a template tries to access a passed
variable that doesn't exist, it will error.
Therefore, generate the metadata at runtime to prevent these errors
from happening. To optimize further, cache the metadata after the
first generation to prevent the expensive call of making a template
module.
Signed-off-by: kingbri <bdashore3@proton.me>
* returning stop str if exists from gen
* added chat template for firefunctionv2
* pulling tool vars from template
* adding parsing for tool inputs/outputs
* passing tool data from endpoint to chat template, adding tool_start to the stop list
* loosened typing on the response tool call, leaning more on the user supplying a quality schema if they want a particular format
* non streaming generation prototype
* cleaning template
* Continued work with type, ingestion into template, and chat template for fire func
* Correction - streaming toolcall comes back as delta obj not inside chatcomprespchoice per chat_completion_chunk.py inside OAI lib.
* Ruff Formating
* Moved stop string and tool updates out of prompt creation func
Updated tool pydantic to match OAI
Support for streaming
Updated generate tool calls to use flag within chat_template and insert tool reminder
* Llama 3.1 chat templates
Updated fire func template
* renamed llama3.1 to chatml_with_headers..
* update name of template
* Support for calling a tool start token rather than the string.
Simplified tool_params
Warning when gen_settings are being overidden becuase user set temp to 0
Corrected schema and tools to correct types for function args. Str for some reason
* draft groq tool use model template
* changed headers to vars for readablity (but mostly because some models are weird about newlines after headers, so this is an easier way to change globally)
* Clean up comments and code in chat comp
* Post processed tool call to meet OAI spec rather than forcing model to write json in a string in the middle of the call.
* changes example back to args as json rather than string of json
* Standardize chat templates to each other
* cleaning/rewording
* stop elements can also be ints (tokens)
* Cleaning/formatting
* added special tokens for tools and tool_response as specified in description
* Cleaning
* removing aux templates - going to live in llm-promp-templates repo instead
* Tree: Format
Signed-off-by: kingbri <bdashore3@proton.me>
* Chat Completions: Don't include internal tool variables in OpenAPI
Use SkipJsonSchema to supress inclusion with the OpenAPI JSON. The
location of these variables may need to be changed in the future.
Signed-off-by: kingbri <bdashore3@proton.me>
* Templates: Deserialize metadata on template load
Since we're only looking for specific template variables that are
static in the template, it makes more sense to render when the template
is initialized.
Signed-off-by: kingbri <bdashore3@proton.me>
* Tools: Fix comments
Adhere to the format style of comments in the rest of the project.
Signed-off-by: kingbri <bdashore3@proton.me>
---------
Co-authored-by: Ben Gitter <gitterbd@gmail.com>
Signed-off-by: kingbri <bdashore3@proton.me>
Embedding models are managed on a separate backend, but are run
in parallel with the model itself. Therefore, manage this in a separate
container with separate routes.
Signed-off-by: kingbri <bdashore3@proton.me>
Use Infinity as a separate backend and handle the model within the
common module. This separates out the embeddings model from the endpoint
which allows for model loading/unloading in core.
Signed-off-by: kingbri <bdashore3@proton.me>
Infinity-emb is an async batching engine for embeddings. This is
preferable to sentence-transformers since it handles scalable usecases
without the need for external thread intervention.
Signed-off-by: kingbri <bdashore3@proton.me>
