use_as_default was not being properly applied into model overrides.
For compartmentalization's sake, apply all overrides in a single function
to avoid clutter.
In addition, fix where the traditional /v1/model/load endpoint checks
for draft options. These can be applied via an inline config, so let
any failures fallthrough.
Signed-off-by: kingbri <8082010+kingbri1@users.noreply.github.com>
The props endpoint is a standard used by llamacpp APIs which returns
various properties of a model to a server. It's still recommended to
use /v1/model to get all the parameters a TabbyAPI model has.
Also include the contents of a prompt template when fetching the current
model.
Signed-off-by: kingbri <8082010+bdashore3@users.noreply.github.com>
Previously, the flow for parsing chat completion messages and rendering
from the prompt template was disconnected between endpoints. Now, create
a common function to render and handle everything appropriately afterwards.
Signed-off-by: kingbri <bdashore3@proton.me>
* More robust checks for OAI chat completion message lists on /v1/encode endpoint
* Added TODO to support other aspects of chat completions
* Fix oversight where embeddings was not defined in advance on /v1/chat/completions endpoint
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>
* 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>
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>
* 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
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>
Place OAI specific routes in the appropriate folder. This is in
preperation for adding new API servers that can be optionally enabled.
Signed-off-by: kingbri <bdashore3@proton.me>
