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>
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>
Previously, when a SIGINT was emitted and a model load is running,
the API didn't shut down until the load finished due to waitng for
the lock. However, when shutting down, the lock doesn't matter since
the process is being killed anyway.
Signed-off-by: kingbri <bdashore3@proton.me>
The async signal exit function should be the internal for exiting
the program. In addition, prevent the handler from being called
twice by adding a boolean. May become an asyncio event later on.
In addition, make sure to skip_wait when running model.unload.
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>
This is necessary for Kobold's API. Current models use bad_words_ids
in generation_config.json, but for some reason, they're also present
in the model's config.json.
Signed-off-by: kingbri <bdashore3@proton.me>
Some of the parameters the API provides are aliases for their OAI
equivalents. It makes more sense to move them to the common file.
Signed-off-by: kingbri <bdashore3@proton.me>
These are faster event loops for asyncio which should improve overall
performance. Gate these under an experimental flag for now to stress
test these loops.
Signed-off-by: kingbri <bdashore3@proton.me>
Add an API parameter to set the timeout in seconds. Keep it to None
by default for uninterrupted downloads.
Signed-off-by: kingbri <bdashore3@proton.me>
This prevents TimeoutErrors from showing up. However, a longer
timeout may be necessary since this is in the API. Turning it off
for now will help resolve immediate errors.
Signed-off-by: kingbri <bdashore3@proton.me>
Log all the parts of a request if the config flag is set. The logged
fields are all server side anyways, so nothing is being exposed to
clients.
Signed-off-by: kingbri <bdashore3@proton.me>
Middleware runs on both the request and response. Therefore, streaming
responses had increased latency when processing tasks and sending
data to the client which resulted in erratic streaming behavior.
Use a depends to add request IDs since it only executes when the
request is run rather than expecting the response to be sent as well.
For the future, it would be best to think about limiting the time
between each tick of chunk data to be safe.
Signed-off-by: kingbri <bdashore3@proton.me>
Identify which request is being processed to help users disambiguate
which logs correspond to which request.
Signed-off-by: kingbri <bdashore3@proton.me>
Raise a 422 exception for the disconnect. This prevents pydantic
errors when returning a "response" which doesn't contain anything
in this case.
Signed-off-by: kingbri <bdashore3@proton.me>
It's possible that tracebacks can give too much info about a system
when sent over the API. Gate this under a flag to send them only
when debugging since this feature is still useful.
Signed-off-by: kingbri <bdashore3@proton.me>
API keys are not allowed to view all the admin's models, templates,
draft models, loras, etc. Basically anything that can be viewed
on the filesystem outside of anything that's currently loaded is
not allowed to be returned unless an admin key is present.
This change helps preserve user privacy while not erroring out on
list endpoints that the OAI spec requires.
Signed-off-by: kingbri <bdashore3@proton.me>
Pass a request and internally unwrap the headers. In addition, allow
X-admin-key to get checked in an API key request.
Signed-off-by: kingbri <bdashore3@proton.me>
Move OpenAPI export as an env var within the main function. This
allows for easy export by running main.
In addition, an env variable provides global and explicit state to
disable conditional wheel imports (ex. Exl2 and torch) which caused
errors at first.
Signed-off-by: kingbri <bdashore3@proton.me>
Previously, the parameters under the "model" block in config.yml only
handled the loading of a model on startup. This meant that any subsequent
API request required each parameter to be filled out or use a sane default
(usually defaults to the model's config.json).
However, there are cases where admins may want an argument from the
config to apply if the parameter isn't provided in the request body.
To help alleviate this, add a mechanism that works like sampler overrides
where users can specify a flag that acts as a fallback.
Therefore, this change both preserves the source of truth of what
parameters the admin is loading and adds some convenience for users
that want customizable defaults for their requests.
This behavior may change in the future, but I think it solves the
issue for now.
Signed-off-by: kingbri <bdashore3@proton.me>
