merge from main and run precommit again

This commit is contained in:
Ashwin Bharambe 2025-10-22 12:17:48 -07:00
parent 13450c1a68
commit 678978a2c9

View file

@ -350,146 +350,46 @@ paths:
in: query in: query
description: >- description: >-
An item ID to list items after, used in pagination. An item ID to list items after, used in pagination.
required: true required: false
schema: schema:
oneOf: type: string
- type: string
- type: object
title: NotGiven
description: >-
A sentinel singleton class used to distinguish omitted keyword arguments
from those passed in with the value None (which may have different
behavior).
For example:
```py
def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response:
...
get(timeout=1) # 1s timeout
get(timeout=None) # No timeout
get() # Default timeout behavior, which may not be statically known
at the method definition.
```
- name: include - name: include
in: query in: query
description: >- description: >-
Specify additional output data to include in the response. Specify additional output data to include in the response.
required: true required: false
schema: schema:
oneOf: type: array
- type: array items:
items: type: string
type: string enum:
enum: - web_search_call.action.sources
- code_interpreter_call.outputs - code_interpreter_call.outputs
- computer_call_output.output.image_url - computer_call_output.output.image_url
- file_search_call.results - file_search_call.results
- message.input_image.image_url - message.input_image.image_url
- message.output_text.logprobs - message.output_text.logprobs
- reasoning.encrypted_content - reasoning.encrypted_content
- type: object title: ConversationItemInclude
title: NotGiven description: >-
description: >- Specify additional output data to include in the model response.
A sentinel singleton class used to distinguish omitted keyword arguments
from those passed in with the value None (which may have different
behavior).
For example:
```py
def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response:
...
get(timeout=1) # 1s timeout
get(timeout=None) # No timeout
get() # Default timeout behavior, which may not be statically known
at the method definition.
```
- name: limit - name: limit
in: query in: query
description: >- description: >-
A limit on the number of objects to be returned (1-100, default 20). A limit on the number of objects to be returned (1-100, default 20).
required: true required: false
schema: schema:
oneOf: type: integer
- type: integer
- type: object
title: NotGiven
description: >-
A sentinel singleton class used to distinguish omitted keyword arguments
from those passed in with the value None (which may have different
behavior).
For example:
```py
def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response:
...
get(timeout=1) # 1s timeout
get(timeout=None) # No timeout
get() # Default timeout behavior, which may not be statically known
at the method definition.
```
- name: order - name: order
in: query in: query
description: >- description: >-
The order to return items in (asc or desc, default desc). The order to return items in (asc or desc, default desc).
required: true required: false
schema: schema:
oneOf: type: string
- type: string enum:
enum: - asc
- asc - desc
- desc
- type: object
title: NotGiven
description: >-
A sentinel singleton class used to distinguish omitted keyword arguments
from those passed in with the value None (which may have different
behavior).
For example:
```py
def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response:
...
get(timeout=1) # 1s timeout
get(timeout=None) # No timeout
get() # Default timeout behavior, which may not be statically known
at the method definition.
```
deprecated: false deprecated: false
post: post:
responses: responses:
@ -6482,6 +6382,7 @@ components:
enum: enum:
- llm - llm
- embedding - embedding
- rerank
title: ModelType title: ModelType
description: >- description: >-
Enumeration of supported model types in Llama Stack. Enumeration of supported model types in Llama Stack.
@ -13585,13 +13486,16 @@ tags:
embeddings. embeddings.
This API provides the raw interface to the underlying models. Two kinds of models This API provides the raw interface to the underlying models. Three kinds of
are supported: models are supported:
- LLM models: these models generate "raw" and "chat" (conversational) completions. - LLM models: these models generate "raw" and "chat" (conversational) completions.
- Embedding models: these models generate embeddings to be used for semantic - Embedding models: these models generate embeddings to be used for semantic
search. search.
- Rerank models: these models reorder the documents based on their relevance
to a query.
x-displayName: Inference x-displayName: Inference
- name: Inspect - name: Inspect
description: >- description: >-