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Updated at January 28, 2026

class yandex_ai_studio_sdk._chat.completions.function.ChatCompletions

A class for working with chat completions models.

This class provides the core functionality for creating chat model instances and managing completions. It handles model URI construction and provides methods for listing available models.

list(*, timeout=60, filters=None)

Returns all available models in selected subdomain (completions, embeddings, etc)

Parameters

  • timeout (float) – The timeout, or the maximum time to wait for the request to complete in seconds.
  • filters (ModelFilter | None) – Optional dict with filters, where keys are model attribute names and values are the desired values.

Return type

tuple[ChatModel, …]

 
>>> filters = {'owner': 'alice', 'version': 'v2', 'fine_tuned': True}

__call__(model_name, *, model_version='latest')

Create a model instance in selected chat subdomain (completions, embeddings, etc)

Constructs the model URI based on the provided name and version. If the name contains ‘://’, it is treated as a full URI. Otherwise constructs a URI in the form ‘gpt://<folder_id>//’.

Parameters

  • model_name (str) – The name or URI of the model.
  • model_version (str) – The version of the model to use. Defaults to ‘latest’.

Return type

ModelTypeT

Model

class yandex_ai_studio_sdk._chat.completions.model.ChatModel

A class for working with chat models providing inference functionality.

This class provides the foundation for chat model implementations, handling configuration, request building, and response processing.

run(messages, *, timeout=180)

Executes the model with the provided messages.

Parameters

Return type

ChatModelResult[ToolCall]

run_stream(messages, *, timeout=180)

Executes the model with the provided messages and yields partial results as they become available.

Parameters

Return type

Iterator[ChatModelResult[ToolCall]]

property config: ConfigTypeT

configure(*, temperature=Undefined, max_tokens=Undefined, reasoning_mode=Undefined, response_format=Undefined, tools=Undefined, parallel_tool_calls=Undefined, tool_choice=Undefined, extra_query=Undefined)

Configure the model with specified parameters.

Parameters

  • temperature (UndefinedOr[float] | None) – Sampling temperature (0-1). Higher values produce more random results.
  • max_tokens (UndefinedOr[int] | None) – Maximum number of tokens to generate in the response.
  • reasoning_mode (UndefinedOr[ChatReasoningModeType] | None) – Reasoning mode for internal processing before responding.
  • response_format (UndefinedOr[ResponseType] | None) – Format of the response (JsonSchema, JSON string, or pydantic model). See structured output documentation_BaseChatModel_URL.
  • tools (UndefinedOr[Sequence[CompletionTool] | CompletionTool]) – Tools available for completion. Can be a sequence or single tool.
  • parallel_tool_calls (UndefinedOr[bool]) – Whether to allow parallel tool calls. Defaults to ‘true’.
  • tool_choice (UndefinedOr[ToolChoiceType]) – Strategy for tool selection. There are several ways to configure tool_choice for query processing: - no tools to call (tool_choice='none'); - required to call any tool (tool_choice='required'); - call a specific tool (tool_choice={'type': 'function', 'function': {'name': 'another_calculator'}} or directly passing a tool object).
  • extra_query (UndefinedOr[QueryType]) – Additional experimental model parameters.

Return type

Self

property fine_tuned: bool | None

property name: str | None

property owner: str | None

property uri: str

property version: str | None