Conversations

Create Conversation

conversations.create() -> Conversation

POST/v1/conversations/

List Conversations

conversations.list() -> ConversationListResponse

GET/v1/conversations/

Retrieve Conversation

conversations.retrieve() -> Conversation

GET/v1/conversations/{conversation_id}

Update Conversation

conversations.update(, ) -> Conversation

PATCH/v1/conversations/{conversation_id}

Delete Conversation

conversations.delete() -> object

DELETE/v1/conversations/{conversation_id}

Cancel Conversation

conversations.cancel(, ) -> ConversationCancelResponse

POST/v1/conversations/{conversation_id}/cancel

Recompile Conversation

conversations.recompile(, ) -> ConversationRecompileResponse

POST/v1/conversations/{conversation_id}/recompile

Fork Conversation

conversations.fork(, ) -> Conversation

POST/v1/conversations/{conversation_id}/fork

ModelsExpand Collapse

class Conversation: …

Represents a conversation on an agent for concurrent messaging.

id: str

The unique identifier of the conversation.

agent_id: str

The ID of the agent this conversation belongs to.

archived: Optional[bool]

Whether the conversation is archived.

archived_at: Optional[datetime]

Timestamp of when the conversation was archived.

formatdate-time

context_window_limit: Optional[int]

The context window limit for this conversation (overrides agent’s context window).

created_at: Optional[datetime]

The timestamp when the object was created.

formatdate-time

created_by_id: Optional[str]

The id of the user that made this object.

description: Optional[str]

A generated description of the conversation used for search and bootstrap context.

in_context_message_ids: Optional[List[str]]

The IDs of in-context messages for the conversation. Null means this field was not retrieved/hydrated for this response.

last_message_at: Optional[datetime]

Timestamp of the most recent message request sent to this conversation.

formatdate-time

last_updated_by_id: Optional[str]

The id of the user that made this object.

model: Optional[str]

The model handle for this conversation (overrides agent’s model). Format: provider/model-name.

model_settings: Optional[ModelSettings]

The model settings for this conversation (overrides agent’s model settings).

One of the following:

class OpenAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openai"]]

The type of the provider.

reasoning: Optional[Reasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsSgLangModelSettings: …

SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["sglang"]]

The type of the provider.

reasoning: Optional[ModelSettingsSgLangModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

tool_call_parser: Optional[str]

SGLang tool call parser name (for example ‘glm47’, ‘qwen25’, or ‘hermes’).

class AnthropicModelSettings: …

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["anthropic"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[Thinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GoogleAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_ai"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class GoogleVertexModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_vertex"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class AzureModelSettings: …

Azure OpenAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["azure"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class XaiModelSettings: …

xAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["xai"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsMoonshotModelSettings: …

Moonshot/Kimi model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsZaiModelSettings: …

Z.ai (ZhipuAI) model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["zai"]]

The type of the provider.

response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsZaiModelSettingsThinking]

The thinking configuration for GLM-4.5+ models.

clear_thinking: Optional[bool]

If False, preserved thinking is used (recommended for agents).

type: Optional[Literal["enabled", "disabled"]]

Whether thinking is enabled or disabled.

One of the following:

"enabled"

"disabled"

class ModelSettingsMoonshotCodingModelSettings: …

Kimi Code model configuration (Anthropic-compatible).

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot_coding"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsMoonshotCodingModelSettingsThinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GroqModelSettings: …

Groq model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["groq"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class DeepseekModelSettings: …

Deepseek model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["deepseek"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class TogetherModelSettings: …

Together AI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["together"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class BedrockModelSettings: …

AWS Bedrock model configuration.

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["bedrock"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsBasetenModelSettings: …

Baseten model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["baseten"]]

The type of the provider.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsOpenRouterModelSettings: …

OpenRouter model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openrouter"]]

The type of the provider.

response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsChatGptoAuthModelSettings: …

ChatGPT OAuth model configuration (uses ChatGPT backend API).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["chatgpt_oauth"]]

The type of the provider.

reasoning: Optional[ModelSettingsChatGptoAuthModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]

The reasoning effort level for GPT-5.x and o-series models.

One of the following:

"none"

"low"

"medium"

"high"

"xhigh"

temperature: Optional[float]

The temperature of the model.

summary: Optional[str]

A summary of the conversation.

updated_at: Optional[datetime]

The timestamp when the object was last updated.

formatdate-time

class CreateConversation: …

Request model for creating a new conversation.

context_window_limit: Optional[int]

The context window limit for this conversation (overrides agent’s context window).

description: Optional[str]

A generated description of the conversation used for search and bootstrap context.

hidden: Optional[bool]

Whether the new conversation should be hidden from listings.

model: Optional[str]

The model handle for this conversation (overrides agent’s model). Format: provider/model-name.

model_settings: Optional[ModelSettings]

The model settings for this conversation (overrides agent’s model settings).

One of the following:

class OpenAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openai"]]

The type of the provider.

reasoning: Optional[Reasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsSgLangModelSettings: …

SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["sglang"]]

The type of the provider.

reasoning: Optional[ModelSettingsSgLangModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

tool_call_parser: Optional[str]

SGLang tool call parser name (for example ‘glm47’, ‘qwen25’, or ‘hermes’).

class AnthropicModelSettings: …

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["anthropic"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[Thinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GoogleAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_ai"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class GoogleVertexModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_vertex"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class AzureModelSettings: …

Azure OpenAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["azure"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class XaiModelSettings: …

xAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["xai"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsMoonshotModelSettings: …

Moonshot/Kimi model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsZaiModelSettings: …

Z.ai (ZhipuAI) model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["zai"]]

The type of the provider.

response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsZaiModelSettingsThinking]

The thinking configuration for GLM-4.5+ models.

clear_thinking: Optional[bool]

If False, preserved thinking is used (recommended for agents).

type: Optional[Literal["enabled", "disabled"]]

Whether thinking is enabled or disabled.

One of the following:

"enabled"

"disabled"

class ModelSettingsMoonshotCodingModelSettings: …

Kimi Code model configuration (Anthropic-compatible).

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot_coding"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsMoonshotCodingModelSettingsThinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GroqModelSettings: …

Groq model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["groq"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class DeepseekModelSettings: …

Deepseek model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["deepseek"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class TogetherModelSettings: …

Together AI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["together"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class BedrockModelSettings: …

AWS Bedrock model configuration.

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["bedrock"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsBasetenModelSettings: …

Baseten model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["baseten"]]

The type of the provider.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsOpenRouterModelSettings: …

OpenRouter model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openrouter"]]

The type of the provider.

response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsChatGptoAuthModelSettings: …

ChatGPT OAuth model configuration (uses ChatGPT backend API).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["chatgpt_oauth"]]

The type of the provider.

reasoning: Optional[ModelSettingsChatGptoAuthModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]

The reasoning effort level for GPT-5.x and o-series models.

One of the following:

"none"

"low"

"medium"

"high"

"xhigh"

temperature: Optional[float]

The temperature of the model.

summary: Optional[str]

A summary of the conversation.

class UpdateConversation: …

Request model for updating a conversation.

archived: Optional[bool]

Whether the conversation is archived.

context_window_limit: Optional[int]

The context window limit for this conversation (overrides agent’s context window).

description: Optional[str]

A generated description of the conversation used for search and bootstrap context.

last_message_at: Optional[datetime]

Timestamp of the most recent message request sent to this conversation.

formatdate-time

model: Optional[str]

The model handle for this conversation (overrides agent’s model). Format: provider/model-name.

model_settings: Optional[ModelSettings]

The model settings for this conversation (overrides agent’s model settings).

One of the following:

class OpenAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openai"]]

The type of the provider.

reasoning: Optional[Reasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsSgLangModelSettings: …

SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["sglang"]]

The type of the provider.

reasoning: Optional[ModelSettingsSgLangModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

tool_call_parser: Optional[str]

SGLang tool call parser name (for example ‘glm47’, ‘qwen25’, or ‘hermes’).

class AnthropicModelSettings: …

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["anthropic"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[Thinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GoogleAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_ai"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class GoogleVertexModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_vertex"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class AzureModelSettings: …

Azure OpenAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["azure"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class XaiModelSettings: …

xAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["xai"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsMoonshotModelSettings: …

Moonshot/Kimi model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsZaiModelSettings: …

Z.ai (ZhipuAI) model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["zai"]]

The type of the provider.

response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsZaiModelSettingsThinking]

The thinking configuration for GLM-4.5+ models.

clear_thinking: Optional[bool]

If False, preserved thinking is used (recommended for agents).

type: Optional[Literal["enabled", "disabled"]]

Whether thinking is enabled or disabled.

One of the following:

"enabled"

"disabled"

class ModelSettingsMoonshotCodingModelSettings: …

Kimi Code model configuration (Anthropic-compatible).

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot_coding"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsMoonshotCodingModelSettingsThinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GroqModelSettings: …

Groq model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["groq"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class DeepseekModelSettings: …

Deepseek model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["deepseek"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class TogetherModelSettings: …

Together AI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["together"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class BedrockModelSettings: …

AWS Bedrock model configuration.

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["bedrock"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsBasetenModelSettings: …

Baseten model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["baseten"]]

The type of the provider.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsOpenRouterModelSettings: …

OpenRouter model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openrouter"]]

The type of the provider.

response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsChatGptoAuthModelSettings: …

ChatGPT OAuth model configuration (uses ChatGPT backend API).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["chatgpt_oauth"]]

The type of the provider.

reasoning: Optional[ModelSettingsChatGptoAuthModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]

The reasoning effort level for GPT-5.x and o-series models.

One of the following:

"none"

"low"

"medium"

"high"

"xhigh"

temperature: Optional[float]

The temperature of the model.

summary: Optional[str]

A summary of the conversation.

List[Conversation]

id: str

The unique identifier of the conversation.

agent_id: str

The ID of the agent this conversation belongs to.

archived: Optional[bool]

Whether the conversation is archived.

archived_at: Optional[datetime]

Timestamp of when the conversation was archived.

formatdate-time

context_window_limit: Optional[int]

The context window limit for this conversation (overrides agent’s context window).

created_at: Optional[datetime]

The timestamp when the object was created.

formatdate-time

created_by_id: Optional[str]

The id of the user that made this object.

description: Optional[str]

A generated description of the conversation used for search and bootstrap context.

in_context_message_ids: Optional[List[str]]

The IDs of in-context messages for the conversation. Null means this field was not retrieved/hydrated for this response.

last_message_at: Optional[datetime]

Timestamp of the most recent message request sent to this conversation.

formatdate-time

last_updated_by_id: Optional[str]

The id of the user that made this object.

model: Optional[str]

The model handle for this conversation (overrides agent’s model). Format: provider/model-name.

model_settings: Optional[ModelSettings]

The model settings for this conversation (overrides agent’s model settings).

One of the following:

class OpenAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openai"]]

The type of the provider.

reasoning: Optional[Reasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsSgLangModelSettings: …

SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["sglang"]]

The type of the provider.

reasoning: Optional[ModelSettingsSgLangModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

tool_call_parser: Optional[str]

SGLang tool call parser name (for example ‘glm47’, ‘qwen25’, or ‘hermes’).

class AnthropicModelSettings: …

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["anthropic"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[Thinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GoogleAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_ai"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class GoogleVertexModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_vertex"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class AzureModelSettings: …

Azure OpenAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["azure"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class XaiModelSettings: …

xAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["xai"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsMoonshotModelSettings: …

Moonshot/Kimi model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsZaiModelSettings: …

Z.ai (ZhipuAI) model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["zai"]]

The type of the provider.

response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsZaiModelSettingsThinking]

The thinking configuration for GLM-4.5+ models.

clear_thinking: Optional[bool]

If False, preserved thinking is used (recommended for agents).

type: Optional[Literal["enabled", "disabled"]]

Whether thinking is enabled or disabled.

One of the following:

"enabled"

"disabled"

class ModelSettingsMoonshotCodingModelSettings: …

Kimi Code model configuration (Anthropic-compatible).

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot_coding"]]

The type of the provider.

response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[ModelSettingsMoonshotCodingModelSettingsThinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GroqModelSettings: …

Groq model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["groq"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class DeepseekModelSettings: …

Deepseek model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["deepseek"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class TogetherModelSettings: …

Together AI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["together"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class BedrockModelSettings: …

AWS Bedrock model configuration.

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["bedrock"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsBasetenModelSettings: …

Baseten model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["baseten"]]

The type of the provider.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsOpenRouterModelSettings: …

OpenRouter model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openrouter"]]

The type of the provider.

response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class ModelSettingsChatGptoAuthModelSettings: …

ChatGPT OAuth model configuration (uses ChatGPT backend API).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["chatgpt_oauth"]]

The type of the provider.

reasoning: Optional[ModelSettingsChatGptoAuthModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]

The reasoning effort level for GPT-5.x and o-series models.

One of the following:

"none"

"low"

"medium"

"high"

"xhigh"

temperature: Optional[float]

The temperature of the model.

summary: Optional[str]

A summary of the conversation.

updated_at: Optional[datetime]

The timestamp when the object was last updated.

formatdate-time

Dict[str, object]

str

ConversationsMessages

List Conversation Messages

conversations.messages.list(, ) -> SyncArrayPage[Message]

GET/v1/conversations/{conversation_id}/messages

Send Conversation Message

conversations.messages.create(, ) -> LettaResponse

POST/v1/conversations/{conversation_id}/messages

Retrieve Conversation Stream

conversations.messages.stream(, ) -> object

POST/v1/conversations/{conversation_id}/stream

Compact Conversation

conversations.messages.compact(, ) -> CompactionResponse

POST/v1/conversations/{conversation_id}/compact

ModelsExpand Collapse

class CompactionRequest: …

compaction_settings: Optional[CompactionSettings]

Configuration for conversation compaction / summarization.

Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle.

clip_chars: Optional[int]

The maximum length of the summary in characters. If none, no clipping is performed.

mode: Optional[Literal["all", "sliding_window", "self_compact_all", "self_compact_sliding_window"]]

The type of summarization technique use.

One of the following:

"all"

"sliding_window"

"self_compact_all"

"self_compact_sliding_window"

model: Optional[str]

Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults.

model_settings: Optional[CompactionSettingsModelSettings]

Optional model settings used to override defaults for the summarizer model.

One of the following:

class OpenAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openai"]]

The type of the provider.

reasoning: Optional[Reasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class CompactionSettingsModelSettingsSgLangModelSettings: …

SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["sglang"]]

The type of the provider.

reasoning: Optional[CompactionSettingsModelSettingsSgLangModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format: Optional[CompactionSettingsModelSettingsSgLangModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

tool_call_parser: Optional[str]

SGLang tool call parser name (for example ‘glm47’, ‘qwen25’, or ‘hermes’).

class AnthropicModelSettings: …

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["anthropic"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[Thinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GoogleAIModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_ai"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class GoogleVertexModelSettings: …

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["google_vertex"]]

The type of the provider.

response_schema: Optional[ResponseSchema]

The response schema for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking_config: Optional[ThinkingConfig]

The thinking configuration for the model.

include_thoughts: Optional[bool]

Whether to include thoughts in the model’s response.

thinking_budget: Optional[int]

The thinking budget for the model.

class AzureModelSettings: …

Azure OpenAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["azure"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class XaiModelSettings: …

xAI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["xai"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class CompactionSettingsModelSettingsMoonshotModelSettings: …

Moonshot/Kimi model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot"]]

The type of the provider.

response_format: Optional[CompactionSettingsModelSettingsMoonshotModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

class CompactionSettingsModelSettingsZaiModelSettings: …

Z.ai (ZhipuAI) model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["zai"]]

The type of the provider.

response_format: Optional[CompactionSettingsModelSettingsZaiModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[CompactionSettingsModelSettingsZaiModelSettingsThinking]

The thinking configuration for GLM-4.5+ models.

clear_thinking: Optional[bool]

If False, preserved thinking is used (recommended for agents).

type: Optional[Literal["enabled", "disabled"]]

Whether thinking is enabled or disabled.

One of the following:

"enabled"

"disabled"

class CompactionSettingsModelSettingsMoonshotCodingModelSettings: …

Kimi Code model configuration (Anthropic-compatible).

effort: Optional[Literal["low", "medium", "high", 2 more]]

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["moonshot_coding"]]

The type of the provider.

response_format: Optional[CompactionSettingsModelSettingsMoonshotCodingModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

strict: Optional[bool]

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature: Optional[float]

The temperature of the model.

thinking: Optional[CompactionSettingsModelSettingsMoonshotCodingModelSettingsThinking]

The thinking configuration for the model.

budget_tokens: Optional[int]

The maximum number of tokens the model can use for extended thinking.

type: Optional[Literal["enabled", "disabled"]]

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity: Optional[Literal["low", "medium", "high"]]

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

class GroqModelSettings: …

Groq model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["groq"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class DeepseekModelSettings: …

Deepseek model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["deepseek"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class TogetherModelSettings: …

Together AI model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["together"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class BedrockModelSettings: …

AWS Bedrock model configuration.

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["bedrock"]]

The type of the provider.

response_format: Optional[ResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class CompactionSettingsModelSettingsBasetenModelSettings: …

Baseten model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["baseten"]]

The type of the provider.

temperature: Optional[float]

The temperature of the model.

class CompactionSettingsModelSettingsOpenRouterModelSettings: …

OpenRouter model configuration (OpenAI-compatible).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["openrouter"]]

The type of the provider.

response_format: Optional[CompactionSettingsModelSettingsOpenRouterModelSettingsResponseFormat]

The response format for the model.

One of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

class JsonSchemaResponseFormat: …

Response format for JSON schema-based responses.

json_schema: Dict[str, object]

The JSON schema of the response.

type: Optional[Literal["json_schema"]]

The type of the response format.

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

temperature: Optional[float]

The temperature of the model.

class CompactionSettingsModelSettingsChatGptoAuthModelSettings: …

ChatGPT OAuth model configuration (uses ChatGPT backend API).

max_output_tokens: Optional[int]

The maximum number of tokens the model can generate.

parallel_tool_calls: Optional[bool]

Whether to enable parallel tool calling.

provider_type: Optional[Literal["chatgpt_oauth"]]

The type of the provider.

reasoning: Optional[CompactionSettingsModelSettingsChatGptoAuthModelSettingsReasoning]

The reasoning configuration for the model.

reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]

The reasoning effort level for GPT-5.x and o-series models.

One of the following:

"none"

"low"

"medium"

"high"

"xhigh"

temperature: Optional[float]

The temperature of the model.

prompt: Optional[str]

The prompt to use for summarization. If None, uses mode-specific default.

prompt_acknowledgement: Optional[bool]

Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs).

sliding_window_percentage: Optional[float]

The percentage of the context window to keep post-summarization (only used in sliding window modes).

class CompactionResponse: …

num_messages_after: int

num_messages_before: int

summary: str