## Update Conversation `conversations.update(strconversation_id, ConversationUpdateParams**kwargs) -> Conversation` **patch** `/v1/conversations/{conversation_id}` Update a conversation. ### Parameters - `conversation_id: str` The ID of the conv in the format 'conv-' - `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[Union[str, datetime, null]]` Timestamp of the most recent message request sent to this conversation. - `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). - `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. - `"openai"` - `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 - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `type: Optional[Literal["text"]]` The type of the response format. - `"text"` - `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. - `"json_schema"` - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `type: Optional[Literal["json_object"]]` The type of the response format. - `"json_object"` - `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. - `"sglang"` - `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 - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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'. - `"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. - `"anthropic"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"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. - `"google_ai"` - `response_schema: Optional[ResponseSchema]` The response schema for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"google_vertex"` - `response_schema: Optional[ResponseSchema]` The response schema for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"azure"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"xai"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"moonshot"` - `response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"zai"` - `response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"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'. - `"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. - `"moonshot_coding"` - `response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"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. - `"groq"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"deepseek"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"together"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"bedrock"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"baseten"` - `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. - `"openrouter"` - `response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"chatgpt_oauth"` - `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. - `"none"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `temperature: Optional[float]` The temperature of the model. - `summary: Optional[str]` A summary of the conversation. ### Returns - `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. - `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. - `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. - `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). - `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. - `"openai"` - `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 - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `type: Optional[Literal["text"]]` The type of the response format. - `"text"` - `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. - `"json_schema"` - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `type: Optional[Literal["json_object"]]` The type of the response format. - `"json_object"` - `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. - `"sglang"` - `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 - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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'. - `"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. - `"anthropic"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"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. - `"google_ai"` - `response_schema: Optional[ResponseSchema]` The response schema for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"google_vertex"` - `response_schema: Optional[ResponseSchema]` The response schema for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"azure"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"xai"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"moonshot"` - `response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"zai"` - `response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"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'. - `"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. - `"moonshot_coding"` - `response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"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. - `"groq"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"deepseek"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"together"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"bedrock"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"baseten"` - `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. - `"openrouter"` - `response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `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. - `"chatgpt_oauth"` - `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. - `"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. ### Example ```python import os from letta_client import Letta client = Letta( api_key=os.environ.get("LETTA_API_KEY"), # This is the default and can be omitted ) conversation = client.conversations.update( conversation_id="conv-123e4567-e89b-42d3-8456-426614174000", ) print(conversation.id) ``` #### Response ```json { "id": "id", "agent_id": "agent_id", "archived": true, "archived_at": "2019-12-27T18:11:19.117Z", "context_window_limit": 0, "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "in_context_message_ids": [ "string" ], "last_message_at": "2019-12-27T18:11:19.117Z", "last_updated_by_id": "last_updated_by_id", "model": "model", "model_settings": { "max_output_tokens": 0, "parallel_tool_calls": true, "provider_type": "openai", "reasoning": { "reasoning_effort": "none" }, "response_format": { "type": "text" }, "strict": true, "temperature": 0 }, "summary": "summary", "updated_at": "2019-12-27T18:11:19.117Z" } ```