# Messages ## List Conversation Messages `client.conversations.messages.list(stringconversationID, MessageListParamsquery?, RequestOptionsoptions?): ArrayPage` **get** `/v1/conversations/{conversation_id}/messages` List all messages in a conversation. Returns LettaMessage objects (UserMessage, AssistantMessage, etc.) for all messages in the conversation, with support for cursor-based pagination. **Agent-direct mode**: Pass conversation_id="default" with agent_id parameter to list messages from the agent's default conversation. **Deprecated**: Passing an agent ID as conversation_id still works but will be removed. ### Parameters - `conversationID: string` The conversation identifier. Can be a conversation ID ('conv-'), 'default' for agent-direct mode (with agent_id parameter), or an agent ID ('agent-') for backwards compatibility (deprecated). - `query: MessageListParams` - `after?: string | null` Cursor for pagination (message ID). Returns results relative to this ID in the specified sort order. Expected format: 'message-' - `agent_id?: string | null` Agent ID for agent-direct mode with 'default' conversation - `before?: string | null` Cursor for pagination (message ID). Returns results relative to this ID in the specified sort order. Expected format: 'message-' - `group_id?: string | null` Group ID to filter messages by. - `include_err?: boolean | null` Whether to include error messages and error statuses. For debugging purposes only. - `include_return_message_types?: Array | null` Message types to include in response. When null, all message types are returned. - `"system_message"` - `"user_message"` - `"assistant_message"` - `"reasoning_message"` - `"hidden_reasoning_message"` - `"tool_call_message"` - `"tool_return_message"` - `"approval_request_message"` - `"approval_response_message"` - `"summary_message"` - `"event_message"` - `limit?: number | null` Maximum number of messages to return - `order?: "asc" | "desc"` Sort order for messages by creation time. 'asc' for oldest first, 'desc' for newest first - `"asc"` - `"desc"` - `order_by?: "created_at"` Field to sort by - `"created_at"` ### Returns - `Message = SystemMessage | UserMessage | ReasoningMessage | 8 more` A message generated by the system. Never streamed back on a response, only used for cursor pagination. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (str): The message content sent by the system - `SystemMessage` A message generated by the system. Never streamed back on a response, only used for cursor pagination. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (str): The message content sent by the system - `id: string` - `content: string` The message content sent by the system - `date: string` - `is_err?: boolean | null` - `message_type?: "system_message"` The type of the message. - `"system_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `UserMessage` A message sent by the user. Never streamed back on a response, only used for cursor pagination. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (Union[str, List[LettaUserMessageContentUnion]]): The message content sent by the user (can be a string or an array of multi-modal content parts) - `id: string` - `content: Array | string` The message content sent by the user (can be a string or an array of multi-modal content parts) - `Array` - `TextContent` - `text: string` The text content of the message. - `signature?: string | null` Stores a unique identifier for any reasoning associated with this text content. - `type?: "text"` The type of the message. - `"text"` - `ImageContent` - `source: URLImage | Base64Image | LettaImage` The source of the image. - `URLImage` - `url: string` The URL of the image. - `type?: "url"` The source type for the image. - `"url"` - `Base64Image` - `data: string` The base64 encoded image data. - `media_type: string` The media type for the image. - `detail?: string | null` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `type?: "base64"` The source type for the image. - `"base64"` - `LettaImage` - `file_id: string` The unique identifier of the image file persisted in storage. - `data?: string | null` The base64 encoded image data. - `detail?: string | null` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `media_type?: string | null` The media type for the image. - `type?: "letta"` The source type for the image. - `"letta"` - `type?: "image"` The type of the message. - `"image"` - `string` - `date: string` - `is_err?: boolean | null` - `message_type?: "user_message"` The type of the message. - `"user_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `ReasoningMessage` Representation of an agent's internal reasoning. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message source (Literal["reasoner_model", "non_reasoner_model"]): Whether the reasoning content was generated natively by a reasoner model or derived via prompting reasoning (str): The internal reasoning of the agent signature (Optional[str]): The model-generated signature of the reasoning step - `id: string` - `date: string` - `reasoning: string` - `is_err?: boolean | null` - `message_type?: "reasoning_message"` The type of the message. - `"reasoning_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `signature?: string | null` - `source?: "reasoner_model" | "non_reasoner_model"` - `"reasoner_model"` - `"non_reasoner_model"` - `step_id?: string | null` - `HiddenReasoningMessage` Representation of an agent's internal reasoning where reasoning content has been hidden from the response. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message state (Literal["redacted", "omitted"]): Whether the reasoning content was redacted by the provider or simply omitted by the API hidden_reasoning (Optional[str]): The internal reasoning of the agent - `id: string` - `date: string` - `state: "redacted" | "omitted"` - `"redacted"` - `"omitted"` - `hidden_reasoning?: string | null` - `is_err?: boolean | null` - `message_type?: "hidden_reasoning_message"` The type of the message. - `"hidden_reasoning_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `ToolCallMessage` A message representing a request to call a tool (generated by the LLM to trigger tool execution). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_call (Union[ToolCall, ToolCallDelta]): The tool call - `id: string` - `date: string` - `tool_call: ToolCall | ToolCallDelta` - `ToolCall` - `arguments: string` - `name: string` - `tool_call_id: string` - `ToolCallDelta` - `arguments?: string | null` - `name?: string | null` - `tool_call_id?: string | null` - `is_err?: boolean | null` - `message_type?: "tool_call_message"` The type of the message. - `"tool_call_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `tool_calls?: Array | ToolCallDelta | null` - `Array` - `arguments: string` - `name: string` - `tool_call_id: string` - `ToolCallDelta` - `ToolReturnMessage` A message representing the return value of a tool call (generated by Letta executing the requested tool). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_return (str): The return value of the tool (deprecated, use tool_returns) status (Literal["success", "error"]): The status of the tool call (deprecated, use tool_returns) tool_call_id (str): A unique identifier for the tool call that generated this message (deprecated, use tool_returns) stdout (Optional[List(str)]): Captured stdout (e.g. prints, logs) from the tool invocation (deprecated, use tool_returns) stderr (Optional[List(str)]): Captured stderr from the tool invocation (deprecated, use tool_returns) tool_returns (Optional[List[ToolReturn]]): List of tool returns for multi-tool support - `id: string` - `date: string` - `status: "success" | "error"` - `"success"` - `"error"` - `tool_call_id: string` - `tool_return: string` - `is_err?: boolean | null` - `message_type?: "tool_return_message"` The type of the message. - `"tool_return_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `stderr?: Array | null` - `stdout?: Array | null` - `step_id?: string | null` - `tool_returns?: Array | null` - `status: "success" | "error"` - `"success"` - `"error"` - `tool_call_id: string` - `tool_return: Array | string` The tool return value - either a string or list of content parts (text/image) - `Array` - `TextContent` - `ImageContent` - `string` - `stderr?: Array | null` - `stdout?: Array | null` - `type?: "tool"` The message type to be created. - `"tool"` - `AssistantMessage` A message sent by the LLM in response to user input. Used in the LLM context. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (Union[str, List[LettaAssistantMessageContentUnion]]): The message content sent by the agent (can be a string or an array of content parts) - `id: string` - `content: Array | string` The message content sent by the agent (can be a string or an array of content parts) - `Array` - `text: string` The text content of the message. - `signature?: string | null` Stores a unique identifier for any reasoning associated with this text content. - `type?: "text"` The type of the message. - `"text"` - `string` - `date: string` - `is_err?: boolean | null` - `message_type?: "assistant_message"` The type of the message. - `"assistant_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `ApprovalRequestMessage` A message representing a request for approval to call a tool (generated by the LLM to trigger tool execution). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_call (ToolCall): The tool call - `id: string` - `date: string` - `tool_call: ToolCall | ToolCallDelta` The tool call that has been requested by the llm to run - `ToolCall` - `ToolCallDelta` - `is_err?: boolean | null` - `message_type?: "approval_request_message"` The type of the message. - `"approval_request_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `tool_calls?: Array | ToolCallDelta | null` The tool calls that have been requested by the llm to run, which are pending approval - `Array` - `arguments: string` - `name: string` - `tool_call_id: string` - `ToolCallDelta` - `ApprovalResponseMessage` A message representing a response form the user indicating whether a tool has been approved to run. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message approve: (bool) Whether the tool has been approved approval_request_id: The ID of the approval request reason: (Optional[str]) An optional explanation for the provided approval status - `id: string` - `date: string` - `approval_request_id?: string | null` The message ID of the approval request - `approvals?: Array | null` The list of approval responses - `ApprovalReturn` - `approve: boolean` Whether the tool has been approved - `tool_call_id: string` The ID of the tool call that corresponds to this approval - `reason?: string | null` An optional explanation for the provided approval status - `type?: "approval"` The message type to be created. - `"approval"` - `ToolReturn` - `status: "success" | "error"` - `tool_call_id: string` - `tool_return: Array | string` The tool return value - either a string or list of content parts (text/image) - `stderr?: Array | null` - `stdout?: Array | null` - `type?: "tool"` The message type to be created. - `approve?: boolean | null` Whether the tool has been approved - `is_err?: boolean | null` - `message_type?: "approval_response_message"` The type of the message. - `"approval_response_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `reason?: string | null` An optional explanation for the provided approval status - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `SummaryMessage` A message representing a summary of the conversation. Sent to the LLM as a user or system message depending on the provider. - `id: string` - `date: string` - `summary: string` - `compaction_stats?: CompactionStats | null` Statistics about a memory compaction operation. - `context_window: number` The model's context window size - `messages_count_after: number` Number of messages after compaction - `messages_count_before: number` Number of messages before compaction - `trigger: string` What triggered the compaction (e.g., 'context_window_exceeded', 'post_step_context_check') - `context_tokens_after?: number | null` Token count after compaction (message tokens only, does not include tool definitions) - `context_tokens_before?: number | null` Token count before compaction (from LLM usage stats, includes full context sent to LLM) - `is_err?: boolean | null` - `message_type?: "summary_message"` - `"summary_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `EventMessage` A message for notifying the developer that an event that has occured (e.g. a compaction). Events are NOT part of the context window. - `id: string` - `date: string` - `event_data: Record` - `event_type: "compaction"` - `"compaction"` - `is_err?: boolean | null` - `message_type?: "event_message"` - `"event_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` ### Example ```typescript import Letta from '@letta-ai/letta-client'; const client = new Letta({ apiKey: process.env['LETTA_API_KEY'], // This is the default and can be omitted }); // Automatically fetches more pages as needed. for await (const message of client.conversations.messages.list('default')) { console.log(message); } ``` #### Response ```json [ { "id": "id", "content": "content", "date": "2019-12-27T18:11:19.117Z", "is_err": true, "message_type": "system_message", "name": "name", "otid": "otid", "run_id": "run_id", "sender_id": "sender_id", "seq_id": 0, "step_id": "step_id" } ] ``` ## Send Conversation Message `client.conversations.messages.create(stringconversationID, MessageCreateParamsbody, RequestOptionsoptions?): LettaResponse | Stream` **post** `/v1/conversations/{conversation_id}/messages` Send a message to a conversation and get a response. This endpoint sends a message to an existing conversation. By default (streaming=true), returns a streaming response (Server-Sent Events). Set streaming=false to get a complete JSON response. **Agent-direct mode**: Pass conversation_id="default" with agent_id in request body to send messages to the agent's default conversation with locking. **Deprecated**: Passing an agent ID as conversation_id still works but will be removed. ### Parameters - `conversationID: string` The conversation identifier. Can be a conversation ID ('conv-'), 'default' for agent-direct mode (with agent_id parameter), or an agent ID ('agent-') for backwards compatibility (deprecated). - `body: MessageCreateParams` - `agent_id?: string | null` Agent ID for agent-direct mode with 'default' conversation. Use with conversation_id='default' in the URL path. - `assistant_message_tool_kwarg?: string` The name of the message argument in the designated message tool. Still supported for legacy agent types, but deprecated for letta_v1_agent onward. - `assistant_message_tool_name?: string` The name of the designated message tool. Still supported for legacy agent types, but deprecated for letta_v1_agent onward. - `background?: boolean` Whether to process the request in the background (only used when streaming=true). - `client_skills?: Array | null` Client-side skills available in the environment. These are rendered in the system prompt's available skills section alongside agent-scoped skills from MemFS. - `description: string` Description of what the skill does - `location: string` Path or location hint for the skill (e.g. skills/my-skill/SKILL.md) - `name: string` The name of the skill - `client_tools?: Array | null` Client-side tools that the agent can call. When the agent calls a client-side tool, execution pauses and returns control to the client to execute the tool and provide the result via a ToolReturn. - `name: string` The name of the tool function - `description?: string | null` Description of what the tool does - `parameters?: Record | null` JSON Schema for the function parameters - `enable_thinking?: string` If set to True, enables reasoning before responses or tool calls from the agent. - `include_compaction_messages?: boolean` If True, compaction events emit structured `SummaryMessage` and `EventMessage` types. If False (default), compaction messages are not included in the response. - `include_pings?: boolean` Whether to include periodic keepalive ping messages in the stream to prevent connection timeouts (only used when streaming=true). - `include_return_message_types?: Array | null` Only return specified message types in the response. If `None` (default) returns all messages. - `"system_message"` - `"user_message"` - `"assistant_message"` - `"reasoning_message"` - `"hidden_reasoning_message"` - `"tool_call_message"` - `"tool_return_message"` - `"approval_request_message"` - `"approval_response_message"` - `"summary_message"` - `"event_message"` - `input?: string | Array | null` Syntactic sugar for a single user message. Equivalent to messages=[{'role': 'user', 'content': input}]. - `string` - `Array` - `TextContent` - `text: string` The text content of the message. - `signature?: string | null` Stores a unique identifier for any reasoning associated with this text content. - `type?: "text"` The type of the message. - `"text"` - `ImageContent` - `source: URLImage | Base64Image | LettaImage` The source of the image. - `URLImage` - `url: string` The URL of the image. - `type?: "url"` The source type for the image. - `"url"` - `Base64Image` - `data: string` The base64 encoded image data. - `media_type: string` The media type for the image. - `detail?: string | null` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `type?: "base64"` The source type for the image. - `"base64"` - `LettaImage` - `file_id: string` The unique identifier of the image file persisted in storage. - `data?: string | null` The base64 encoded image data. - `detail?: string | null` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `media_type?: string | null` The media type for the image. - `type?: "letta"` The source type for the image. - `"letta"` - `type?: "image"` The type of the message. - `"image"` - `ToolCallContent` - `id: string` A unique identifier for this specific tool call instance. - `input: Record` The parameters being passed to the tool, structured as a dictionary of parameter names to values. - `name: string` The name of the tool being called. - `signature?: string | null` Stores a unique identifier for any reasoning associated with this tool call. - `type?: "tool_call"` Indicates this content represents a tool call event. - `"tool_call"` - `ToolReturnContent` - `content: string` The content returned by the tool execution. - `is_error: boolean` Indicates whether the tool execution resulted in an error. - `tool_call_id: string` References the ID of the ToolCallContent that initiated this tool call. - `type?: "tool_return"` Indicates this content represents a tool return event. - `"tool_return"` - `ReasoningContent` Sent via the Anthropic Messages API - `is_native: boolean` Whether the reasoning content was generated by a reasoner model that processed this step. - `reasoning: string` The intermediate reasoning or thought process content. - `signature?: string | null` A unique identifier for this reasoning step. - `type?: "reasoning"` Indicates this is a reasoning/intermediate step. - `"reasoning"` - `RedactedReasoningContent` Sent via the Anthropic Messages API - `data: string` The redacted or filtered intermediate reasoning content. - `type?: "redacted_reasoning"` Indicates this is a redacted thinking step. - `"redacted_reasoning"` - `OmittedReasoningContent` A placeholder for reasoning content we know is present, but isn't returned by the provider (e.g. OpenAI GPT-5 on ChatCompletions) - `signature?: string | null` A unique identifier for this reasoning step. - `type?: "omitted_reasoning"` Indicates this is an omitted reasoning step. - `"omitted_reasoning"` - `SummarizedReasoningContent` The style of reasoning content returned by the OpenAI Responses API - `id: string` The unique identifier for this reasoning step. - `summary: Array` Summaries of the reasoning content. - `index: number` The index of the summary part. - `text: string` The text of the summary part. - `encrypted_content?: string` The encrypted reasoning content. - `type?: "summarized_reasoning"` Indicates this is a summarized reasoning step. - `"summarized_reasoning"` - `max_steps?: number` Maximum number of steps the agent should take to process the request. - `messages?: Array | null` The messages to be sent to the agent. - `MessageCreate` Request to create a message - `content: Array | string` The content of the message. - `Array` - `TextContent` - `ImageContent` - `ToolCallContent` - `ToolReturnContent` - `ReasoningContent` Sent via the Anthropic Messages API - `RedactedReasoningContent` Sent via the Anthropic Messages API - `OmittedReasoningContent` A placeholder for reasoning content we know is present, but isn't returned by the provider (e.g. OpenAI GPT-5 on ChatCompletions) - `string` - `role: "user" | "system" | "assistant"` The role of the participant. - `"user"` - `"system"` - `"assistant"` - `batch_item_id?: string | null` The id of the LLMBatchItem that this message is associated with - `group_id?: string | null` The multi-agent group that the message was sent in - `name?: string | null` The name of the participant. - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `sender_id?: string | null` The id of the sender of the message, can be an identity id or agent id - `type?: "message" | null` The message type to be created. - `"message"` - `ApprovalCreate` Input to approve or deny a tool call request - `approval_request_id?: string | null` The message ID of the approval request - `approvals?: Array | null` The list of approval responses - `ApprovalReturn` - `approve: boolean` Whether the tool has been approved - `tool_call_id: string` The ID of the tool call that corresponds to this approval - `reason?: string | null` An optional explanation for the provided approval status - `type?: "approval"` The message type to be created. - `"approval"` - `ToolReturn` - `status: "success" | "error"` - `"success"` - `"error"` - `tool_call_id: string` - `tool_return: Array | string` The tool return value - either a string or list of content parts (text/image) - `Array` - `TextContent` - `ImageContent` - `string` - `stderr?: Array | null` - `stdout?: Array | null` - `type?: "tool"` The message type to be created. - `"tool"` - `approve?: boolean | null` Whether the tool has been approved - `group_id?: string | null` The multi-agent group that the message was sent in - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `reason?: string | null` An optional explanation for the provided approval status - `type?: "approval"` The message type to be created. - `"approval"` - `ToolReturnCreate` Submit tool return(s) from client-side tool execution. This is the preferred way to send tool results back to the agent after client-side tool execution. It is equivalent to sending an ApprovalCreate with tool return approvals, but provides a cleaner API for the common case. - `tool_returns: Array` List of tool returns from client-side execution - `status: "success" | "error"` - `tool_call_id: string` - `tool_return: Array | string` The tool return value - either a string or list of content parts (text/image) - `stderr?: Array | null` - `stdout?: Array | null` - `type?: "tool"` The message type to be created. - `group_id?: string | null` The multi-agent group that the message was sent in - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `type?: "tool_return"` The message type to be created. - `"tool_return"` - `override_model?: string | null` Model handle to use for this request instead of the agent's default model. This allows sending a message to a different model without changing the agent's configuration. - `override_system?: string | null` Optional per-request system prompt override. When set, this is passed directly to the underlying LLM request and bypasses the persisted/compiled system message for that request. - `return_logprobs?: boolean` If True, returns log probabilities of the output tokens in the response. Useful for RL training. Only supported for OpenAI-compatible providers (including SGLang). - `return_token_ids?: boolean` If True, returns token IDs and logprobs for ALL LLM generations in the agent step, not just the last one. Uses SGLang native /generate endpoint. Returns 'turns' field with TurnTokenData for each assistant/tool turn. Required for proper multi-turn RL training with loss masking. - `stream_tokens?: boolean` Flag to determine if individual tokens should be streamed, rather than streaming per step (only used when streaming=true). - `streaming?: boolean` If True (default), returns a streaming response (Server-Sent Events). If False, returns a complete JSON response. - `top_logprobs?: number | null` Number of most likely tokens to return at each position (0-20). Requires return_logprobs=True. - `use_assistant_message?: boolean` Whether the server should parse specific tool call arguments (default `send_message`) as `AssistantMessage` objects. Still supported for legacy agent types, but deprecated for letta_v1_agent onward. ### Returns - `LettaResponse` Response object from an agent interaction, consisting of the new messages generated by the agent and usage statistics. The type of the returned messages can be either `Message` or `LettaMessage`, depending on what was specified in the request. Attributes: messages (List[Union[Message, LettaMessage]]): The messages returned by the agent. usage (LettaUsageStatistics): The usage statistics - `messages: Array` The messages returned by the agent. - `SystemMessage` A message generated by the system. Never streamed back on a response, only used for cursor pagination. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (str): The message content sent by the system - `id: string` - `content: string` The message content sent by the system - `date: string` - `is_err?: boolean | null` - `message_type?: "system_message"` The type of the message. - `"system_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `UserMessage` A message sent by the user. Never streamed back on a response, only used for cursor pagination. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (Union[str, List[LettaUserMessageContentUnion]]): The message content sent by the user (can be a string or an array of multi-modal content parts) - `id: string` - `content: Array | string` The message content sent by the user (can be a string or an array of multi-modal content parts) - `Array` - `TextContent` - `text: string` The text content of the message. - `signature?: string | null` Stores a unique identifier for any reasoning associated with this text content. - `type?: "text"` The type of the message. - `"text"` - `ImageContent` - `source: URLImage | Base64Image | LettaImage` The source of the image. - `URLImage` - `url: string` The URL of the image. - `type?: "url"` The source type for the image. - `"url"` - `Base64Image` - `data: string` The base64 encoded image data. - `media_type: string` The media type for the image. - `detail?: string | null` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `type?: "base64"` The source type for the image. - `"base64"` - `LettaImage` - `file_id: string` The unique identifier of the image file persisted in storage. - `data?: string | null` The base64 encoded image data. - `detail?: string | null` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `media_type?: string | null` The media type for the image. - `type?: "letta"` The source type for the image. - `"letta"` - `type?: "image"` The type of the message. - `"image"` - `string` - `date: string` - `is_err?: boolean | null` - `message_type?: "user_message"` The type of the message. - `"user_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `ReasoningMessage` Representation of an agent's internal reasoning. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message source (Literal["reasoner_model", "non_reasoner_model"]): Whether the reasoning content was generated natively by a reasoner model or derived via prompting reasoning (str): The internal reasoning of the agent signature (Optional[str]): The model-generated signature of the reasoning step - `id: string` - `date: string` - `reasoning: string` - `is_err?: boolean | null` - `message_type?: "reasoning_message"` The type of the message. - `"reasoning_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `signature?: string | null` - `source?: "reasoner_model" | "non_reasoner_model"` - `"reasoner_model"` - `"non_reasoner_model"` - `step_id?: string | null` - `HiddenReasoningMessage` Representation of an agent's internal reasoning where reasoning content has been hidden from the response. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message state (Literal["redacted", "omitted"]): Whether the reasoning content was redacted by the provider or simply omitted by the API hidden_reasoning (Optional[str]): The internal reasoning of the agent - `id: string` - `date: string` - `state: "redacted" | "omitted"` - `"redacted"` - `"omitted"` - `hidden_reasoning?: string | null` - `is_err?: boolean | null` - `message_type?: "hidden_reasoning_message"` The type of the message. - `"hidden_reasoning_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `ToolCallMessage` A message representing a request to call a tool (generated by the LLM to trigger tool execution). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_call (Union[ToolCall, ToolCallDelta]): The tool call - `id: string` - `date: string` - `tool_call: ToolCall | ToolCallDelta` - `ToolCall` - `arguments: string` - `name: string` - `tool_call_id: string` - `ToolCallDelta` - `arguments?: string | null` - `name?: string | null` - `tool_call_id?: string | null` - `is_err?: boolean | null` - `message_type?: "tool_call_message"` The type of the message. - `"tool_call_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `tool_calls?: Array | ToolCallDelta | null` - `Array` - `arguments: string` - `name: string` - `tool_call_id: string` - `ToolCallDelta` - `ToolReturnMessage` A message representing the return value of a tool call (generated by Letta executing the requested tool). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_return (str): The return value of the tool (deprecated, use tool_returns) status (Literal["success", "error"]): The status of the tool call (deprecated, use tool_returns) tool_call_id (str): A unique identifier for the tool call that generated this message (deprecated, use tool_returns) stdout (Optional[List(str)]): Captured stdout (e.g. prints, logs) from the tool invocation (deprecated, use tool_returns) stderr (Optional[List(str)]): Captured stderr from the tool invocation (deprecated, use tool_returns) tool_returns (Optional[List[ToolReturn]]): List of tool returns for multi-tool support - `id: string` - `date: string` - `status: "success" | "error"` - `"success"` - `"error"` - `tool_call_id: string` - `tool_return: string` - `is_err?: boolean | null` - `message_type?: "tool_return_message"` The type of the message. - `"tool_return_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `stderr?: Array | null` - `stdout?: Array | null` - `step_id?: string | null` - `tool_returns?: Array | null` - `status: "success" | "error"` - `"success"` - `"error"` - `tool_call_id: string` - `tool_return: Array | string` The tool return value - either a string or list of content parts (text/image) - `Array` - `TextContent` - `ImageContent` - `string` - `stderr?: Array | null` - `stdout?: Array | null` - `type?: "tool"` The message type to be created. - `"tool"` - `AssistantMessage` A message sent by the LLM in response to user input. Used in the LLM context. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message content (Union[str, List[LettaAssistantMessageContentUnion]]): The message content sent by the agent (can be a string or an array of content parts) - `id: string` - `content: Array | string` The message content sent by the agent (can be a string or an array of content parts) - `Array` - `text: string` The text content of the message. - `signature?: string | null` Stores a unique identifier for any reasoning associated with this text content. - `type?: "text"` The type of the message. - `"text"` - `string` - `date: string` - `is_err?: boolean | null` - `message_type?: "assistant_message"` The type of the message. - `"assistant_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `ApprovalRequestMessage` A message representing a request for approval to call a tool (generated by the LLM to trigger tool execution). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_call (ToolCall): The tool call - `id: string` - `date: string` - `tool_call: ToolCall | ToolCallDelta` The tool call that has been requested by the llm to run - `ToolCall` - `ToolCallDelta` - `is_err?: boolean | null` - `message_type?: "approval_request_message"` The type of the message. - `"approval_request_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `tool_calls?: Array | ToolCallDelta | null` The tool calls that have been requested by the llm to run, which are pending approval - `Array` - `arguments: string` - `name: string` - `tool_call_id: string` - `ToolCallDelta` - `ApprovalResponseMessage` A message representing a response form the user indicating whether a tool has been approved to run. Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message approve: (bool) Whether the tool has been approved approval_request_id: The ID of the approval request reason: (Optional[str]) An optional explanation for the provided approval status - `id: string` - `date: string` - `approval_request_id?: string | null` The message ID of the approval request - `approvals?: Array | null` The list of approval responses - `ApprovalReturn` - `approve: boolean` Whether the tool has been approved - `tool_call_id: string` The ID of the tool call that corresponds to this approval - `reason?: string | null` An optional explanation for the provided approval status - `type?: "approval"` The message type to be created. - `"approval"` - `ToolReturn` - `status: "success" | "error"` - `tool_call_id: string` - `tool_return: Array | string` The tool return value - either a string or list of content parts (text/image) - `stderr?: Array | null` - `stdout?: Array | null` - `type?: "tool"` The message type to be created. - `approve?: boolean | null` Whether the tool has been approved - `is_err?: boolean | null` - `message_type?: "approval_response_message"` The type of the message. - `"approval_response_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `reason?: string | null` An optional explanation for the provided approval status - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `SummaryMessage` A message representing a summary of the conversation. Sent to the LLM as a user or system message depending on the provider. - `id: string` - `date: string` - `summary: string` - `compaction_stats?: CompactionStats | null` Statistics about a memory compaction operation. - `context_window: number` The model's context window size - `messages_count_after: number` Number of messages after compaction - `messages_count_before: number` Number of messages before compaction - `trigger: string` What triggered the compaction (e.g., 'context_window_exceeded', 'post_step_context_check') - `context_tokens_after?: number | null` Token count after compaction (message tokens only, does not include tool definitions) - `context_tokens_before?: number | null` Token count before compaction (from LLM usage stats, includes full context sent to LLM) - `is_err?: boolean | null` - `message_type?: "summary_message"` - `"summary_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `EventMessage` A message for notifying the developer that an event that has occured (e.g. a compaction). Events are NOT part of the context window. - `id: string` - `date: string` - `event_data: Record` - `event_type: "compaction"` - `"compaction"` - `is_err?: boolean | null` - `message_type?: "event_message"` - `"event_message"` - `name?: string | null` - `otid?: string | null` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id?: string | null` - `sender_id?: string | null` - `seq_id?: number | null` - `step_id?: string | null` - `stop_reason: StopReason` The stop reason from Letta indicating why agent loop stopped execution. - `stop_reason: StopReasonType` The reason why execution stopped. - `"end_turn"` - `"error"` - `"llm_api_error"` - `"invalid_llm_response"` - `"invalid_tool_call"` - `"max_steps"` - `"max_tokens_exceeded"` - `"no_tool_call"` - `"tool_rule"` - `"cancelled"` - `"insufficient_credits"` - `"requires_approval"` - `"context_window_overflow_in_system_prompt"` - `message_type?: "stop_reason"` The type of the message. - `"stop_reason"` - `usage: Usage` The usage statistics of the agent. - `cache_write_tokens?: number | null` The number of input tokens written to cache (Anthropic only). None if not reported by provider. - `cached_input_tokens?: number | null` The number of input tokens served from cache. None if not reported by provider. - `completion_tokens?: number` The number of tokens generated by the agent. - `context_tokens?: number | null` Estimate of tokens currently in the context window. - `message_type?: "usage_statistics"` - `"usage_statistics"` - `prompt_tokens?: number` The number of tokens in the prompt. - `reasoning_tokens?: number | null` The number of reasoning/thinking tokens generated. None if not reported by provider. - `run_ids?: Array | null` The background task run IDs associated with the agent interaction - `step_count?: number` The number of steps taken by the agent. - `total_tokens?: number` The total number of tokens processed by the agent. - `logprobs?: Logprobs | null` Log probabilities of the output tokens from the last LLM call. Only present if return_logprobs was enabled. - `content?: Array | null` - `token: string` - `logprob: number` - `top_logprobs: Array` - `token: string` - `logprob: number` - `bytes?: Array | null` - `bytes?: Array | null` - `refusal?: Array | null` - `token: string` - `logprob: number` - `top_logprobs: Array` - `token: string` - `logprob: number` - `bytes?: Array | null` - `bytes?: Array | null` - `turns?: Array | null` Token data for all LLM generations in multi-turn agent interaction. Includes token IDs and logprobs for each assistant turn, plus tool result content. Only present if return_token_ids was enabled. Used for RL training with loss masking. - `role: "assistant" | "tool"` Role of this turn: 'assistant' for LLM generations (trainable), 'tool' for tool results (non-trainable). - `"assistant"` - `"tool"` - `content?: string | null` Text content. For tool turns, client tokenizes this with loss_mask=0. - `output_ids?: Array | null` Token IDs from SGLang native endpoint. Only present for assistant turns. - `output_token_logprobs?: Array> | null` Logprobs from SGLang: [[logprob, token_id, top_logprob_or_null], ...]. Only present for assistant turns. - `tool_name?: string | null` Name of the tool called. Only present for tool turns. ### Example ```typescript import Letta from '@letta-ai/letta-client'; const client = new Letta({ apiKey: process.env['LETTA_API_KEY'], // This is the default and can be omitted }); const lettaResponse = await client.conversations.messages.create('default'); console.log(lettaResponse.messages); ``` #### Response ```json { "messages": [ { "id": "id", "content": "content", "date": "2019-12-27T18:11:19.117Z", "is_err": true, "message_type": "system_message", "name": "name", "otid": "otid", "run_id": "run_id", "sender_id": "sender_id", "seq_id": 0, "step_id": "step_id" } ], "stop_reason": { "stop_reason": "end_turn", "message_type": "stop_reason" }, "usage": { "cache_write_tokens": 0, "cached_input_tokens": 0, "completion_tokens": 0, "context_tokens": 0, "message_type": "usage_statistics", "prompt_tokens": 0, "reasoning_tokens": 0, "run_ids": [ "string" ], "step_count": 0, "total_tokens": 0 }, "logprobs": { "content": [ { "token": "token", "logprob": 0, "top_logprobs": [ { "token": "token", "logprob": 0, "bytes": [ 0 ] } ], "bytes": [ 0 ] } ], "refusal": [ { "token": "token", "logprob": 0, "top_logprobs": [ { "token": "token", "logprob": 0, "bytes": [ 0 ] } ], "bytes": [ 0 ] } ] }, "turns": [ { "role": "assistant", "content": "content", "output_ids": [ 0 ], "output_token_logprobs": [ [ {} ] ], "tool_name": "tool_name" } ] } ``` ## Retrieve Conversation Stream `client.conversations.messages.stream(stringconversationID, MessageStreamParamsbody?, RequestOptionsoptions?): MessageStreamResponse | Stream` **post** `/v1/conversations/{conversation_id}/stream` Resume the stream for the most recent active run in a conversation. This endpoint allows you to reconnect to an active background stream for a conversation, enabling recovery from network interruptions. **Agent-direct mode**: Pass conversation_id="default" with agent_id in request body to retrieve the stream for the agent's most recent active run. **Direct run access**: Pass run_id directly to skip run lookup entirely. Useful for recovery from duplicate request 409 errors. **OTID lookup**: Pass otid to look up the run_id from Redis. Useful when you have the otid from a 409 error response. **Deprecated**: Passing an agent ID as conversation_id still works but will be removed. ### Parameters - `conversationID: string` The conversation identifier. Can be a conversation ID ('conv-'), 'default' for agent-direct mode (with agent_id parameter), or an agent ID ('agent-') for backwards compatibility (deprecated). - `body: MessageStreamParams` - `agent_id?: string | null` Agent ID for agent-direct mode with 'default' conversation. Use with conversation_id='default' in the URL path. - `batch_size?: number | null` Number of entries to read per batch. - `include_pings?: boolean | null` Whether to include periodic keepalive ping messages in the stream to prevent connection timeouts. - `otid?: string | null` Offline threading ID to look up the run_id. Bypasses active run lookup if run_id not provided. - `poll_interval?: number | null` Seconds to wait between polls when no new data. - `run_id?: string | null` Run ID to stream directly, bypassing run lookup. Use for recovery from duplicate requests. - `starting_after?: number` Sequence id to use as a cursor for pagination. Response will start streaming after this chunk sequence id ### Returns - `MessageStreamResponse = unknown` ### Example ```typescript import Letta from '@letta-ai/letta-client'; const client = new Letta({ apiKey: process.env['LETTA_API_KEY'], // This is the default and can be omitted }); const response = await client.conversations.messages.stream('default'); console.log(response); ``` #### Response ```json {} ``` ## Compact Conversation `client.conversations.messages.compact(stringconversationID, MessageCompactParamsbody?, RequestOptionsoptions?): CompactionResponse` **post** `/v1/conversations/{conversation_id}/compact` Compact (summarize) a conversation's message history. This endpoint summarizes the in-context messages for a specific conversation, reducing the message count while preserving important context. **Agent-direct mode**: Pass conversation_id="default" with agent_id in request body to compact the agent's default conversation messages. **Deprecated**: Passing an agent ID as conversation_id still works but will be removed. ### Parameters - `conversationID: string` The conversation identifier. Can be a conversation ID ('conv-'), 'default' for agent-direct mode (with agent_id parameter), or an agent ID ('agent-') for backwards compatibility (deprecated). - `body: MessageCompactParams` - `agent_id?: string | null` Agent ID for agent-direct mode with 'default' conversation. Use with conversation_id='default' in the URL path. - `compaction_settings?: CompactionSettings | null` Configuration for conversation compaction / summarization. Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle. - `clip_chars?: number | null` The maximum length of the summary in characters. If none, no clipping is performed. - `mode?: "all" | "sliding_window" | "self_compact_all" | "self_compact_sliding_window"` The type of summarization technique use. - `"all"` - `"sliding_window"` - `"self_compact_all"` - `"self_compact_sliding_window"` - `model?: string | null` Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults. - `model_settings?: OpenAIModelSettings | SgLangModelSettings | AnthropicModelSettings | 14 more | null` Optional model settings used to override defaults for the summarizer model. - `OpenAIModelSettings` - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "openai"` The type of the provider. - `"openai"` - `reasoning?: Reasoning` The reasoning configuration for the model. - `reasoning_effort?: "none" | "minimal" | "low" | 3 more` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `type?: "text"` The type of the response format. - `"text"` - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `json_schema: Record` The JSON schema of the response. - `type?: "json_schema"` The type of the response format. - `"json_schema"` - `JsonObjectResponseFormat` Response format for JSON object responses. - `type?: "json_object"` The type of the response format. - `"json_object"` - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `SgLangModelSettings` SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "sglang"` The type of the provider. - `"sglang"` - `reasoning?: Reasoning` The reasoning configuration for the model. - `reasoning_effort?: "none" | "minimal" | "low" | 3 more` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `tool_call_parser?: string | null` SGLang tool call parser name (for example 'glm47', 'qwen25', or 'hermes'). - `AnthropicModelSettings` - `effort?: "low" | "medium" | "high" | 2 more | null` 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?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "anthropic"` The type of the provider. - `"anthropic"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `thinking?: Thinking` The thinking configuration for the model. - `budget_tokens?: number` The maximum number of tokens the model can use for extended thinking. - `type?: "enabled" | "disabled"` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity?: "low" | "medium" | "high" | null` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `GoogleAIModelSettings` - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "google_ai"` The type of the provider. - `"google_ai"` - `response_schema?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response schema for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `thinking_config?: ThinkingConfig` The thinking configuration for the model. - `include_thoughts?: boolean` Whether to include thoughts in the model's response. - `thinking_budget?: number` The thinking budget for the model. - `GoogleVertexModelSettings` - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "google_vertex"` The type of the provider. - `"google_vertex"` - `response_schema?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response schema for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `thinking_config?: ThinkingConfig` The thinking configuration for the model. - `include_thoughts?: boolean` Whether to include thoughts in the model's response. - `thinking_budget?: number` The thinking budget for the model. - `AzureModelSettings` Azure OpenAI model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "azure"` The type of the provider. - `"azure"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `XaiModelSettings` xAI model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "xai"` The type of the provider. - `"xai"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `MoonshotModelSettings` Moonshot/Kimi model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "moonshot"` The type of the provider. - `"moonshot"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `ZaiModelSettings` Z.ai (ZhipuAI) model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "zai"` The type of the provider. - `"zai"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `thinking?: Thinking` The thinking configuration for GLM-4.5+ models. - `clear_thinking?: boolean` If False, preserved thinking is used (recommended for agents). - `type?: "enabled" | "disabled"` Whether thinking is enabled or disabled. - `"enabled"` - `"disabled"` - `MoonshotCodingModelSettings` Kimi Code model configuration (Anthropic-compatible). - `effort?: "low" | "medium" | "high" | 2 more | null` 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?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "moonshot_coding"` The type of the provider. - `"moonshot_coding"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `thinking?: Thinking` The thinking configuration for the model. - `budget_tokens?: number` The maximum number of tokens the model can use for extended thinking. - `type?: "enabled" | "disabled"` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity?: "low" | "medium" | "high" | null` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `GroqModelSettings` Groq model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "groq"` The type of the provider. - `"groq"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `DeepseekModelSettings` Deepseek model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "deepseek"` The type of the provider. - `"deepseek"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `TogetherModelSettings` Together AI model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "together"` The type of the provider. - `"together"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `BedrockModelSettings` AWS Bedrock model configuration. - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "bedrock"` The type of the provider. - `"bedrock"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `BasetenModelSettings` Baseten model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "baseten"` The type of the provider. - `"baseten"` - `temperature?: number` The temperature of the model. - `OpenRouterModelSettings` OpenRouter model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "openrouter"` The type of the provider. - `"openrouter"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `ChatGptoAuthModelSettings` ChatGPT OAuth model configuration (uses ChatGPT backend API). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "chatgpt_oauth"` The type of the provider. - `"chatgpt_oauth"` - `reasoning?: Reasoning` The reasoning configuration for the model. - `reasoning_effort?: "none" | "low" | "medium" | 2 more` The reasoning effort level for GPT-5.x and o-series models. - `"none"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `temperature?: number` The temperature of the model. - `prompt?: string | null` The prompt to use for summarization. If None, uses mode-specific default. - `prompt_acknowledgement?: boolean` Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs). - `sliding_window_percentage?: number` The percentage of the context window to keep post-summarization (only used in sliding window modes). ### Returns - `CompactionResponse` - `num_messages_after: number` - `num_messages_before: number` - `summary: string` ### Example ```typescript import Letta from '@letta-ai/letta-client'; const client = new Letta({ apiKey: process.env['LETTA_API_KEY'], // This is the default and can be omitted }); const compactionResponse = await client.conversations.messages.compact('default'); console.log(compactionResponse.num_messages_after); ``` #### Response ```json { "num_messages_after": 0, "num_messages_before": 0, "summary": "summary" } ``` ## Domain Types ### Compaction Request - `CompactionRequest` - `compaction_settings?: CompactionSettings | null` Configuration for conversation compaction / summarization. Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle. - `clip_chars?: number | null` The maximum length of the summary in characters. If none, no clipping is performed. - `mode?: "all" | "sliding_window" | "self_compact_all" | "self_compact_sliding_window"` The type of summarization technique use. - `"all"` - `"sliding_window"` - `"self_compact_all"` - `"self_compact_sliding_window"` - `model?: string | null` Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults. - `model_settings?: OpenAIModelSettings | SgLangModelSettings | AnthropicModelSettings | 14 more | null` Optional model settings used to override defaults for the summarizer model. - `OpenAIModelSettings` - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "openai"` The type of the provider. - `"openai"` - `reasoning?: Reasoning` The reasoning configuration for the model. - `reasoning_effort?: "none" | "minimal" | "low" | 3 more` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `type?: "text"` The type of the response format. - `"text"` - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `json_schema: Record` The JSON schema of the response. - `type?: "json_schema"` The type of the response format. - `"json_schema"` - `JsonObjectResponseFormat` Response format for JSON object responses. - `type?: "json_object"` The type of the response format. - `"json_object"` - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `SgLangModelSettings` SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "sglang"` The type of the provider. - `"sglang"` - `reasoning?: Reasoning` The reasoning configuration for the model. - `reasoning_effort?: "none" | "minimal" | "low" | 3 more` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `tool_call_parser?: string | null` SGLang tool call parser name (for example 'glm47', 'qwen25', or 'hermes'). - `AnthropicModelSettings` - `effort?: "low" | "medium" | "high" | 2 more | null` 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?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "anthropic"` The type of the provider. - `"anthropic"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `thinking?: Thinking` The thinking configuration for the model. - `budget_tokens?: number` The maximum number of tokens the model can use for extended thinking. - `type?: "enabled" | "disabled"` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity?: "low" | "medium" | "high" | null` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `GoogleAIModelSettings` - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "google_ai"` The type of the provider. - `"google_ai"` - `response_schema?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response schema for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `thinking_config?: ThinkingConfig` The thinking configuration for the model. - `include_thoughts?: boolean` Whether to include thoughts in the model's response. - `thinking_budget?: number` The thinking budget for the model. - `GoogleVertexModelSettings` - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "google_vertex"` The type of the provider. - `"google_vertex"` - `response_schema?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response schema for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `thinking_config?: ThinkingConfig` The thinking configuration for the model. - `include_thoughts?: boolean` Whether to include thoughts in the model's response. - `thinking_budget?: number` The thinking budget for the model. - `AzureModelSettings` Azure OpenAI model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "azure"` The type of the provider. - `"azure"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `XaiModelSettings` xAI model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "xai"` The type of the provider. - `"xai"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `MoonshotModelSettings` Moonshot/Kimi model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "moonshot"` The type of the provider. - `"moonshot"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `ZaiModelSettings` Z.ai (ZhipuAI) model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "zai"` The type of the provider. - `"zai"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `thinking?: Thinking` The thinking configuration for GLM-4.5+ models. - `clear_thinking?: boolean` If False, preserved thinking is used (recommended for agents). - `type?: "enabled" | "disabled"` Whether thinking is enabled or disabled. - `"enabled"` - `"disabled"` - `MoonshotCodingModelSettings` Kimi Code model configuration (Anthropic-compatible). - `effort?: "low" | "medium" | "high" | 2 more | null` 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?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "moonshot_coding"` The type of the provider. - `"moonshot_coding"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `strict?: boolean` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature?: number` The temperature of the model. - `thinking?: Thinking` The thinking configuration for the model. - `budget_tokens?: number` The maximum number of tokens the model can use for extended thinking. - `type?: "enabled" | "disabled"` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity?: "low" | "medium" | "high" | null` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `GroqModelSettings` Groq model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "groq"` The type of the provider. - `"groq"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `DeepseekModelSettings` Deepseek model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "deepseek"` The type of the provider. - `"deepseek"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `TogetherModelSettings` Together AI model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "together"` The type of the provider. - `"together"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `BedrockModelSettings` AWS Bedrock model configuration. - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "bedrock"` The type of the provider. - `"bedrock"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `BasetenModelSettings` Baseten model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "baseten"` The type of the provider. - `"baseten"` - `temperature?: number` The temperature of the model. - `OpenRouterModelSettings` OpenRouter model configuration (OpenAI-compatible). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "openrouter"` The type of the provider. - `"openrouter"` - `response_format?: TextResponseFormat | JsonSchemaResponseFormat | JsonObjectResponseFormat | null` The response format for the model. - `TextResponseFormat` Response format for plain text responses. - `JsonSchemaResponseFormat` Response format for JSON schema-based responses. - `JsonObjectResponseFormat` Response format for JSON object responses. - `temperature?: number` The temperature of the model. - `ChatGptoAuthModelSettings` ChatGPT OAuth model configuration (uses ChatGPT backend API). - `max_output_tokens?: number` The maximum number of tokens the model can generate. - `parallel_tool_calls?: boolean` Whether to enable parallel tool calling. - `provider_type?: "chatgpt_oauth"` The type of the provider. - `"chatgpt_oauth"` - `reasoning?: Reasoning` The reasoning configuration for the model. - `reasoning_effort?: "none" | "low" | "medium" | 2 more` The reasoning effort level for GPT-5.x and o-series models. - `"none"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `temperature?: number` The temperature of the model. - `prompt?: string | null` The prompt to use for summarization. If None, uses mode-specific default. - `prompt_acknowledgement?: boolean` Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs). - `sliding_window_percentage?: number` The percentage of the context window to keep post-summarization (only used in sliding window modes). ### Compaction Response - `CompactionResponse` - `num_messages_after: number` - `num_messages_before: number` - `summary: string` ### Message Stream Response - `MessageStreamResponse = unknown`