## List Agents `agents.list(AgentListParams**kwargs) -> SyncArrayPage[AgentState]` **get** `/v1/agents/` Get a list of all agents. ### Parameters - `after: Optional[str]` Cursor for pagination - `ascending: Optional[bool]` Whether to sort agents oldest to newest (True) or newest to oldest (False, default) - `base_template_id: Optional[str]` Search agents by base template ID - `before: Optional[str]` Cursor for pagination - `created_by_id: Optional[str]` Filter agents by the user who created them. - `identifier_keys: Optional[Sequence[str]]` Search agents by identifier keys - `identity_id: Optional[str]` Search agents by identity ID - `include: Optional[List[Literal["agent.blocks", "agent.identities", "agent.managed_group", 5 more]]]` Specify which relational fields to include in the response. No relationships are included by default. - `"agent.blocks"` - `"agent.identities"` - `"agent.managed_group"` - `"agent.pending_approval"` - `"agent.secrets"` - `"agent.sources"` - `"agent.tags"` - `"agent.tools"` - `include_relationships: Optional[Sequence[str]]` Specify which relational fields (e.g., 'tools', 'sources', 'memory') to include in the response. If not provided, all relationships are loaded by default. Using this can optimize performance by reducing unnecessary joins.This is a legacy parameter, and no longer supported after 1.0.0 SDK versions. - `last_stop_reason: Optional[StopReasonType]` Filter agents by their last stop reason. - `"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"` - `limit: Optional[int]` Limit for pagination - `match_all_tags: Optional[bool]` If True, only returns agents that match ALL given tags. Otherwise, return agents that have ANY of the passed-in tags. - `name: Optional[str]` Name of the agent - `order: Optional[Literal["asc", "desc"]]` Sort order for agents by creation time. 'asc' for oldest first, 'desc' for newest first - `"asc"` - `"desc"` - `order_by: Optional[Literal["created_at", "updated_at", "last_run_completion"]]` Field to sort by - `"created_at"` - `"updated_at"` - `"last_run_completion"` - `project_id: Optional[str]` Search agents by project ID - this will default to your default project on cloud - `query_text: Optional[str]` Search agents by name - `sort_by: Optional[str]` Field to sort by. Options: 'created_at' (default), 'last_run_completion' - `tags: Optional[Sequence[str]]` List of tags to filter agents by - `template_id: Optional[str]` Search agents by template ID ### Returns - `class AgentState: …` Representation of an agent's state. This is the state of the agent at a given time, and is persisted in the DB backend. The state has all the information needed to recreate a persisted agent. - `id: str` The id of the agent. Assigned by the database. - `agent_type: AgentType` The type of agent. - `"memgpt_agent"` - `"memgpt_v2_agent"` - `"letta_v1_agent"` - `"react_agent"` - `"workflow_agent"` - `"split_thread_agent"` - `"sleeptime_agent"` - `"voice_convo_agent"` - `"voice_sleeptime_agent"` - `blocks: List[Block]` The memory blocks used by the agent. - `value: str` Value of the block. - `id: Optional[str]` The human-friendly ID of the Block - `base_template_id: Optional[str]` The base template id of the block. - `created_by_id: Optional[str]` The id of the user that made this Block. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` Description of the block. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the block will be hidden. - `is_template: Optional[bool]` Whether the block is a template (e.g. saved human/persona options). - `label: Optional[str]` Label of the block (e.g. 'human', 'persona') in the context window. - `last_updated_by_id: Optional[str]` The id of the user that last updated this Block. - `limit: Optional[int]` Character limit of the block. - `metadata: Optional[Dict[str, object]]` Metadata of the block. - `preserve_on_migration: Optional[bool]` Preserve the block on template migration. - `project_id: Optional[str]` The associated project id. - `read_only: Optional[bool]` Whether the agent has read-only access to the block. - `tags: Optional[List[str]]` The tags associated with the block. - `template_id: Optional[str]` The id of the template. - `template_name: Optional[str]` Name of the block if it is a template. - `llm_config: LlmConfig` Deprecated: Use `model` field instead. The LLM configuration used by the agent. - `context_window: int` The context window size for the model. - `model: str` LLM model name. - `model_endpoint_type: Literal["openai", "anthropic", "google_ai", 27 more]` The endpoint type for the model. - `"openai"` - `"anthropic"` - `"google_ai"` - `"google_vertex"` - `"azure"` - `"groq"` - `"ollama"` - `"webui"` - `"webui-legacy"` - `"lmstudio"` - `"lmstudio-legacy"` - `"lmstudio-chatcompletions"` - `"llamacpp"` - `"koboldcpp"` - `"vllm"` - `"hugging-face"` - `"minimax"` - `"moonshot"` - `"moonshot_coding"` - `"mistral"` - `"together"` - `"bedrock"` - `"deepseek"` - `"xai"` - `"zai"` - `"zai_coding"` - `"baseten"` - `"fireworks"` - `"openrouter"` - `"chatgpt_oauth"` - `compatibility_type: Optional[Literal["gguf", "mlx"]]` The framework compatibility type for the model. - `"gguf"` - `"mlx"` - `display_name: Optional[str]` A human-friendly display name for the model. - `effort: Optional[Literal["low", "medium", "high", 2 more]]` The effort level for Anthropic models that support it (Opus 4.5+). Controls token spending and thinking behavior. Not setting this gives similar performance to 'high'. - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `"max"` - `enable_reasoner: Optional[bool]` Whether or not the model should use extended thinking if it is a 'reasoning' style model - `frequency_penalty: Optional[float]` Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. From OpenAI: Number between -2.0 and 2.0. - `handle: Optional[str]` The handle for this config, in the format provider/model-name. - `max_reasoning_tokens: Optional[int]` Configurable thinking budget for extended thinking. Used for enable_reasoner and also for Google Vertex models like Gemini 2.5 Flash. Minimum value is 1024 when used with enable_reasoner. - `max_tokens: Optional[int]` The maximum number of tokens to generate. If not set, the model will use its default value. - `model_endpoint: Optional[str]` The endpoint for the model. - `model_wrapper: Optional[str]` The wrapper for the model. - `parallel_tool_calls: Optional[bool]` Deprecated: Use model_settings to configure parallel tool calls instead. If set to True, enables parallel tool calling. Defaults to False. - `provider_category: Optional[ProviderCategory]` The provider category for the model. - `"base"` - `"byok"` - `provider_name: Optional[str]` The provider name for the model. - `put_inner_thoughts_in_kwargs: Optional[bool]` Puts 'inner_thoughts' as a kwarg in the function call if this is set to True. This helps with function calling performance and also the generation of inner thoughts. - `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's output. Supports text, json_object, and json_schema (structured outputs). Can be set via model_settings. - `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"` - `return_logprobs: Optional[bool]` Whether to return log probabilities of the output tokens. Useful for RL training. - `return_token_ids: Optional[bool]` Whether to return token IDs for all LLM generations via SGLang native endpoint. Required for multi-turn RL training with loss masking. Only works with SGLang provider. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool schemas include strict: true and additionalProperties: false, guaranteeing tool outputs match JSON schemas. - `temperature: Optional[float]` The temperature to use when generating text with the model. A higher temperature will result in more random text. - `tier: Optional[str]` The cost tier for the model (cloud only). - `tool_call_parser: Optional[str]` SGLang tool call parser name (e.g. 'glm47', 'qwen25', 'hermes'). Used by the SGLang native adapter to parse tool calls from raw model output. - `top_logprobs: Optional[int]` Number of most likely tokens to return at each position (0-20). Requires return_logprobs=True. - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `memory: Memory` Deprecated: Use `blocks` field instead. The in-context memory of the agent. - `blocks: List[Block]` Memory blocks contained in the agent's in-context memory - `value: str` Value of the block. - `id: Optional[str]` The human-friendly ID of the Block - `base_template_id: Optional[str]` The base template id of the block. - `created_by_id: Optional[str]` The id of the user that made this Block. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` Description of the block. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the block will be hidden. - `is_template: Optional[bool]` Whether the block is a template (e.g. saved human/persona options). - `label: Optional[str]` Label of the block (e.g. 'human', 'persona') in the context window. - `last_updated_by_id: Optional[str]` The id of the user that last updated this Block. - `limit: Optional[int]` Character limit of the block. - `metadata: Optional[Dict[str, object]]` Metadata of the block. - `preserve_on_migration: Optional[bool]` Preserve the block on template migration. - `project_id: Optional[str]` The associated project id. - `read_only: Optional[bool]` Whether the agent has read-only access to the block. - `tags: Optional[List[str]]` The tags associated with the block. - `template_id: Optional[str]` The id of the template. - `template_name: Optional[str]` Name of the block if it is a template. - `agent_type: Optional[Union[AgentType, str, null]]` Agent type controlling prompt rendering. - `Literal["memgpt_agent", "memgpt_v2_agent", "letta_v1_agent", 6 more]` - `"memgpt_agent"` - `"memgpt_v2_agent"` - `"letta_v1_agent"` - `"react_agent"` - `"workflow_agent"` - `"split_thread_agent"` - `"sleeptime_agent"` - `"voice_convo_agent"` - `"voice_sleeptime_agent"` - `str` - `file_blocks: Optional[List[MemoryFileBlock]]` Special blocks representing the agent's in-context memory of an attached file - `file_id: str` Unique identifier of the file. - `is_open: bool` True if the agent currently has the file open. - `source_id: str` Deprecated: Use `folder_id` field instead. Unique identifier of the source. - `value: str` Value of the block. - `id: Optional[str]` The human-friendly ID of the Block - `base_template_id: Optional[str]` The base template id of the block. - `created_by_id: Optional[str]` The id of the user that made this Block. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` Description of the block. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the block will be hidden. - `is_template: Optional[bool]` Whether the block is a template (e.g. saved human/persona options). - `label: Optional[str]` Label of the block (e.g. 'human', 'persona') in the context window. - `last_accessed_at: Optional[datetime]` UTC timestamp of the agent’s most recent access to this file. Any operations from the open, close, or search tools will update this field. - `last_updated_by_id: Optional[str]` The id of the user that last updated this Block. - `limit: Optional[int]` Character limit of the block. - `metadata: Optional[Dict[str, object]]` Metadata of the block. - `preserve_on_migration: Optional[bool]` Preserve the block on template migration. - `project_id: Optional[str]` The associated project id. - `read_only: Optional[bool]` Whether the agent has read-only access to the block. - `tags: Optional[List[str]]` The tags associated with the block. - `template_id: Optional[str]` The id of the template. - `template_name: Optional[str]` Name of the block if it is a template. - `git_enabled: Optional[bool]` Whether this agent uses git-backed memory with structured labels. - `prompt_template: Optional[str]` Deprecated. Ignored for performance. - `name: str` The name of the agent. - `sources: List[Source]` Deprecated: Use `folders` field instead. The sources used by the agent. - `id: str` The human-friendly ID of the Source - `embedding_config: EmbeddingConfig` The embedding configuration used by the source. - `embedding_dim: int` The dimension of the embedding. - `embedding_endpoint_type: Literal["openai", "anthropic", "bedrock", 16 more]` The endpoint type for the model. - `"openai"` - `"anthropic"` - `"bedrock"` - `"google_ai"` - `"google_vertex"` - `"azure"` - `"groq"` - `"ollama"` - `"webui"` - `"webui-legacy"` - `"lmstudio"` - `"lmstudio-legacy"` - `"llamacpp"` - `"koboldcpp"` - `"vllm"` - `"hugging-face"` - `"mistral"` - `"together"` - `"pinecone"` - `embedding_model: str` The model for the embedding. - `azure_deployment: Optional[str]` The Azure deployment for the model. - `azure_endpoint: Optional[str]` The Azure endpoint for the model. - `azure_version: Optional[str]` The Azure version for the model. - `batch_size: Optional[int]` The maximum batch size for processing embeddings. - `embedding_chunk_size: Optional[int]` The chunk size of the embedding. - `embedding_endpoint: Optional[str]` The endpoint for the model (`None` if local). - `handle: Optional[str]` The handle for this config, in the format provider/model-name. - `name: str` The name of the source. - `created_at: Optional[datetime]` The timestamp when the source was created. - `created_by_id: Optional[str]` The id of the user that made this Tool. - `description: Optional[str]` The description of the source. - `instructions: Optional[str]` Instructions for how to use the source. - `last_updated_by_id: Optional[str]` The id of the user that made this Tool. - `metadata: Optional[Dict[str, object]]` Metadata associated with the source. - `updated_at: Optional[datetime]` The timestamp when the source was last updated. - `vector_db_provider: Optional[VectorDBProvider]` The vector database provider used for this source's passages - `"native"` - `"tpuf"` - `"pinecone"` - `system: str` The system prompt used by the agent. - `tags: List[str]` The tags associated with the agent. - `tools: List[Tool]` The tools used by the agent. - `id: str` The human-friendly ID of the Tool - `args_json_schema: Optional[Dict[str, object]]` The args JSON schema of the function. - `created_by_id: Optional[str]` The id of the user that made this Tool. - `default_requires_approval: Optional[bool]` Default value for whether or not executing this tool requires approval. - `description: Optional[str]` The description of the tool. - `enable_parallel_execution: Optional[bool]` If set to True, then this tool will potentially be executed concurrently with other tools. Default False. - `json_schema: Optional[Dict[str, object]]` The JSON schema of the function. - `last_updated_by_id: Optional[str]` The id of the user that made this Tool. - `metadata: Optional[Dict[str, object]]` A dictionary of additional metadata for the tool. - `name: Optional[str]` The name of the function. - `npm_requirements: Optional[List[NpmRequirement]]` Optional list of npm packages required by this tool. - `name: str` Name of the npm package. - `version: Optional[str]` Optional version of the package, following semantic versioning. - `pip_requirements: Optional[List[PipRequirement]]` Optional list of pip packages required by this tool. - `name: str` Name of the pip package. - `version: Optional[str]` Optional version of the package, following semantic versioning. - `project_id: Optional[str]` The project id of the tool. - `return_char_limit: Optional[int]` The maximum number of characters in the response. - `source_code: Optional[str]` The source code of the function. - `source_type: Optional[str]` The type of the source code. - `tags: Optional[List[str]]` Metadata tags. - `tool_type: Optional[ToolType]` The type of the tool. - `"custom"` - `"letta_core"` - `"letta_memory_core"` - `"letta_multi_agent_core"` - `"letta_sleeptime_core"` - `"letta_voice_sleeptime_core"` - `"letta_builtin"` - `"letta_files_core"` - `"external_langchain"` - `"external_composio"` - `"external_mcp"` - `base_template_id: Optional[str]` The base template id of the agent. - `compaction_settings: Optional[CompactionSettings]` Configuration for conversation compaction / summarization. Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle. - `clip_chars: Optional[int]` The maximum length of the summary in characters. If none, no clipping is performed. - `mode: Optional[Literal["all", "sliding_window", "self_compact_all", "self_compact_sliding_window"]]` The type of summarization technique use. - `"all"` - `"sliding_window"` - `"self_compact_all"` - `"self_compact_sliding_window"` - `model: Optional[str]` Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults. - `model_settings: Optional[CompactionSettingsModelSettings]` Optional model settings used to override defaults for the summarizer model. - `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. - `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 CompactionSettingsModelSettingsSgLangModelSettings: …` SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["sglang"]]` The type of the provider. - `"sglang"` - `reasoning: Optional[CompactionSettingsModelSettingsSgLangModelSettingsReasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[CompactionSettingsModelSettingsSgLangModelSettingsResponseFormat]` 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 CompactionSettingsModelSettingsMoonshotModelSettings: …` Moonshot/Kimi model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["moonshot"]]` The type of the provider. - `"moonshot"` - `response_format: Optional[CompactionSettingsModelSettingsMoonshotModelSettingsResponseFormat]` 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 CompactionSettingsModelSettingsZaiModelSettings: …` Z.ai (ZhipuAI) model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["zai"]]` The type of the provider. - `"zai"` - `response_format: Optional[CompactionSettingsModelSettingsZaiModelSettingsResponseFormat]` 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[CompactionSettingsModelSettingsZaiModelSettingsThinking]` The thinking configuration for GLM-4.5+ models. - `clear_thinking: Optional[bool]` If False, preserved thinking is used (recommended for agents). - `type: Optional[Literal["enabled", "disabled"]]` Whether thinking is enabled or disabled. - `"enabled"` - `"disabled"` - `class CompactionSettingsModelSettingsMoonshotCodingModelSettings: …` Kimi Code model configuration (Anthropic-compatible). - `effort: Optional[Literal["low", "medium", "high", 2 more]]` Effort level for supported Anthropic models (controls token spending). 'xhigh' and 'max' are available on Opus 4.6+. Not setting this gives similar performance to 'high'. - `"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[CompactionSettingsModelSettingsMoonshotCodingModelSettingsResponseFormat]` 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[CompactionSettingsModelSettingsMoonshotCodingModelSettingsThinking]` The thinking configuration for the model. - `budget_tokens: Optional[int]` The maximum number of tokens the model can use for extended thinking. - `type: Optional[Literal["enabled", "disabled"]]` The type of thinking to use. - `"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 CompactionSettingsModelSettingsBasetenModelSettings: …` Baseten model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["baseten"]]` The type of the provider. - `"baseten"` - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsOpenRouterModelSettings: …` OpenRouter model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["openrouter"]]` The type of the provider. - `"openrouter"` - `response_format: Optional[CompactionSettingsModelSettingsOpenRouterModelSettingsResponseFormat]` 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 CompactionSettingsModelSettingsChatGptoAuthModelSettings: …` ChatGPT OAuth model configuration (uses ChatGPT backend API). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["chatgpt_oauth"]]` The type of the provider. - `"chatgpt_oauth"` - `reasoning: Optional[CompactionSettingsModelSettingsChatGptoAuthModelSettingsReasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]` The reasoning effort level for GPT-5.x and o-series models. - `"none"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `temperature: Optional[float]` The temperature of the model. - `prompt: Optional[str]` The prompt to use for summarization. If None, uses mode-specific default. - `prompt_acknowledgement: Optional[bool]` Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs). - `sliding_window_percentage: Optional[float]` The percentage of the context window to keep post-summarization (only used in sliding window modes). - `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. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` The description of the agent. - `embedding: Optional[str]` The embedding model handle used by the agent (format: provider/model-name). - `embedding_config: Optional[EmbeddingConfig]` Configuration for embedding model connection and processing parameters. - `enable_sleeptime: Optional[bool]` If set to True, memory management will move to a background agent thread. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the agent will be hidden. - `identities: Optional[List[Identity]]` The identities associated with this agent. - `id: str` The human-friendly ID of the Identity - `agent_ids: List[str]` The IDs of the agents associated with the identity. - `block_ids: List[str]` The IDs of the blocks associated with the identity. - `identifier_key: str` External, user-generated identifier key of the identity. - `identity_type: Literal["org", "user", "other"]` The type of the identity. - `"org"` - `"user"` - `"other"` - `name: str` The name of the identity. - `project_id: Optional[str]` The project id of the identity, if applicable. - `properties: Optional[List[IdentityProperty]]` List of properties associated with the identity - `key: str` The key of the property - `type: Literal["string", "number", "boolean", "json"]` The type of the property - `"string"` - `"number"` - `"boolean"` - `"json"` - `value: Union[str, float, bool, Dict[str, object]]` The value of the property - `str` - `float` - `bool` - `Dict[str, object]` - `identity_ids: Optional[List[str]]` Deprecated: Use `identities` field instead. The ids of the identities associated with this agent. - `last_run_completion: Optional[datetime]` The timestamp when the agent last completed a run. - `last_run_duration_ms: Optional[int]` The duration in milliseconds of the agent's last run. - `last_stop_reason: Optional[StopReasonType]` The stop reason from the agent's last run. - `"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"` - `last_updated_by_id: Optional[str]` The id of the user that made this object. - `managed_group: Optional[ManagedGroup]` The multi-agent group that this agent manages - `id: str` The id of the group. Assigned by the database. - `agent_ids: List[str]` - `description: str` - `manager_type: Literal["round_robin", "supervisor", "dynamic", 3 more]` - `"round_robin"` - `"supervisor"` - `"dynamic"` - `"sleeptime"` - `"voice_sleeptime"` - `"swarm"` - `base_template_id: Optional[str]` The base template id. - `deployment_id: Optional[str]` The id of the deployment. - `hidden: Optional[bool]` If set to True, the group will be hidden. - `last_processed_message_id: Optional[str]` - `manager_agent_id: Optional[str]` - `max_message_buffer_length: Optional[int]` The desired maximum length of messages in the context window of the convo agent. This is a best effort, and may be off slightly due to user/assistant interleaving. - `max_turns: Optional[int]` - `min_message_buffer_length: Optional[int]` The desired minimum length of messages in the context window of the convo agent. This is a best effort, and may be off-by-one due to user/assistant interleaving. - `project_id: Optional[str]` The associated project id. - `shared_block_ids: Optional[List[str]]` - `sleeptime_agent_frequency: Optional[int]` - `template_id: Optional[str]` The id of the template. - `termination_token: Optional[str]` - `turns_counter: Optional[int]` - `max_files_open: Optional[int]` Maximum number of files that can be open at once for this agent. Setting this too high may exceed the context window, which will break the agent. - `message_buffer_autoclear: Optional[bool]` If set to True, the agent will not remember previous messages (though the agent will still retain state via core memory blocks and archival/recall memory). Not recommended unless you have an advanced use case. - `message_ids: Optional[List[str]]` The ids of the messages in the agent's in-context memory. - `metadata: Optional[Dict[str, object]]` The metadata of the agent. - `model: Optional[str]` The model handle used by the agent (format: provider/model-name). - `model_settings: Optional[ModelSettings]` The model settings used by the agent. - `class OpenAIModelSettings: …` - `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: …` - `class GoogleAIModelSettings: …` - `class GoogleVertexModelSettings: …` - `class AzureModelSettings: …` Azure OpenAI model configuration (OpenAI-compatible). - `class XaiModelSettings: …` xAI model configuration (OpenAI-compatible). - `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). - `class DeepseekModelSettings: …` Deepseek model configuration (OpenAI-compatible). - `class TogetherModelSettings: …` Together AI model configuration (OpenAI-compatible). - `class BedrockModelSettings: …` AWS Bedrock model configuration. - `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. - `multi_agent_group: Optional[MultiAgentGroup]` Deprecated: Use `managed_group` field instead. The multi-agent group that this agent manages. - `id: str` The id of the group. Assigned by the database. - `agent_ids: List[str]` - `description: str` - `manager_type: Literal["round_robin", "supervisor", "dynamic", 3 more]` - `"round_robin"` - `"supervisor"` - `"dynamic"` - `"sleeptime"` - `"voice_sleeptime"` - `"swarm"` - `base_template_id: Optional[str]` The base template id. - `deployment_id: Optional[str]` The id of the deployment. - `hidden: Optional[bool]` If set to True, the group will be hidden. - `last_processed_message_id: Optional[str]` - `manager_agent_id: Optional[str]` - `max_message_buffer_length: Optional[int]` The desired maximum length of messages in the context window of the convo agent. This is a best effort, and may be off slightly due to user/assistant interleaving. - `max_turns: Optional[int]` - `min_message_buffer_length: Optional[int]` The desired minimum length of messages in the context window of the convo agent. This is a best effort, and may be off-by-one due to user/assistant interleaving. - `project_id: Optional[str]` The associated project id. - `shared_block_ids: Optional[List[str]]` - `sleeptime_agent_frequency: Optional[int]` - `template_id: Optional[str]` The id of the template. - `termination_token: Optional[str]` - `turns_counter: Optional[int]` - `pending_approval: Optional[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: str` - `date: datetime` - `tool_call: ToolCall` The tool call that has been requested by the llm to run - `class ToolCall: …` - `arguments: str` - `name: str` - `tool_call_id: str` - `class ToolCallDelta: …` - `arguments: Optional[str]` - `name: Optional[str]` - `tool_call_id: Optional[str]` - `is_err: Optional[bool]` - `message_type: Optional[Literal["approval_request_message"]]` The type of the message. - `"approval_request_message"` - `name: Optional[str]` - `otid: Optional[str]` 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: Optional[str]` - `sender_id: Optional[str]` - `seq_id: Optional[int]` - `step_id: Optional[str]` - `tool_calls: Optional[ToolCalls]` The tool calls that have been requested by the llm to run, which are pending approval - `List[ToolCall]` - `arguments: str` - `name: str` - `tool_call_id: str` - `class ToolCallDelta: …` - `per_file_view_window_char_limit: Optional[int]` The per-file view window character limit for this agent. Setting this too high may exceed the context window, which will break the agent. - `project_id: Optional[str]` The id of the project the agent belongs to. - `response_format: Optional[ResponseFormat]` The response format used by the agent - `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. - `secrets: Optional[List[AgentEnvironmentVariable]]` The environment variables for tool execution specific to this agent. - `agent_id: str` The ID of the agent this environment variable belongs to. - `key: str` The name of the environment variable. - `value: str` The value of the environment variable. - `id: Optional[str]` The human-friendly ID of the Agent-env - `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]` An optional description of the environment variable. - `last_updated_by_id: Optional[str]` The id of the user that made this object. - `updated_at: Optional[datetime]` The timestamp when the object was last updated. - `value_enc: Optional[str]` Encrypted secret value (stored as encrypted string) - `template_id: Optional[str]` The id of the template the agent belongs to. - `timezone: Optional[str]` The timezone of the agent (IANA format). - `tool_exec_environment_variables: Optional[List[AgentEnvironmentVariable]]` Deprecated: use `secrets` field instead. - `agent_id: str` The ID of the agent this environment variable belongs to. - `key: str` The name of the environment variable. - `value: str` The value of the environment variable. - `id: Optional[str]` The human-friendly ID of the Agent-env - `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]` An optional description of the environment variable. - `last_updated_by_id: Optional[str]` The id of the user that made this object. - `updated_at: Optional[datetime]` The timestamp when the object was last updated. - `value_enc: Optional[str]` Encrypted secret value (stored as encrypted string) - `tool_rules: Optional[List[ToolRule]]` The list of tool rules. - `class ChildToolRule: …` A ToolRule represents a tool that can be invoked by the agent. - `children: List[str]` The children tools that can be invoked. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `child_arg_nodes: Optional[List[ChildArgNode]]` Optional list of typed child argument overrides. Each node must reference a child in 'children'. - `name: str` The name of the child tool to invoke next. - `args: Optional[Dict[str, object]]` Optional prefilled arguments for this child tool. Keys must match the tool's parameter names and values must satisfy the tool's JSON schema. Supports partial prefill; non-overlapping parameters are left to the model. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["constrain_child_tools"]]` - `"constrain_child_tools"` - `class InitToolRule: …` Represents the initial tool rule configuration. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `args: Optional[Dict[str, object]]` Optional prefilled arguments for this tool. When present, these values will override any LLM-provided arguments with the same keys during invocation. Keys must match the tool's parameter names and values must satisfy the tool's JSON schema. Supports partial prefill; non-overlapping parameters are left to the model. - `prompt_template: Optional[str]` Optional template string (ignored). Rendering uses fast built-in formatting for performance. - `type: Optional[Literal["run_first"]]` - `"run_first"` - `class TerminalToolRule: …` Represents a terminal tool rule configuration where if this tool gets called, it must end the agent loop. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["exit_loop"]]` - `"exit_loop"` - `class ConditionalToolRule: …` A ToolRule that conditionally maps to different child tools based on the output. - `child_output_mapping: Dict[str, str]` The output case to check for mapping - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `default_child: Optional[str]` The default child tool to be called. If None, any tool can be called. - `prompt_template: Optional[str]` Optional template string (ignored). - `require_output_mapping: Optional[bool]` Whether to throw an error when output doesn't match any case - `type: Optional[Literal["conditional"]]` - `"conditional"` - `class ContinueToolRule: …` Represents a tool rule configuration where if this tool gets called, it must continue the agent loop. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["continue_loop"]]` - `"continue_loop"` - `class RequiredBeforeExitToolRule: …` Represents a tool rule configuration where this tool must be called before the agent loop can exit. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["required_before_exit"]]` - `"required_before_exit"` - `class MaxCountPerStepToolRule: …` Represents a tool rule configuration which constrains the total number of times this tool can be invoked in a single step. - `max_count_limit: int` The max limit for the total number of times this tool can be invoked in a single step. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["max_count_per_step"]]` - `"max_count_per_step"` - `class ParentToolRule: …` A ToolRule that only allows a child tool to be called if the parent has been called. - `children: List[str]` The children tools that can be invoked. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["parent_last_tool"]]` - `"parent_last_tool"` - `class RequiresApprovalToolRule: …` Represents a tool rule configuration which requires approval before the tool can be invoked. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). Rendering uses fast built-in formatting for performance. - `type: Optional[Literal["requires_approval"]]` - `"requires_approval"` - `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 ) page = client.agents.list() page = page.items[0] print(page.id) ``` #### Response ```json [ { "id": "id", "agent_type": "memgpt_agent", "blocks": [ { "value": "value", "id": "block-123e4567-e89b-12d3-a456-426614174000", "base_template_id": "base_template_id", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "entity_id": "entity_id", "hidden": true, "is_template": true, "label": "label", "last_updated_by_id": "last_updated_by_id", "limit": 0, "metadata": { "foo": "bar" }, "preserve_on_migration": true, "project_id": "project_id", "read_only": true, "tags": [ "string" ], "template_id": "template_id", "template_name": "template_name" } ], "llm_config": { "context_window": 0, "model": "model", "model_endpoint_type": "openai", "compatibility_type": "gguf", "display_name": "display_name", "effort": "low", "enable_reasoner": true, "frequency_penalty": 0, "handle": "handle", "max_reasoning_tokens": 0, "max_tokens": 0, "model_endpoint": "model_endpoint", "model_wrapper": "model_wrapper", "parallel_tool_calls": true, "provider_category": "base", "provider_name": "provider_name", "put_inner_thoughts_in_kwargs": true, "reasoning_effort": "none", "response_format": { "type": "text" }, "return_logprobs": true, "return_token_ids": true, "strict": true, "temperature": 0, "tier": "tier", "tool_call_parser": "tool_call_parser", "top_logprobs": 0, "verbosity": "low" }, "memory": { "blocks": [ { "value": "value", "id": "block-123e4567-e89b-12d3-a456-426614174000", "base_template_id": "base_template_id", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "entity_id": "entity_id", "hidden": true, "is_template": true, "label": "label", "last_updated_by_id": "last_updated_by_id", "limit": 0, "metadata": { "foo": "bar" }, "preserve_on_migration": true, "project_id": "project_id", "read_only": true, "tags": [ "string" ], "template_id": "template_id", "template_name": "template_name" } ], "agent_type": "memgpt_agent", "file_blocks": [ { "file_id": "file_id", "is_open": true, "source_id": "source_id", "value": "value", "id": "block-123e4567-e89b-12d3-a456-426614174000", "base_template_id": "base_template_id", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "entity_id": "entity_id", "hidden": true, "is_template": true, "label": "label", "last_accessed_at": "2019-12-27T18:11:19.117Z", "last_updated_by_id": "last_updated_by_id", "limit": 0, "metadata": { "foo": "bar" }, "preserve_on_migration": true, "project_id": "project_id", "read_only": true, "tags": [ "string" ], "template_id": "template_id", "template_name": "template_name" } ], "git_enabled": true, "prompt_template": "prompt_template" }, "name": "name", "sources": [ { "id": "source-123e4567-e89b-12d3-a456-426614174000", "embedding_config": { "embedding_dim": 0, "embedding_endpoint_type": "openai", "embedding_model": "embedding_model", "azure_deployment": "azure_deployment", "azure_endpoint": "azure_endpoint", "azure_version": "azure_version", "batch_size": 0, "embedding_chunk_size": 0, "embedding_endpoint": "embedding_endpoint", "handle": "handle" }, "name": "name", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "instructions": "instructions", "last_updated_by_id": "last_updated_by_id", "metadata": { "foo": "bar" }, "updated_at": "2019-12-27T18:11:19.117Z", "vector_db_provider": "native" } ], "system": "system", "tags": [ "string" ], "tools": [ { "id": "tool-123e4567-e89b-12d3-a456-426614174000", "args_json_schema": { "foo": "bar" }, "created_by_id": "created_by_id", "default_requires_approval": true, "description": "description", "enable_parallel_execution": true, "json_schema": { "foo": "bar" }, "last_updated_by_id": "last_updated_by_id", "metadata_": { "foo": "bar" }, "name": "name", "npm_requirements": [ { "name": "x", "version": "version" } ], "pip_requirements": [ { "name": "x", "version": "version" } ], "project_id": "project_id", "return_char_limit": 1, "source_code": "source_code", "source_type": "source_type", "tags": [ "string" ], "tool_type": "custom" } ], "base_template_id": "base_template_id", "compaction_settings": { "clip_chars": 0, "mode": "all", "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 }, "prompt": "prompt", "prompt_acknowledgement": true, "sliding_window_percentage": 0 }, "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "embedding": "embedding", "embedding_config": { "embedding_dim": 0, "embedding_endpoint_type": "openai", "embedding_model": "embedding_model", "azure_deployment": "azure_deployment", "azure_endpoint": "azure_endpoint", "azure_version": "azure_version", "batch_size": 0, "embedding_chunk_size": 0, "embedding_endpoint": "embedding_endpoint", "handle": "handle" }, "enable_sleeptime": true, "entity_id": "entity_id", "hidden": true, "identities": [ { "id": "identity-123e4567-e89b-12d3-a456-426614174000", "agent_ids": [ "string" ], "block_ids": [ "string" ], "identifier_key": "identifier_key", "identity_type": "org", "name": "name", "project_id": "project_id", "properties": [ { "key": "key", "type": "string", "value": "string" } ] } ], "identity_ids": [ "string" ], "last_run_completion": "2019-12-27T18:11:19.117Z", "last_run_duration_ms": 0, "last_stop_reason": "end_turn", "last_updated_by_id": "last_updated_by_id", "managed_group": { "id": "id", "agent_ids": [ "string" ], "description": "description", "manager_type": "round_robin", "base_template_id": "base_template_id", "deployment_id": "deployment_id", "hidden": true, "last_processed_message_id": "last_processed_message_id", "manager_agent_id": "manager_agent_id", "max_message_buffer_length": 0, "max_turns": 0, "min_message_buffer_length": 0, "project_id": "project_id", "shared_block_ids": [ "string" ], "sleeptime_agent_frequency": 0, "template_id": "template_id", "termination_token": "termination_token", "turns_counter": 0 }, "max_files_open": 0, "message_buffer_autoclear": true, "message_ids": [ "string" ], "metadata": { "foo": "bar" }, "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 }, "multi_agent_group": { "id": "id", "agent_ids": [ "string" ], "description": "description", "manager_type": "round_robin", "base_template_id": "base_template_id", "deployment_id": "deployment_id", "hidden": true, "last_processed_message_id": "last_processed_message_id", "manager_agent_id": "manager_agent_id", "max_message_buffer_length": 0, "max_turns": 0, "min_message_buffer_length": 0, "project_id": "project_id", "shared_block_ids": [ "string" ], "sleeptime_agent_frequency": 0, "template_id": "template_id", "termination_token": "termination_token", "turns_counter": 0 }, "pending_approval": { "id": "id", "date": "2019-12-27T18:11:19.117Z", "tool_call": { "arguments": "arguments", "name": "name", "tool_call_id": "tool_call_id" }, "is_err": true, "message_type": "approval_request_message", "name": "name", "otid": "otid", "run_id": "run_id", "sender_id": "sender_id", "seq_id": 0, "step_id": "step_id", "tool_calls": [ { "arguments": "arguments", "name": "name", "tool_call_id": "tool_call_id" } ] }, "per_file_view_window_char_limit": 0, "project_id": "project_id", "response_format": { "type": "text" }, "secrets": [ { "agent_id": "agent_id", "key": "key", "value": "value", "id": "agent-env-123e4567-e89b-12d3-a456-426614174000", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "last_updated_by_id": "last_updated_by_id", "updated_at": "2019-12-27T18:11:19.117Z", "value_enc": "value_enc" } ], "template_id": "template_id", "timezone": "timezone", "tool_exec_environment_variables": [ { "agent_id": "agent_id", "key": "key", "value": "value", "id": "agent-env-123e4567-e89b-12d3-a456-426614174000", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "last_updated_by_id": "last_updated_by_id", "updated_at": "2019-12-27T18:11:19.117Z", "value_enc": "value_enc" } ], "tool_rules": [ { "children": [ "string" ], "tool_name": "tool_name", "child_arg_nodes": [ { "name": "name", "args": { "foo": "bar" } } ], "prompt_template": "prompt_template", "type": "constrain_child_tools" } ], "updated_at": "2019-12-27T18:11:19.117Z" } ] ```