List Agents For Identity

identities.agents.list(, ) -> SyncArrayPage[AgentState]

get/v1/identities/{identity_id}/agents

Get all agents associated with the specified identity.

ParametersExpand Collapse

identity_id: str

The ID of the identity in the format 'identity-'

minLength45

maxLength45

after: Optional[str]

Agent ID cursor for pagination. Returns agents that come after this agent ID in the specified sort order

before: Optional[str]

Agent ID cursor for pagination. Returns agents that come before this agent ID in the specified sort order

include: Optional[List[Literal["agent.blocks", "agent.identities", "agent.managed_group", 4 more]]]

Specify which relational fields to include in the response. No relationships are included by default.

Accepts one of the following:

"agent.blocks"

"agent.identities"

"agent.managed_group"

"agent.secrets"

"agent.sources"

"agent.tags"

"agent.tools"

limit: Optional[int]

Maximum number of agents to return

order: Optional[Literal["asc", "desc"]]

Sort order for agents by creation time. 'asc' for oldest first, 'desc' for newest first

Accepts one of the following:

"asc"

"desc"

order_by: Optional[Literal["created_at"]]

Field to sort by

Accepts one of the following:

"created_at"

ReturnsExpand Collapse

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.

Accepts one of the following:

"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.

template_id: Optional[str]

The id of the template.

template_name: Optional[str]

Name of the block if it is a template.

Deprecatedembedding_config: EmbeddingConfig

Deprecated: Use embedding field instead. The embedding configuration used by the agent.

embedding_dim: int

The dimension of the embedding.

embedding_endpoint_type: Literal["openai", "anthropic", "bedrock", 16 more]

The endpoint type for the model.

Accepts one of the following:

"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.

Deprecatedllm_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", 18 more]

The endpoint type for the model.

Accepts one of the following:

"openai"

"anthropic"

"google_ai"

"google_vertex"

"azure"

"groq"

"ollama"

"webui"

"webui-legacy"

"lmstudio"

"lmstudio-legacy"

"lmstudio-chatcompletions"

"llamacpp"

"koboldcpp"

"vllm"

"hugging-face"

"mistral"

"together"

"bedrock"

"deepseek"

"xai"

compatibility_type: Optional[Literal["gguf", "mlx"]]

The framework compatibility type for the model.

Accepts one of the following:

"gguf"

"mlx"

display_name: Optional[str]

A human-friendly display name for the model.

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]

If set to True, enables parallel tool calling. Defaults to False.

provider_category: Optional[ProviderCategory]

The provider category for the model.

Accepts one of the following:

"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["minimal", "low", "medium", "high"]]

The reasoning effort to use when generating text reasoning models

Accepts one of the following:

"minimal"

"low"

"medium"

"high"

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).

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

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

Accepts one of the following:

"low"

"medium"

"high"

Deprecatedmemory: 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.

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.

Accepts one of the following:

Literal["memgpt_agent", "memgpt_v2_agent", "letta_v1_agent", 6 more]

Accepts one of the following:

"memgpt_agent"

"memgpt_v2_agent"

"letta_v1_agent"

"react_agent"

"workflow_agent"

"split_thread_agent"

"sleeptime_agent"

"voice_convo_agent"

"voice_sleeptime_agent"

MemoryAgentTypeUnionMember1 = 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

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.

formatdate-time

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.

template_id: Optional[str]

The id of the template.

template_name: Optional[str]

Name of the block if it is a template.

prompt_template: Optional[str]

Deprecated. Ignored for performance.

The name of the agent.

sources: List[Source]

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.

Accepts one of the following:

"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.

The name of the source.

created_at: Optional[datetime]

The timestamp when the source was created.

formatdate-time

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.

formatdate-time

vector_db_provider: Optional[VectorDBProvider]

The vector database provider used for this source's passages

Accepts one of the following:

"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.

The name of the function.

npm_requirements: Optional[List[NpmRequirement]]

Optional list of npm packages required by this tool.

Name of the npm package.

minLength1

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 of the pip package.

minLength1

version: Optional[str]

Optional version of the package, following semantic versioning.

return_char_limit: Optional[int]

The maximum number of characters in the response.

maximum1000000

minimum1

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.

Accepts one of the following:

"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.

created_at: Optional[datetime]

The timestamp when the object was created.

formatdate-time

created_by_id: Optional[str]

The id of the user that made this object.

deployment_id: Optional[str]

The id of the deployment.

description: Optional[str]

The description of the agent.

embedding: Optional[Embedding]

Schema for defining settings for an embedding model

model: str

The name of the model.

provider: Literal["openai", "ollama"]

The provider of the model.

Accepts one of the following:

"openai"

"ollama"

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

Deprecatedagent_ids: List[str]

The IDs of the agents associated with the identity.

Deprecatedblock_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: IdentityType

The type of the identity.

Accepts one of the following:

"org"

"user"

"other"

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

Accepts one of the following:

"string"

"number"

"boolean"

"json"

value: Union[str, float, bool, Dict[str, object]]

The value of the property

Accepts one of the following:

ValueUnionMember0 = str

ValueUnionMember1 = float

ValueUnionMember2 = bool

ValueUnionMember3 = Dict[str, object]

Deprecatedidentity_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.

formatdate-time

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.

Accepts one of the following:

"end_turn"

"error"

"llm_api_error"

"invalid_llm_response"

"invalid_tool_call"

"max_steps"

"no_tool_call"

"tool_rule"

"cancelled"

"requires_approval"

last_updated_by_id: Optional[str]

The id of the user that made this object.

managed_group: Optional[Group]

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: ManagerType

Accepts one of the following:

"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.

Deprecatedshared_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[Model]

Schema for defining settings for a model

model: str

The name of the model.

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.

Deprecatedmulti_agent_group: Optional[Group]

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: ManagerType

Accepts one of the following:

"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.

Deprecatedshared_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]

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

Accepts one of the following:

class TextResponseFormat: …

Response format for plain text responses.

type: Optional[Literal["text"]]

The type of the response format.

Accepts one of the following:

"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.

Accepts one of the following:

"json_schema"

class JsonObjectResponseFormat: …

Response format for JSON object responses.

type: Optional[Literal["json_object"]]

The type of the response format.

Accepts one of the following:

"json_object"

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.

formatdate-time

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.

formatdate-time

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).

Deprecatedtool_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.

formatdate-time

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.

formatdate-time

value_enc: Optional[str]

Encrypted secret value (stored as encrypted string)

tool_rules: Optional[List[ToolRule]]

The list of tool rules.

Accepts one of the following:

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'.

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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"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"]]

Accepts one of the following:

"requires_approval"

updated_at: Optional[datetime]

The timestamp when the object was last updated.

formatdate-time

List Agents For Identity

from letta_client import Letta

client = Letta(
    api_key="My API Key",
)
page = client.identities.agents.list(
    identity_id="identity-123e4567-e89b-42d3-8456-426614174000",
)
page = page.items[0]
print(page.id)

[
  {
    "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,
        "template_id": "template_id",
        "template_name": "template_name"
      }
    ],
    "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"
    },
    "llm_config": {
      "context_window": 0,
      "model": "model",
      "model_endpoint_type": "openai",
      "compatibility_type": "gguf",
      "display_name": "display_name",
      "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": "minimal",
      "temperature": 0,
      "tier": "tier",
      "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,
          "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,
          "template_id": "template_id",
          "template_name": "template_name"
        }
      ],
      "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"
          }
        ],
        "return_char_limit": 1,
        "source_code": "source_code",
        "source_type": "source_type",
        "tags": [
          "string"
        ],
        "tool_type": "custom"
      }
    ],
    "base_template_id": "base_template_id",
    "created_at": "2019-12-27T18:11:19.117Z",
    "created_by_id": "created_by_id",
    "deployment_id": "deployment_id",
    "description": "description",
    "embedding": {
      "model": "model",
      "provider": "openai"
    },
    "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",
      "max_output_tokens": 0,
      "parallel_tool_calls": true
    },
    "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
    },
    "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"
  }
]

Returns Examples

[
  {
    "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,
        "template_id": "template_id",
        "template_name": "template_name"
      }
    ],
    "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"
    },
    "llm_config": {
      "context_window": 0,
      "model": "model",
      "model_endpoint_type": "openai",
      "compatibility_type": "gguf",
      "display_name": "display_name",
      "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": "minimal",
      "temperature": 0,
      "tier": "tier",
      "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,
          "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,
          "template_id": "template_id",
          "template_name": "template_name"
        }
      ],
      "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"
          }
        ],
        "return_char_limit": 1,
        "source_code": "source_code",
        "source_type": "source_type",
        "tags": [
          "string"
        ],
        "tool_type": "custom"
      }
    ],
    "base_template_id": "base_template_id",
    "created_at": "2019-12-27T18:11:19.117Z",
    "created_by_id": "created_by_id",
    "deployment_id": "deployment_id",
    "description": "description",
    "embedding": {
      "model": "model",
      "provider": "openai"
    },
    "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",
      "max_output_tokens": 0,
      "parallel_tool_calls": true
    },
    "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
    },
    "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"
  }
]