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API Reference
Blocks
Agents
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List Agents For Block

blocks.agents.list(strblock_id, AgentListParams**kwargs) -> SyncArrayPage[AgentState]
get/v1/blocks/{block_id}/agents

Retrieves all agents associated with the specified block. Raises a 404 if the block does not exist.

ParametersExpand Collapse
block_id: str

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

minLength42
maxLength42
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"
include_relationships: Optional[SequenceNotStr[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.

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.

name: str

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.

name: str

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.

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.

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: str

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"
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

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'.

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"]]
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 Block
  • HTTP
  • TypeScript
  • Python
from letta_client import Letta

client = Letta(
    api_key="My API Key",
)
page = client.blocks.agents.list(
    block_id="block-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"
  }
]