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MemGPT/letta/client/client.py
cthomas c0efe8ad0c
chore: bump version 0.7.21 (#2653) 
Co-authored-by: Andy Li <55300002+cliandy@users.noreply.github.com>
Co-authored-by: Kevin Lin <klin5061@gmail.com>
Co-authored-by: Sarah Wooders <sarahwooders@gmail.com>
Co-authored-by: jnjpng <jin@letta.com>
Co-authored-by: Matthew Zhou <mattzh1314@gmail.com>
2025-05-21 16:33:29 -07:00

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import asyncio
import logging
import sys
import time
from typing import Callable, Dict, Generator, List, Optional, Union
import requests
import letta.utils
from letta.constants import ADMIN_PREFIX, BASE_MEMORY_TOOLS, BASE_TOOLS, DEFAULT_HUMAN, DEFAULT_PERSONA, FUNCTION_RETURN_CHAR_LIMIT
from letta.data_sources.connectors import DataConnector
from letta.functions.functions import parse_source_code
from letta.orm.errors import NoResultFound
from letta.schemas.agent import AgentState, AgentType, CreateAgent, UpdateAgent
from letta.schemas.block import Block, BlockUpdate, CreateBlock, Human, Persona
from letta.schemas.embedding_config import EmbeddingConfig
# new schemas
from letta.schemas.enums import JobStatus, MessageRole
from letta.schemas.environment_variables import (
SandboxEnvironmentVariable,
SandboxEnvironmentVariableCreate,
SandboxEnvironmentVariableUpdate,
)
from letta.schemas.file import FileMetadata
from letta.schemas.job import Job
from letta.schemas.letta_message import LettaMessage, LettaMessageUnion
from letta.schemas.letta_request import LettaRequest, LettaStreamingRequest
from letta.schemas.letta_response import LettaResponse, LettaStreamingResponse
from letta.schemas.llm_config import LLMConfig
from letta.schemas.memory import ArchivalMemorySummary, ChatMemory, CreateArchivalMemory, Memory, RecallMemorySummary
from letta.schemas.message import Message, MessageCreate
from letta.schemas.openai.chat_completion_response import UsageStatistics
from letta.schemas.organization import Organization
from letta.schemas.passage import Passage
from letta.schemas.response_format import ResponseFormatUnion
from letta.schemas.run import Run
from letta.schemas.sandbox_config import E2BSandboxConfig, LocalSandboxConfig, SandboxConfig, SandboxConfigCreate, SandboxConfigUpdate
from letta.schemas.source import Source, SourceCreate, SourceUpdate
from letta.schemas.tool import Tool, ToolCreate, ToolUpdate
from letta.schemas.tool_rule import BaseToolRule
from letta.server.rest_api.interface import QueuingInterface
from letta.utils import get_human_text, get_persona_text
# Print deprecation notice in yellow when module is imported
print(
"\n\n\033[93m"
+ "DEPRECATION WARNING: This legacy Python client has been deprecated and will be removed in a future release.\n"
+ "Please migrate to the new official python SDK by running: pip install letta-client\n"
+ "For further documentation, visit: https://docs.letta.com/api-reference/overview#python-sdk"
+ "\033[0m\n\n",
file=sys.stderr,
)
def create_client(base_url: Optional[str] = None, token: Optional[str] = None):
if base_url is None:
return LocalClient()
else:
return RESTClient(base_url, token)
class AbstractClient(object):
def __init__(
self,
debug: bool = False,
):
self.debug = debug
def agent_exists(self, agent_id: Optional[str] = None, agent_name: Optional[str] = None) -> bool:
raise NotImplementedError
def create_agent(
self,
name: Optional[str] = None,
agent_type: Optional[AgentType] = AgentType.memgpt_agent,
embedding_config: Optional[EmbeddingConfig] = None,
llm_config: Optional[LLMConfig] = None,
memory=None,
block_ids: Optional[List[str]] = None,
system: Optional[str] = None,
tool_ids: Optional[List[str]] = None,
tool_rules: Optional[List[BaseToolRule]] = None,
include_base_tools: Optional[bool] = True,
metadata: Optional[Dict] = {"human:": DEFAULT_HUMAN, "persona": DEFAULT_PERSONA},
description: Optional[str] = None,
tags: Optional[List[str]] = None,
message_buffer_autoclear: bool = False,
response_format: Optional[ResponseFormatUnion] = None,
) -> AgentState:
raise NotImplementedError
def update_agent(
self,
agent_id: str,
name: Optional[str] = None,
description: Optional[str] = None,
system: Optional[str] = None,
tool_ids: Optional[List[str]] = None,
metadata: Optional[Dict] = None,
llm_config: Optional[LLMConfig] = None,
embedding_config: Optional[EmbeddingConfig] = None,
message_ids: Optional[List[str]] = None,
memory: Optional[Memory] = None,
tags: Optional[List[str]] = None,
response_format: Optional[ResponseFormatUnion] = None,
):
raise NotImplementedError
def get_tools_from_agent(self, agent_id: str) -> List[Tool]:
raise NotImplementedError
def attach_tool(self, agent_id: str, tool_id: str) -> AgentState:
raise NotImplementedError
def detach_tool(self, agent_id: str, tool_id: str) -> AgentState:
raise NotImplementedError
def rename_agent(self, agent_id: str, new_name: str) -> AgentState:
raise NotImplementedError
def delete_agent(self, agent_id: str) -> None:
raise NotImplementedError
def get_agent(self, agent_id: str) -> AgentState:
raise NotImplementedError
def get_agent_id(self, agent_name: str) -> AgentState:
raise NotImplementedError
def get_in_context_memory(self, agent_id: str) -> Memory:
raise NotImplementedError
def update_in_context_memory(self, agent_id: str, section: str, value: Union[List[str], str]) -> Memory:
raise NotImplementedError
def get_archival_memory_summary(self, agent_id: str) -> ArchivalMemorySummary:
raise NotImplementedError
def get_recall_memory_summary(self, agent_id: str) -> RecallMemorySummary:
raise NotImplementedError
def get_in_context_messages(self, agent_id: str) -> List[Message]:
raise NotImplementedError
def send_message(
self,
message: str,
role: str,
agent_id: Optional[str] = None,
name: Optional[str] = None,
stream: Optional[bool] = False,
stream_steps: bool = False,
stream_tokens: bool = False,
) -> LettaResponse:
raise NotImplementedError
def user_message(self, agent_id: str, message: str) -> LettaResponse:
raise NotImplementedError
def create_human(self, name: str, text: str) -> Human:
raise NotImplementedError
def create_persona(self, name: str, text: str) -> Persona:
raise NotImplementedError
def list_humans(self) -> List[Human]:
raise NotImplementedError
def list_personas(self) -> List[Persona]:
raise NotImplementedError
def update_human(self, human_id: str, text: str) -> Human:
raise NotImplementedError
def update_persona(self, persona_id: str, text: str) -> Persona:
raise NotImplementedError
def get_persona(self, id: str) -> Persona:
raise NotImplementedError
def get_human(self, id: str) -> Human:
raise NotImplementedError
def get_persona_id(self, name: str) -> str:
raise NotImplementedError
def get_human_id(self, name: str) -> str:
raise NotImplementedError
def delete_persona(self, id: str):
raise NotImplementedError
def delete_human(self, id: str):
raise NotImplementedError
def load_langchain_tool(self, langchain_tool: "LangChainBaseTool", additional_imports_module_attr_map: dict[str, str] = None) -> Tool:
raise NotImplementedError
def load_composio_tool(self, action: "ActionType") -> Tool:
raise NotImplementedError
def create_tool(self, func, tags: Optional[List[str]] = None, return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT) -> Tool:
raise NotImplementedError
def create_or_update_tool(self, func, tags: Optional[List[str]] = None, return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT) -> Tool:
raise NotImplementedError
def update_tool(
self,
id: str,
description: Optional[str] = None,
func: Optional[Callable] = None,
tags: Optional[List[str]] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
raise NotImplementedError
def list_tools(self, after: Optional[str] = None, limit: Optional[int] = 50) -> List[Tool]:
raise NotImplementedError
def get_tool(self, id: str) -> Tool:
raise NotImplementedError
def delete_tool(self, id: str):
raise NotImplementedError
def get_tool_id(self, name: str) -> Optional[str]:
raise NotImplementedError
def list_attached_tools(self, agent_id: str) -> List[Tool]:
"""
List all tools attached to an agent.
Args:
agent_id (str): ID of the agent
Returns:
List[Tool]: A list of attached tools
"""
raise NotImplementedError
def upsert_base_tools(self) -> List[Tool]:
raise NotImplementedError
def load_data(self, connector: DataConnector, source_name: str):
raise NotImplementedError
def load_file_to_source(self, filename: str, source_id: str, blocking=True) -> Job:
raise NotImplementedError
def delete_file_from_source(self, source_id: str, file_id: str) -> None:
raise NotImplementedError
def create_source(self, name: str, embedding_config: Optional[EmbeddingConfig] = None) -> Source:
raise NotImplementedError
def delete_source(self, source_id: str):
raise NotImplementedError
def get_source(self, source_id: str) -> Source:
raise NotImplementedError
def get_source_id(self, source_name: str) -> str:
raise NotImplementedError
def attach_source(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None) -> AgentState:
raise NotImplementedError
def detach_source(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None) -> AgentState:
raise NotImplementedError
def list_sources(self) -> List[Source]:
raise NotImplementedError
def list_attached_sources(self, agent_id: str) -> List[Source]:
raise NotImplementedError
def list_files_from_source(self, source_id: str, limit: int = 1000, after: Optional[str] = None) -> List[FileMetadata]:
raise NotImplementedError
def update_source(self, source_id: str, name: Optional[str] = None) -> Source:
raise NotImplementedError
def insert_archival_memory(self, agent_id: str, memory: str) -> List[Passage]:
raise NotImplementedError
def delete_archival_memory(self, agent_id: str, memory_id: str):
raise NotImplementedError
def get_archival_memory(
self, agent_id: str, after: Optional[str] = None, before: Optional[str] = None, limit: Optional[int] = 1000
) -> List[Passage]:
raise NotImplementedError
def get_messages(
self, agent_id: str, after: Optional[str] = None, before: Optional[str] = None, limit: Optional[int] = 1000
) -> List[LettaMessage]:
raise NotImplementedError
def list_model_configs(self) -> List[LLMConfig]:
raise NotImplementedError
def list_embedding_configs(self) -> List[EmbeddingConfig]:
raise NotImplementedError
def create_org(self, name: Optional[str] = None) -> Organization:
raise NotImplementedError
def list_orgs(self, after: Optional[str] = None, limit: Optional[int] = 50) -> List[Organization]:
raise NotImplementedError
def delete_org(self, org_id: str) -> Organization:
raise NotImplementedError
def create_sandbox_config(self, config: Union[LocalSandboxConfig, E2BSandboxConfig]) -> SandboxConfig:
"""
Create a new sandbox configuration.
Args:
config (Union[LocalSandboxConfig, E2BSandboxConfig]): The sandbox settings.
Returns:
SandboxConfig: The created sandbox configuration.
"""
raise NotImplementedError
def update_sandbox_config(self, sandbox_config_id: str, config: Union[LocalSandboxConfig, E2BSandboxConfig]) -> SandboxConfig:
"""
Update an existing sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to update.
config (Union[LocalSandboxConfig, E2BSandboxConfig]): The updated sandbox settings.
Returns:
SandboxConfig: The updated sandbox configuration.
"""
raise NotImplementedError
def delete_sandbox_config(self, sandbox_config_id: str) -> None:
"""
Delete a sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to delete.
"""
raise NotImplementedError
def list_sandbox_configs(self, limit: int = 50, after: Optional[str] = None) -> List[SandboxConfig]:
"""
List all sandbox configurations.
Args:
limit (int, optional): The maximum number of sandbox configurations to return. Defaults to 50.
after (Optional[str], optional): The pagination cursor for retrieving the next set of results.
Returns:
List[SandboxConfig]: A list of sandbox configurations.
"""
raise NotImplementedError
def create_sandbox_env_var(
self, sandbox_config_id: str, key: str, value: str, description: Optional[str] = None
) -> SandboxEnvironmentVariable:
"""
Create a new environment variable for a sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to associate the environment variable with.
key (str): The name of the environment variable.
value (str): The value of the environment variable.
description (Optional[str], optional): A description of the environment variable. Defaults to None.
Returns:
SandboxEnvironmentVariable: The created environment variable.
"""
raise NotImplementedError
def update_sandbox_env_var(
self, env_var_id: str, key: Optional[str] = None, value: Optional[str] = None, description: Optional[str] = None
) -> SandboxEnvironmentVariable:
"""
Update an existing environment variable.
Args:
env_var_id (str): The ID of the environment variable to update.
key (Optional[str], optional): The updated name of the environment variable. Defaults to None.
value (Optional[str], optional): The updated value of the environment variable. Defaults to None.
description (Optional[str], optional): The updated description of the environment variable. Defaults to None.
Returns:
SandboxEnvironmentVariable: The updated environment variable.
"""
raise NotImplementedError
def delete_sandbox_env_var(self, env_var_id: str) -> None:
"""
Delete an environment variable by its ID.
Args:
env_var_id (str): The ID of the environment variable to delete.
"""
raise NotImplementedError
def list_sandbox_env_vars(
self, sandbox_config_id: str, limit: int = 50, after: Optional[str] = None
) -> List[SandboxEnvironmentVariable]:
"""
List all environment variables associated with a sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to retrieve environment variables for.
limit (int, optional): The maximum number of environment variables to return. Defaults to 50.
after (Optional[str], optional): The pagination cursor for retrieving the next set of results.
Returns:
List[SandboxEnvironmentVariable]: A list of environment variables.
"""
raise NotImplementedError
def attach_block(self, agent_id: str, block_id: str) -> AgentState:
"""
Attach a block to an agent.
Args:
agent_id (str): ID of the agent
block_id (str): ID of the block to attach
"""
raise NotImplementedError
def detach_block(self, agent_id: str, block_id: str) -> AgentState:
"""
Detach a block from an agent.
Args:
agent_id (str): ID of the agent
block_id (str): ID of the block to detach
"""
raise NotImplementedError
class RESTClient(AbstractClient):
"""
REST client for Letta
Attributes:
base_url (str): Base URL of the REST API
headers (Dict): Headers for the REST API (includes token)
"""
def __init__(
self,
base_url: str,
token: Optional[str] = None,
password: Optional[str] = None,
api_prefix: str = "v1",
debug: bool = False,
default_llm_config: Optional[LLMConfig] = None,
default_embedding_config: Optional[EmbeddingConfig] = None,
headers: Optional[Dict] = None,
):
"""
Initializes a new instance of Client class.
Args:
user_id (str): The user ID.
debug (bool): Whether to print debug information.
default_llm_config (Optional[LLMConfig]): The default LLM configuration.
default_embedding_config (Optional[EmbeddingConfig]): The default embedding configuration.
headers (Optional[Dict]): The additional headers for the REST API.
token (Optional[str]): The token for the REST API when using managed letta service.
password (Optional[str]): The password for the REST API when using self hosted letta service.
"""
super().__init__(debug=debug)
self.base_url = base_url
self.api_prefix = api_prefix
if token:
self.headers = {"accept": "application/json", "Authorization": f"Bearer {token}"}
elif password:
self.headers = {"accept": "application/json", "Authorization": f"Bearer {password}"}
else:
self.headers = {"accept": "application/json"}
if headers:
self.headers.update(headers)
self._default_llm_config = default_llm_config
self._default_embedding_config = default_embedding_config
def list_agents(
self,
tags: Optional[List[str]] = None,
query_text: Optional[str] = None,
limit: int = 50,
before: Optional[str] = None,
after: Optional[str] = None,
) -> List[AgentState]:
params = {"limit": limit}
if tags:
params["tags"] = tags
params["match_all_tags"] = False
if query_text:
params["query_text"] = query_text
if before:
params["before"] = before
if after:
params["after"] = after
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents", headers=self.headers, params=params)
return [AgentState(**agent) for agent in response.json()]
def agent_exists(self, agent_id: str) -> bool:
"""
Check if an agent exists
Args:
agent_id (str): ID of the agent
agent_name (str): Name of the agent
Returns:
exists (bool): `True` if the agent exists, `False` otherwise
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}", headers=self.headers)
if response.status_code == 404:
# not found error
return False
elif response.status_code == 200:
return True
else:
raise ValueError(f"Failed to check if agent exists: {response.text}")
def create_agent(
self,
name: Optional[str] = None,
# agent config
agent_type: Optional[AgentType] = AgentType.memgpt_agent,
# model configs
embedding_config: EmbeddingConfig = None,
llm_config: LLMConfig = None,
# memory
memory: Memory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_persona_text(DEFAULT_PERSONA)),
# Existing blocks
block_ids: Optional[List[str]] = None,
# system
system: Optional[str] = None,
# tools
tool_ids: Optional[List[str]] = None,
tool_rules: Optional[List[BaseToolRule]] = None,
include_base_tools: Optional[bool] = True,
include_multi_agent_tools: Optional[bool] = False,
# metadata
metadata: Optional[Dict] = {"human:": DEFAULT_HUMAN, "persona": DEFAULT_PERSONA},
description: Optional[str] = None,
initial_message_sequence: Optional[List[Message]] = None,
tags: Optional[List[str]] = None,
message_buffer_autoclear: bool = False,
response_format: Optional[ResponseFormatUnion] = None,
) -> AgentState:
"""Create an agent
Args:
name (str): Name of the agent
embedding_config (EmbeddingConfig): Embedding configuration
llm_config (LLMConfig): LLM configuration
memory (Memory): Memory configuration
system (str): System configuration
tool_ids (List[str]): List of tool ids
include_base_tools (bool): Include base tools
metadata (Dict): Metadata
description (str): Description
tags (List[str]): Tags for filtering agents
Returns:
agent_state (AgentState): State of the created agent
"""
tool_ids = tool_ids or []
tool_names = []
if include_base_tools:
tool_names += BASE_TOOLS
tool_names += BASE_MEMORY_TOOLS
tool_ids += [self.get_tool_id(tool_name=name) for name in tool_names]
assert embedding_config or self._default_embedding_config, f"Embedding config must be provided"
assert llm_config or self._default_llm_config, f"LLM config must be provided"
# TODO: This should not happen here, we need to have clear separation between create/add blocks
# TODO: This is insanely hacky and a result of allowing free-floating blocks
# TODO: When we create the block, it gets it's own block ID
blocks = []
for block in memory.get_blocks():
blocks.append(
self.create_block(
label=block.label,
value=block.value,
limit=block.limit,
template_name=block.template_name,
is_template=block.is_template,
)
)
memory.blocks = blocks
block_ids = block_ids or []
# create agent
create_params = {
"description": description,
"metadata": metadata,
"memory_blocks": [],
"block_ids": [b.id for b in memory.get_blocks()] + block_ids,
"tool_ids": tool_ids,
"tool_rules": tool_rules,
"system": system,
"agent_type": agent_type,
"llm_config": llm_config if llm_config else self._default_llm_config,
"embedding_config": embedding_config if embedding_config else self._default_embedding_config,
"initial_message_sequence": initial_message_sequence,
"tags": tags,
"include_base_tools": include_base_tools,
"message_buffer_autoclear": message_buffer_autoclear,
"include_multi_agent_tools": include_multi_agent_tools,
"response_format": response_format,
}
# Only add name if it's not None
if name is not None:
create_params["name"] = name
request = CreateAgent(**create_params)
# Use model_dump_json() instead of model_dump()
# If we use model_dump(), the datetime objects will not be serialized correctly
# response = requests.post(f"{self.base_url}/{self.api_prefix}/agents", json=request.model_dump(), headers=self.headers)
response = requests.post(
f"{self.base_url}/{self.api_prefix}/agents",
data=request.model_dump_json(), # Use model_dump_json() instead of json=model_dump()
headers={"Content-Type": "application/json", **self.headers},
)
if response.status_code != 200:
raise ValueError(f"Status {response.status_code} - Failed to create agent: {response.text}")
# gather agent state
agent_state = AgentState(**response.json())
# refresh and return agent
return self.get_agent(agent_state.id)
def update_agent(
self,
agent_id: str,
name: Optional[str] = None,
description: Optional[str] = None,
system: Optional[str] = None,
tool_ids: Optional[List[str]] = None,
metadata: Optional[Dict] = None,
llm_config: Optional[LLMConfig] = None,
embedding_config: Optional[EmbeddingConfig] = None,
message_ids: Optional[List[str]] = None,
tags: Optional[List[str]] = None,
response_format: Optional[ResponseFormatUnion] = None,
) -> AgentState:
"""
Update an existing agent
Args:
agent_id (str): ID of the agent
name (str): Name of the agent
description (str): Description of the agent
system (str): System configuration
tool_ids (List[str]): List of tools
metadata (Dict): Metadata
llm_config (LLMConfig): LLM configuration
embedding_config (EmbeddingConfig): Embedding configuration
message_ids (List[str]): List of message IDs
tags (List[str]): Tags for filtering agents
Returns:
agent_state (AgentState): State of the updated agent
"""
request = UpdateAgent(
name=name,
system=system,
tool_ids=tool_ids,
tags=tags,
description=description,
metadata=metadata,
llm_config=llm_config,
embedding_config=embedding_config,
message_ids=message_ids,
response_format=response_format,
)
response = requests.patch(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update agent: {response.text}")
return AgentState(**response.json())
def get_tools_from_agent(self, agent_id: str) -> List[Tool]:
"""
Get tools to an existing agent
Args:
agent_id (str): ID of the agent
Returns:
List[Tool]: A List of Tool objs
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/tools", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get tools from agents: {response.text}")
return [Tool(**tool) for tool in response.json()]
def attach_tool(self, agent_id: str, tool_id: str) -> AgentState:
"""
Add tool to an existing agent
Args:
agent_id (str): ID of the agent
tool_id (str): A tool id
Returns:
agent_state (AgentState): State of the updated agent
"""
response = requests.patch(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/tools/attach/{tool_id}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update agent: {response.text}")
return AgentState(**response.json())
def detach_tool(self, agent_id: str, tool_id: str) -> AgentState:
"""
Removes tools from an existing agent
Args:
agent_id (str): ID of the agent
tool_id (str): The tool id
Returns:
agent_state (AgentState): State of the updated agent
"""
response = requests.patch(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/tools/detach/{tool_id}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update agent: {response.text}")
return AgentState(**response.json())
def rename_agent(self, agent_id: str, new_name: str) -> AgentState:
"""
Rename an agent
Args:
agent_id (str): ID of the agent
new_name (str): New name for the agent
Returns:
agent_state (AgentState): State of the updated agent
"""
return self.update_agent(agent_id, name=new_name)
def delete_agent(self, agent_id: str) -> None:
"""
Delete an agent
Args:
agent_id (str): ID of the agent to delete
"""
response = requests.delete(f"{self.base_url}/{self.api_prefix}/agents/{str(agent_id)}", headers=self.headers)
assert response.status_code == 200, f"Failed to delete agent: {response.text}"
def get_agent(self, agent_id: Optional[str] = None, agent_name: Optional[str] = None) -> AgentState:
"""
Get an agent's state by it's ID.
Args:
agent_id (str): ID of the agent
Returns:
agent_state (AgentState): State representation of the agent
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}", headers=self.headers)
assert response.status_code == 200, f"Failed to get agent: {response.text}"
return AgentState(**response.json())
def get_agent_id(self, agent_name: str) -> AgentState:
"""
Get the ID of an agent by name (names are unique per user)
Args:
agent_name (str): Name of the agent
Returns:
agent_id (str): ID of the agent
"""
# TODO: implement this
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents", headers=self.headers, params={"name": agent_name})
agents = [AgentState(**agent) for agent in response.json()]
if len(agents) == 0:
return None
agents = [agents[0]] # TODO: @matt monkeypatched
assert len(agents) == 1, f"Multiple agents with the same name: {[(agents.name, agents.id) for agents in agents]}"
return agents[0].id
# memory
def get_in_context_memory(self, agent_id: str) -> Memory:
"""
Get the in-contxt (i.e. core) memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
memory (Memory): In-context memory of the agent
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get in-context memory: {response.text}")
return Memory(**response.json())
def get_core_memory(self, agent_id: str) -> Memory:
return self.get_in_context_memory(agent_id)
def update_in_context_memory(self, agent_id: str, section: str, value: Union[List[str], str]) -> Memory:
"""
Update the in-context memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
memory (Memory): The updated in-context memory of the agent
"""
memory_update_dict = {section: value}
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory", json=memory_update_dict, headers=self.headers
)
if response.status_code != 200:
raise ValueError(f"Failed to update in-context memory: {response.text}")
return Memory(**response.json())
def get_archival_memory_summary(self, agent_id: str) -> ArchivalMemorySummary:
"""
Get a summary of the archival memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
summary (ArchivalMemorySummary): Summary of the archival memory
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/context", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get archival memory summary: {response.text}")
return ArchivalMemorySummary(size=response.json().get("num_archival_memory", 0))
def get_recall_memory_summary(self, agent_id: str) -> RecallMemorySummary:
"""
Get a summary of the recall memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
summary (RecallMemorySummary): Summary of the recall memory
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/context", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get recall memory summary: {response.text}")
return RecallMemorySummary(size=response.json().get("num_recall_memory", 0))
def get_in_context_messages(self, agent_id: str) -> List[Message]:
"""
Get in-context messages of an agent
Args:
agent_id (str): ID of the agent
Returns:
messages (List[Message]): List of in-context messages
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/context", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get recall memory summary: {response.text}")
return [Message(**message) for message in response.json().get("messages", "")]
# agent interactions
def user_message(self, agent_id: str, message: str) -> LettaResponse:
"""
Send a message to an agent as a user
Args:
agent_id (str): ID of the agent
message (str): Message to send
Returns:
response (LettaResponse): Response from the agent
"""
return self.send_message(agent_id=agent_id, message=message, role="user")
def save(self):
raise NotImplementedError
# archival memory
def get_archival_memory(
self, agent_id: str, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000
) -> List[Passage]:
"""
Get archival memory from an agent with pagination.
Args:
agent_id (str): ID of the agent
before (str): Get memories before a certain time
after (str): Get memories after a certain time
limit (int): Limit number of memories
Returns:
passages (List[Passage]): List of passages
"""
params = {"limit": limit}
if before:
params["before"] = str(before)
if after:
params["after"] = str(after)
response = requests.get(
f"{self.base_url}/{self.api_prefix}/agents/{str(agent_id)}/archival-memory", params=params, headers=self.headers
)
assert response.status_code == 200, f"Failed to get archival memory: {response.text}"
return [Passage(**passage) for passage in response.json()]
def insert_archival_memory(self, agent_id: str, memory: str) -> List[Passage]:
"""
Insert archival memory into an agent
Args:
agent_id (str): ID of the agent
memory (str): Memory string to insert
Returns:
passages (List[Passage]): List of inserted passages
"""
request = CreateArchivalMemory(text=memory)
response = requests.post(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/archival-memory", headers=self.headers, json=request.model_dump()
)
if response.status_code != 200:
raise ValueError(f"Failed to insert archival memory: {response.text}")
return [Passage(**passage) for passage in response.json()]
def delete_archival_memory(self, agent_id: str, memory_id: str):
"""
Delete archival memory from an agent
Args:
agent_id (str): ID of the agent
memory_id (str): ID of the memory
"""
response = requests.delete(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/archival-memory/{memory_id}", headers=self.headers)
assert response.status_code == 200, f"Failed to delete archival memory: {response.text}"
# messages (recall memory)
def get_messages(
self, agent_id: str, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000
) -> List[LettaMessage]:
"""
Get messages from an agent with pagination.
Args:
agent_id (str): ID of the agent
before (str): Get messages before a certain time
after (str): Get messages after a certain time
limit (int): Limit number of messages
Returns:
messages (List[Message]): List of messages
"""
params = {"before": before, "after": after, "limit": limit, "msg_object": True}
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages", params=params, headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get messages: {response.text}")
return [LettaMessage(**message) for message in response.json()]
def send_message(
self,
message: str,
role: str,
agent_id: Optional[str] = None,
name: Optional[str] = None,
stream: Optional[bool] = False,
stream_steps: bool = False,
stream_tokens: bool = False,
) -> Union[LettaResponse, Generator[LettaStreamingResponse, None, None]]:
"""
Send a message to an agent
Args:
message (str): Message to send
role (str): Role of the message
agent_id (str): ID of the agent
name(str): Name of the sender
stream (bool): Stream the response (default: `False`)
stream_tokens (bool): Stream tokens (default: `False`)
Returns:
response (LettaResponse): Response from the agent
"""
# TODO: implement include_full_message
messages = [MessageCreate(role=MessageRole(role), content=message, name=name)]
# TODO: figure out how to handle stream_steps and stream_tokens
# When streaming steps is True, stream_tokens must be False
if stream_tokens or stream_steps:
from letta.client.streaming import _sse_post
request = LettaStreamingRequest(messages=messages, stream_tokens=stream_tokens)
return _sse_post(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages/stream", request.model_dump(), self.headers)
else:
request = LettaRequest(messages=messages)
response = requests.post(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages", json=request.model_dump(), headers=self.headers
)
if response.status_code != 200:
raise ValueError(f"Failed to send message: {response.text}")
response = LettaResponse(**response.json())
# simplify messages
# if not include_full_message:
# messages = []
# for m in response.messages:
# assert isinstance(m, Message)
# messages += m.to_letta_messages()
# response.messages = messages
return response
def send_message_async(
self,
message: str,
role: str,
agent_id: Optional[str] = None,
name: Optional[str] = None,
) -> Run:
"""
Send a message to an agent (async, returns a job)
Args:
message (str): Message to send
role (str): Role of the message
agent_id (str): ID of the agent
name(str): Name of the sender
Returns:
job (Job): Information about the async job
"""
messages = [MessageCreate(role=MessageRole(role), content=message, name=name)]
request = LettaRequest(messages=messages)
response = requests.post(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages/async",
json=request.model_dump(),
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to send message: {response.text}")
response = Run(**response.json())
return response
# humans / personas
def list_blocks(self, label: Optional[str] = None, templates_only: Optional[bool] = True) -> List[Block]:
params = {"label": label, "templates_only": templates_only}
response = requests.get(f"{self.base_url}/{self.api_prefix}/blocks", params=params, headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list blocks: {response.text}")
if label == "human":
return [Human(**human) for human in response.json()]
elif label == "persona":
return [Persona(**persona) for persona in response.json()]
else:
return [Block(**block) for block in response.json()]
def create_block(
self, label: str, value: str, limit: Optional[int] = None, template_name: Optional[str] = None, is_template: bool = False
) -> Block: #
request_kwargs = dict(label=label, value=value, template=is_template, template_name=template_name)
if limit:
request_kwargs["limit"] = limit
request = CreateBlock(**request_kwargs)
response = requests.post(f"{self.base_url}/{self.api_prefix}/blocks", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to create block: {response.text}")
if request.label == "human":
return Human(**response.json())
elif request.label == "persona":
return Persona(**response.json())
else:
return Block(**response.json())
def update_block(self, block_id: str, name: Optional[str] = None, text: Optional[str] = None, limit: Optional[int] = None) -> Block:
request = BlockUpdate(id=block_id, template_name=name, value=text, limit=limit if limit else self.get_block(block_id).limit)
response = requests.post(f"{self.base_url}/{self.api_prefix}/blocks/{block_id}", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update block: {response.text}")
return Block(**response.json())
def get_block(self, block_id: str) -> Optional[Block]:
response = requests.get(f"{self.base_url}/{self.api_prefix}/blocks/{block_id}", headers=self.headers)
if response.status_code == 404:
return None
elif response.status_code != 200:
raise ValueError(f"Failed to get block: {response.text}")
return Block(**response.json())
def get_block_id(self, name: str, label: str) -> str:
params = {"name": name, "label": label}
response = requests.get(f"{self.base_url}/{self.api_prefix}/blocks", params=params, headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get block ID: {response.text}")
blocks = [Block(**block) for block in response.json()]
if len(blocks) == 0:
return None
elif len(blocks) > 1:
raise ValueError(f"Multiple blocks found with name {name}")
return blocks[0].id
def delete_block(self, id: str) -> Block:
response = requests.delete(f"{self.base_url}/{self.api_prefix}/blocks/{id}", headers=self.headers)
assert response.status_code == 200, f"Failed to delete block: {response.text}"
if response.status_code != 200:
raise ValueError(f"Failed to delete block: {response.text}")
return Block(**response.json())
def list_humans(self):
"""
List available human block templates
Returns:
humans (List[Human]): List of human blocks
"""
blocks = self.list_blocks(label="human")
return [Human(**block.model_dump()) for block in blocks]
def create_human(self, name: str, text: str) -> Human:
"""
Create a human block template (saved human string to pre-fill `ChatMemory`)
Args:
name (str): Name of the human block template
text (str): Text of the human block template
Returns:
human (Human): Human block
"""
return self.create_block(label="human", template_name=name, value=text, is_template=True)
def update_human(self, human_id: str, name: Optional[str] = None, text: Optional[str] = None) -> Human:
"""
Update a human block template
Args:
human_id (str): ID of the human block
text (str): Text of the human block
Returns:
human (Human): Updated human block
"""
request = UpdateHuman(id=human_id, template_name=name, value=text)
response = requests.post(f"{self.base_url}/{self.api_prefix}/blocks/{human_id}", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update human: {response.text}")
return Human(**response.json())
def list_personas(self):
"""
List available persona block templates
Returns:
personas (List[Persona]): List of persona blocks
"""
blocks = self.list_blocks(label="persona")
return [Persona(**block.model_dump()) for block in blocks]
def create_persona(self, name: str, text: str) -> Persona:
"""
Create a persona block template (saved persona string to pre-fill `ChatMemory`)
Args:
name (str): Name of the persona block
text (str): Text of the persona block
Returns:
persona (Persona): Persona block
"""
return self.create_block(label="persona", template_name=name, value=text, is_template=True)
def update_persona(self, persona_id: str, name: Optional[str] = None, text: Optional[str] = None) -> Persona:
"""
Update a persona block template
Args:
persona_id (str): ID of the persona block
text (str): Text of the persona block
Returns:
persona (Persona): Updated persona block
"""
request = UpdatePersona(id=persona_id, template_name=name, value=text)
response = requests.post(f"{self.base_url}/{self.api_prefix}/blocks/{persona_id}", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update persona: {response.text}")
return Persona(**response.json())
def get_persona(self, persona_id: str) -> Persona:
"""
Get a persona block template
Args:
id (str): ID of the persona block
Returns:
persona (Persona): Persona block
"""
return self.get_block(persona_id)
def get_persona_id(self, name: str) -> str:
"""
Get the ID of a persona block template
Args:
name (str): Name of the persona block
Returns:
id (str): ID of the persona block
"""
return self.get_block_id(name, "persona")
def delete_persona(self, persona_id: str) -> Persona:
"""
Delete a persona block template
Args:
id (str): ID of the persona block
"""
return self.delete_block(persona_id)
def get_human(self, human_id: str) -> Human:
"""
Get a human block template
Args:
id (str): ID of the human block
Returns:
human (Human): Human block
"""
return self.get_block(human_id)
def get_human_id(self, name: str) -> str:
"""
Get the ID of a human block template
Args:
name (str): Name of the human block
Returns:
id (str): ID of the human block
"""
return self.get_block_id(name, "human")
def delete_human(self, human_id: str) -> Human:
"""
Delete a human block template
Args:
id (str): ID of the human block
"""
return self.delete_block(human_id)
# sources
def get_source(self, source_id: str) -> Source:
"""
Get a source given the ID.
Args:
source_id (str): ID of the source
Returns:
source (Source): Source
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/sources/{source_id}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get source: {response.text}")
return Source(**response.json())
def get_source_id(self, source_name: str) -> str:
"""
Get the ID of a source
Args:
source_name (str): Name of the source
Returns:
source_id (str): ID of the source
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/sources/name/{source_name}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get source ID: {response.text}")
return response.json()
def list_sources(self) -> List[Source]:
"""
List available sources
Returns:
sources (List[Source]): List of sources
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/sources", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list sources: {response.text}")
return [Source(**source) for source in response.json()]
def delete_source(self, source_id: str):
"""
Delete a source
Args:
source_id (str): ID of the source
"""
response = requests.delete(f"{self.base_url}/{self.api_prefix}/sources/{str(source_id)}", headers=self.headers)
assert response.status_code == 200, f"Failed to delete source: {response.text}"
def get_job(self, job_id: str) -> Job:
response = requests.get(f"{self.base_url}/{self.api_prefix}/jobs/{job_id}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get job: {response.text}")
return Job(**response.json())
def delete_job(self, job_id: str) -> Job:
response = requests.delete(f"{self.base_url}/{self.api_prefix}/jobs/{job_id}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to delete job: {response.text}")
return Job(**response.json())
def list_jobs(self):
response = requests.get(f"{self.base_url}/{self.api_prefix}/jobs", headers=self.headers)
return [Job(**job) for job in response.json()]
def list_active_jobs(self):
response = requests.get(f"{self.base_url}/{self.api_prefix}/jobs/active", headers=self.headers)
return [Job(**job) for job in response.json()]
def load_data(self, connector: DataConnector, source_name: str):
raise NotImplementedError
def load_file_to_source(self, filename: str, source_id: str, blocking=True) -> Job:
"""
Load a file into a source
Args:
filename (str): Name of the file
source_id (str): ID of the source
blocking (bool): Block until the job is complete
Returns:
job (Job): Data loading job including job status and metadata
"""
files = {"file": open(filename, "rb")}
# create job
response = requests.post(f"{self.base_url}/{self.api_prefix}/sources/{source_id}/upload", files=files, headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to upload file to source: {response.text}")
job = Job(**response.json())
if blocking:
# wait until job is completed
while True:
job = self.get_job(job.id)
if job.status == JobStatus.completed:
break
elif job.status == JobStatus.failed:
raise ValueError(f"Job failed: {job.metadata}")
time.sleep(1)
return job
def delete_file_from_source(self, source_id: str, file_id: str) -> None:
response = requests.delete(f"{self.base_url}/{self.api_prefix}/sources/{source_id}/{file_id}", headers=self.headers)
if response.status_code not in [200, 204]:
raise ValueError(f"Failed to delete tool: {response.text}")
def create_source(self, name: str, embedding_config: Optional[EmbeddingConfig] = None) -> Source:
"""
Create a source
Args:
name (str): Name of the source
Returns:
source (Source): Created source
"""
assert embedding_config or self._default_embedding_config, f"Must specify embedding_config for source"
source_create = SourceCreate(name=name, embedding_config=embedding_config or self._default_embedding_config)
payload = source_create.model_dump()
response = requests.post(f"{self.base_url}/{self.api_prefix}/sources", json=payload, headers=self.headers)
response_json = response.json()
return Source(**response_json)
def list_attached_sources(self, agent_id: str) -> List[Source]:
"""
List sources attached to an agent
Args:
agent_id (str): ID of the agent
Returns:
sources (List[Source]): List of sources
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/sources", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list attached sources: {response.text}")
return [Source(**source) for source in response.json()]
def list_files_from_source(self, source_id: str, limit: int = 1000, after: Optional[str] = None) -> List[FileMetadata]:
"""
List files from source with pagination support.
Args:
source_id (str): ID of the source
limit (int): Number of files to return
after (str): Get files after a certain time
Returns:
List[FileMetadata]: List of files
"""
# Prepare query parameters for pagination
params = {"limit": limit, "after": after}
# Make the request to the FastAPI endpoint
response = requests.get(f"{self.base_url}/{self.api_prefix}/sources/{source_id}/files", headers=self.headers, params=params)
if response.status_code != 200:
raise ValueError(f"Failed to list files with source id {source_id}: [{response.status_code}] {response.text}")
# Parse the JSON response
return [FileMetadata(**metadata) for metadata in response.json()]
def update_source(self, source_id: str, name: Optional[str] = None) -> Source:
"""
Update a source
Args:
source_id (str): ID of the source
name (str): Name of the source
Returns:
source (Source): Updated source
"""
request = SourceUpdate(name=name)
response = requests.patch(f"{self.base_url}/{self.api_prefix}/sources/{source_id}", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update source: {response.text}")
return Source(**response.json())
def attach_source(self, source_id: str, agent_id: str) -> AgentState:
"""
Attach a source to an agent
Args:
agent_id (str): ID of the agent
source_id (str): ID of the source
source_name (str): Name of the source
"""
params = {"agent_id": agent_id}
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/sources/attach/{source_id}", params=params, headers=self.headers
)
assert response.status_code == 200, f"Failed to attach source to agent: {response.text}"
return AgentState(**response.json())
def detach_source(self, source_id: str, agent_id: str) -> AgentState:
"""Detach a source from an agent"""
params = {"agent_id": str(agent_id)}
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/sources/detach/{source_id}", params=params, headers=self.headers
)
assert response.status_code == 200, f"Failed to detach source from agent: {response.text}"
return AgentState(**response.json())
# tools
def get_tool_id(self, tool_name: str):
"""
Get the ID of a tool
Args:
name (str): Name of the tool
Returns:
id (str): ID of the tool (`None` if not found)
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/tools", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get tool: {response.text}")
tools = [tool for tool in [Tool(**tool) for tool in response.json()] if tool.name == tool_name]
if not tools:
return None
return tools[0].id
def list_attached_tools(self, agent_id: str) -> List[Tool]:
"""
List all tools attached to an agent.
Args:
agent_id (str): ID of the agent
Returns:
List[Tool]: A list of attached tools
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/tools", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list attached tools: {response.text}")
return [Tool(**tool) for tool in response.json()]
def upsert_base_tools(self) -> List[Tool]:
response = requests.post(f"{self.base_url}/{self.api_prefix}/tools/add-base-tools/", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to add base tools: {response.text}")
return [Tool(**tool) for tool in response.json()]
def create_tool(
self,
func: Callable,
tags: Optional[List[str]] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
"""
Create a tool. This stores the source code of function on the server, so that the server can execute the function and generate an OpenAI JSON schemas for it when using with an agent.
Args:
func (callable): The function to create a tool for.
name: (str): Name of the tool (must be unique per-user.)
tags (Optional[List[str]], optional): Tags for the tool. Defaults to None.
return_char_limit (int): The character limit for the tool's return value. Defaults to FUNCTION_RETURN_CHAR_LIMIT.
Returns:
tool (Tool): The created tool.
"""
source_code = parse_source_code(func)
source_type = "python"
# call server function
request = ToolCreate(source_type=source_type, source_code=source_code, return_char_limit=return_char_limit)
if tags:
request.tags = tags
response = requests.post(f"{self.base_url}/{self.api_prefix}/tools", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to create tool: {response.text}")
return Tool(**response.json())
def create_or_update_tool(
self,
func: Callable,
tags: Optional[List[str]] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
"""
Creates or updates a tool. This stores the source code of function on the server, so that the server can execute the function and generate an OpenAI JSON schemas for it when using with an agent.
Args:
func (callable): The function to create a tool for.
name: (str): Name of the tool (must be unique per-user.)
tags (Optional[List[str]], optional): Tags for the tool. Defaults to None.
return_char_limit (int): The character limit for the tool's return value. Defaults to FUNCTION_RETURN_CHAR_LIMIT.
Returns:
tool (Tool): The created tool.
"""
source_code = parse_source_code(func)
source_type = "python"
# call server function
request = ToolCreate(source_type=source_type, source_code=source_code, return_char_limit=return_char_limit)
if tags:
request.tags = tags
response = requests.put(f"{self.base_url}/{self.api_prefix}/tools", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to create tool: {response.text}")
return Tool(**response.json())
def update_tool(
self,
id: str,
description: Optional[str] = None,
func: Optional[Callable] = None,
tags: Optional[List[str]] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
"""
Update a tool with provided parameters (name, func, tags)
Args:
id (str): ID of the tool
name (str): Name of the tool
func (callable): Function to wrap in a tool
tags (List[str]): Tags for the tool
return_char_limit (int): The character limit for the tool's return value. Defaults to FUNCTION_RETURN_CHAR_LIMIT.
Returns:
tool (Tool): Updated tool
"""
if func:
source_code = parse_source_code(func)
else:
source_code = None
source_type = "python"
request = ToolUpdate(
description=description,
source_type=source_type,
source_code=source_code,
tags=tags,
return_char_limit=return_char_limit,
)
response = requests.patch(f"{self.base_url}/{self.api_prefix}/tools/{id}", json=request.model_dump(), headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to update tool: {response.text}")
return Tool(**response.json())
def list_tools(self, after: Optional[str] = None, limit: Optional[int] = 50) -> List[Tool]:
"""
List available tools for the user.
Returns:
tools (List[Tool]): List of tools
"""
params = {}
if after:
params["after"] = after
if limit:
params["limit"] = limit
response = requests.get(f"{self.base_url}/{self.api_prefix}/tools", params=params, headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list tools: {response.text}")
return [Tool(**tool) for tool in response.json()]
def delete_tool(self, name: str):
"""
Delete a tool given the ID.
Args:
id (str): ID of the tool
"""
response = requests.delete(f"{self.base_url}/{self.api_prefix}/tools/{name}", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to delete tool: {response.text}")
def get_tool(self, id: str) -> Optional[Tool]:
"""
Get a tool give its ID.
Args:
id (str): ID of the tool
Returns:
tool (Tool): Tool
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/tools/{id}", headers=self.headers)
if response.status_code == 404:
return None
elif response.status_code != 200:
raise ValueError(f"Failed to get tool: {response.text}")
return Tool(**response.json())
def set_default_llm_config(self, llm_config: LLMConfig):
"""
Set the default LLM configuration
Args:
llm_config (LLMConfig): LLM configuration
"""
self._default_llm_config = llm_config
def set_default_embedding_config(self, embedding_config: EmbeddingConfig):
"""
Set the default embedding configuration
Args:
embedding_config (EmbeddingConfig): Embedding configuration
"""
self._default_embedding_config = embedding_config
def list_llm_configs(self) -> List[LLMConfig]:
"""
List available LLM configurations
Returns:
configs (List[LLMConfig]): List of LLM configurations
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/models", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list LLM configs: {response.text}")
return [LLMConfig(**config) for config in response.json()]
def list_embedding_configs(self) -> List[EmbeddingConfig]:
"""
List available embedding configurations
Returns:
configs (List[EmbeddingConfig]): List of embedding configurations
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/models/embedding", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to list embedding configs: {response.text}")
return [EmbeddingConfig(**config) for config in response.json()]
def list_orgs(self, after: Optional[str] = None, limit: Optional[int] = 50) -> List[Organization]:
"""
Retrieves a list of all organizations in the database, with optional pagination.
@param after: the pagination cursor, if any
@param limit: the maximum number of organizations to retrieve
@return: a list of Organization objects
"""
params = {"after": after, "limit": limit}
response = requests.get(f"{self.base_url}/{ADMIN_PREFIX}/orgs", headers=self.headers, params=params)
if response.status_code != 200:
raise ValueError(f"Failed to retrieve organizations: {response.text}")
return [Organization(**org_data) for org_data in response.json()]
def create_org(self, name: Optional[str] = None) -> Organization:
"""
Creates an organization with the given name. If not provided, we generate a random one.
@param name: the name of the organization
@return: the created Organization
"""
payload = {"name": name}
response = requests.post(f"{self.base_url}/{ADMIN_PREFIX}/orgs", headers=self.headers, json=payload)
if response.status_code != 200:
raise ValueError(f"Failed to create org: {response.text}")
return Organization(**response.json())
def delete_org(self, org_id: str) -> Organization:
"""
Deletes an organization by its ID.
@param org_id: the ID of the organization to delete
@return: the deleted Organization object
"""
# Define query parameters with org_id
params = {"org_id": org_id}
# Make the DELETE request with query parameters
response = requests.delete(f"{self.base_url}/{ADMIN_PREFIX}/orgs", headers=self.headers, params=params)
if response.status_code == 404:
raise ValueError(f"Organization with ID '{org_id}' does not exist")
elif response.status_code != 200:
raise ValueError(f"Failed to delete organization: {response.text}")
# Parse and return the deleted organization
return Organization(**response.json())
def create_sandbox_config(self, config: Union[LocalSandboxConfig, E2BSandboxConfig]) -> SandboxConfig:
"""
Create a new sandbox configuration.
Args:
config (Union[LocalSandboxConfig, E2BSandboxConfig]): The sandbox settings.
Returns:
SandboxConfig: The created sandbox configuration.
"""
payload = {
"config": config.model_dump(),
}
response = requests.post(f"{self.base_url}/{self.api_prefix}/sandbox-config", headers=self.headers, json=payload)
if response.status_code != 200:
raise ValueError(f"Failed to create sandbox config: {response.text}")
return SandboxConfig(**response.json())
def update_sandbox_config(self, sandbox_config_id: str, config: Union[LocalSandboxConfig, E2BSandboxConfig]) -> SandboxConfig:
"""
Update an existing sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to update.
config (Union[LocalSandboxConfig, E2BSandboxConfig]): The updated sandbox settings.
Returns:
SandboxConfig: The updated sandbox configuration.
"""
payload = {
"config": config.model_dump(),
}
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/sandbox-config/{sandbox_config_id}",
headers=self.headers,
json=payload,
)
if response.status_code != 200:
raise ValueError(f"Failed to update sandbox config with ID '{sandbox_config_id}': {response.text}")
return SandboxConfig(**response.json())
def delete_sandbox_config(self, sandbox_config_id: str) -> None:
"""
Delete a sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to delete.
"""
response = requests.delete(f"{self.base_url}/{self.api_prefix}/sandbox-config/{sandbox_config_id}", headers=self.headers)
if response.status_code == 404:
raise ValueError(f"Sandbox config with ID '{sandbox_config_id}' does not exist")
elif response.status_code != 204:
raise ValueError(f"Failed to delete sandbox config with ID '{sandbox_config_id}': {response.text}")
def list_sandbox_configs(self, limit: int = 50, after: Optional[str] = None) -> List[SandboxConfig]:
"""
List all sandbox configurations.
Args:
limit (int, optional): The maximum number of sandbox configurations to return. Defaults to 50.
after (Optional[str], optional): The pagination cursor for retrieving the next set of results.
Returns:
List[SandboxConfig]: A list of sandbox configurations.
"""
params = {"limit": limit, "after": after}
response = requests.get(f"{self.base_url}/{self.api_prefix}/sandbox-config", headers=self.headers, params=params)
if response.status_code != 200:
raise ValueError(f"Failed to list sandbox configs: {response.text}")
return [SandboxConfig(**config_data) for config_data in response.json()]
def create_sandbox_env_var(
self, sandbox_config_id: str, key: str, value: str, description: Optional[str] = None
) -> SandboxEnvironmentVariable:
"""
Create a new environment variable for a sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to associate the environment variable with.
key (str): The name of the environment variable.
value (str): The value of the environment variable.
description (Optional[str], optional): A description of the environment variable. Defaults to None.
Returns:
SandboxEnvironmentVariable: The created environment variable.
"""
payload = {"key": key, "value": value, "description": description}
response = requests.post(
f"{self.base_url}/{self.api_prefix}/sandbox-config/{sandbox_config_id}/environment-variable",
headers=self.headers,
json=payload,
)
if response.status_code != 200:
raise ValueError(f"Failed to create environment variable for sandbox config ID '{sandbox_config_id}': {response.text}")
return SandboxEnvironmentVariable(**response.json())
def update_sandbox_env_var(
self, env_var_id: str, key: Optional[str] = None, value: Optional[str] = None, description: Optional[str] = None
) -> SandboxEnvironmentVariable:
"""
Update an existing environment variable.
Args:
env_var_id (str): The ID of the environment variable to update.
key (Optional[str], optional): The updated name of the environment variable. Defaults to None.
value (Optional[str], optional): The updated value of the environment variable. Defaults to None.
description (Optional[str], optional): The updated description of the environment variable. Defaults to None.
Returns:
SandboxEnvironmentVariable: The updated environment variable.
"""
payload = {k: v for k, v in {"key": key, "value": value, "description": description}.items() if v is not None}
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/sandbox-config/environment-variable/{env_var_id}",
headers=self.headers,
json=payload,
)
if response.status_code != 200:
raise ValueError(f"Failed to update environment variable with ID '{env_var_id}': {response.text}")
return SandboxEnvironmentVariable(**response.json())
def delete_sandbox_env_var(self, env_var_id: str) -> None:
"""
Delete an environment variable by its ID.
Args:
env_var_id (str): The ID of the environment variable to delete.
"""
response = requests.delete(
f"{self.base_url}/{self.api_prefix}/sandbox-config/environment-variable/{env_var_id}", headers=self.headers
)
if response.status_code == 404:
raise ValueError(f"Environment variable with ID '{env_var_id}' does not exist")
elif response.status_code != 204:
raise ValueError(f"Failed to delete environment variable with ID '{env_var_id}': {response.text}")
def list_sandbox_env_vars(
self, sandbox_config_id: str, limit: int = 50, after: Optional[str] = None
) -> List[SandboxEnvironmentVariable]:
"""
List all environment variables associated with a sandbox configuration.
Args:
sandbox_config_id (str): The ID of the sandbox configuration to retrieve environment variables for.
limit (int, optional): The maximum number of environment variables to return. Defaults to 50.
after (Optional[str], optional): The pagination cursor for retrieving the next set of results.
Returns:
List[SandboxEnvironmentVariable]: A list of environment variables.
"""
params = {"limit": limit, "after": after}
response = requests.get(
f"{self.base_url}/{self.api_prefix}/sandbox-config/{sandbox_config_id}/environment-variable",
headers=self.headers,
params=params,
)
if response.status_code != 200:
raise ValueError(f"Failed to list environment variables for sandbox config ID '{sandbox_config_id}': {response.text}")
return [SandboxEnvironmentVariable(**var_data) for var_data in response.json()]
def update_agent_memory_block_label(self, agent_id: str, current_label: str, new_label: str) -> Memory:
"""Rename a block in the agent's core memory
Args:
agent_id (str): The agent ID
current_label (str): The current label of the block
new_label (str): The new label of the block
Returns:
memory (Memory): The updated memory
"""
block = self.get_agent_memory_block(agent_id, current_label)
return self.update_block(block.id, label=new_label)
def attach_block(self, agent_id: str, block_id: str) -> AgentState:
"""
Attach a block to an agent.
Args:
agent_id (str): ID of the agent
block_id (str): ID of the block to attach
"""
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory/blocks/attach/{block_id}",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to attach block to agent: {response.text}")
return AgentState(**response.json())
def detach_block(self, agent_id: str, block_id: str) -> AgentState:
"""
Detach a block from an agent.
Args:
agent_id (str): ID of the agent
block_id (str): ID of the block to detach
"""
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory/blocks/detach/{block_id}", headers=self.headers
)
if response.status_code != 200:
raise ValueError(f"Failed to detach block from agent: {response.text}")
return AgentState(**response.json())
def list_agent_memory_blocks(self, agent_id: str) -> List[Block]:
"""
Get all the blocks in the agent's core memory
Args:
agent_id (str): The agent ID
Returns:
blocks (List[Block]): The blocks in the agent's core memory
"""
response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory/blocks", headers=self.headers)
if response.status_code != 200:
raise ValueError(f"Failed to get agent memory blocks: {response.text}")
return [Block(**block) for block in response.json()]
def get_agent_memory_block(self, agent_id: str, label: str) -> Block:
"""
Get a block in the agent's core memory by its label
Args:
agent_id (str): The agent ID
label (str): The label in the agent's core memory
Returns:
block (Block): The block corresponding to the label
"""
response = requests.get(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory/blocks/{label}",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to get agent memory block: {response.text}")
return Block(**response.json())
def update_agent_memory_block(
self,
agent_id: str,
label: str,
value: Optional[str] = None,
limit: Optional[int] = None,
):
"""
Update a block in the agent's core memory by specifying its label
Args:
agent_id (str): The agent ID
label (str): The label of the block
value (str): The new value of the block
limit (int): The new limit of the block
Returns:
block (Block): The updated block
"""
# setup data
data = {}
if value:
data["value"] = value
if limit:
data["limit"] = limit
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core-memory/blocks/{label}",
headers=self.headers,
json=data,
)
if response.status_code != 200:
raise ValueError(f"Failed to update agent memory block: {response.text}")
return Block(**response.json())
def update_block(
self,
block_id: str,
label: Optional[str] = None,
value: Optional[str] = None,
limit: Optional[int] = None,
):
"""
Update a block given the ID with the provided fields
Args:
block_id (str): ID of the block
label (str): Label to assign to the block
value (str): Value to assign to the block
limit (int): Token limit to assign to the block
Returns:
block (Block): Updated block
"""
data = {}
if value:
data["value"] = value
if limit:
data["limit"] = limit
if label:
data["label"] = label
response = requests.patch(
f"{self.base_url}/{self.api_prefix}/blocks/{block_id}",
headers=self.headers,
json=data,
)
if response.status_code != 200:
raise ValueError(f"Failed to update block: {response.text}")
return Block(**response.json())
def get_run_messages(
self,
run_id: str,
before: Optional[str] = None,
after: Optional[str] = None,
limit: Optional[int] = 100,
ascending: bool = True,
role: Optional[MessageRole] = None,
) -> List[LettaMessageUnion]:
"""
Get messages associated with a job with filtering options.
Args:
job_id: ID of the job
before: Cursor for pagination
after: Cursor for pagination
limit: Maximum number of messages to return
ascending: Sort order by creation time
role: Filter by message role (user/assistant/system/tool)
Returns:
List of messages matching the filter criteria
"""
params = {
"before": before,
"after": after,
"limit": limit,
"ascending": ascending,
"role": role,
}
# Remove None values
params = {k: v for k, v in params.items() if v is not None}
response = requests.get(f"{self.base_url}/{self.api_prefix}/runs/{run_id}/messages", params=params)
if response.status_code != 200:
raise ValueError(f"Failed to get run messages: {response.text}")
return [LettaMessage(**message) for message in response.json()]
def get_run_usage(
self,
run_id: str,
) -> List[UsageStatistics]:
"""
Get usage statistics associated with a job.
Args:
job_id (str): ID of the job
Returns:
List[UsageStatistics]: List of usage statistics associated with the job
"""
response = requests.get(
f"{self.base_url}/{self.api_prefix}/runs/{run_id}/usage",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to get run usage statistics: {response.text}")
return [UsageStatistics(**stat) for stat in [response.json()]]
def get_run(self, run_id: str) -> Run:
"""
Get a run by ID.
Args:
run_id (str): ID of the run
Returns:
run (Run): Run
"""
response = requests.get(
f"{self.base_url}/{self.api_prefix}/runs/{run_id}",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to get run: {response.text}")
return Run(**response.json())
def delete_run(self, run_id: str) -> None:
"""
Delete a run by ID.
Args:
run_id (str): ID of the run
"""
response = requests.delete(
f"{self.base_url}/{self.api_prefix}/runs/{run_id}",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to delete run: {response.text}")
def list_runs(self) -> List[Run]:
"""
List all runs.
Returns:
runs (List[Run]): List of runs
"""
response = requests.get(
f"{self.base_url}/{self.api_prefix}/runs",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to list runs: {response.text}")
return [Run(**run) for run in response.json()]
def list_active_runs(self) -> List[Run]:
"""
List all active runs.
Returns:
runs (List[Run]): List of active runs
"""
response = requests.get(
f"{self.base_url}/{self.api_prefix}/runs/active",
headers=self.headers,
)
if response.status_code != 200:
raise ValueError(f"Failed to list active runs: {response.text}")
return [Run(**run) for run in response.json()]
def get_tags(
self,
after: Optional[str] = None,
limit: int = 100,
query_text: Optional[str] = None,
) -> List[str]:
"""
Get a list of all unique tags.
Args:
after: Optional cursor for pagination (first tag seen)
limit: Optional maximum number of tags to return
query_text: Optional text to filter tags
Returns:
List[str]: List of unique tags
"""
params = {}
if after:
params["after"] = after
if limit:
params["limit"] = limit
if query_text:
params["query_text"] = query_text
response = requests.get(f"{self.base_url}/{self.api_prefix}/tags", headers=self.headers, params=params)
if response.status_code != 200:
raise ValueError(f"Failed to get tags: {response.text}")
return response.json()
class LocalClient(AbstractClient):
"""
A local client for Letta, which corresponds to a single user.
Attributes:
user_id (str): The user ID.
debug (bool): Whether to print debug information.
interface (QueuingInterface): The interface for the client.
server (SyncServer): The server for the client.
"""
def __init__(
self,
user_id: Optional[str] = None,
org_id: Optional[str] = None,
debug: bool = False,
default_llm_config: Optional[LLMConfig] = None,
default_embedding_config: Optional[EmbeddingConfig] = None,
):
"""
Initializes a new instance of Client class.
Args:
user_id (str): The user ID.
debug (bool): Whether to print debug information.
"""
from letta.server.server import SyncServer
# set logging levels
letta.utils.DEBUG = debug
logging.getLogger().setLevel(logging.CRITICAL)
# save default model config
self._default_llm_config = default_llm_config
self._default_embedding_config = default_embedding_config
# create server
self.interface = QueuingInterface(debug=debug)
self.server = SyncServer(default_interface_factory=lambda: self.interface)
# save org_id that `LocalClient` is associated with
if org_id:
self.org_id = org_id
else:
self.org_id = self.server.organization_manager.DEFAULT_ORG_ID
# save user_id that `LocalClient` is associated with
if user_id:
self.user_id = user_id
else:
# get default user
self.user_id = self.server.user_manager.DEFAULT_USER_ID
self.user = self.server.user_manager.get_user_or_default(self.user_id)
self.organization = self.server.get_organization_or_default(self.org_id)
# agents
def list_agents(
self,
query_text: Optional[str] = None,
tags: Optional[List[str]] = None,
limit: int = 100,
before: Optional[str] = None,
after: Optional[str] = None,
) -> List[AgentState]:
self.interface.clear()
return self.server.agent_manager.list_agents(
actor=self.user, tags=tags, query_text=query_text, limit=limit, before=before, after=after
)
def agent_exists(self, agent_id: Optional[str] = None, agent_name: Optional[str] = None) -> bool:
"""
Check if an agent exists
Args:
agent_id (str): ID of the agent
agent_name (str): Name of the agent
Returns:
exists (bool): `True` if the agent exists, `False` otherwise
"""
if not (agent_id or agent_name):
raise ValueError(f"Either agent_id or agent_name must be provided")
if agent_id and agent_name:
raise ValueError(f"Only one of agent_id or agent_name can be provided")
existing = self.list_agents()
if agent_id:
return str(agent_id) in [str(agent.id) for agent in existing]
else:
return agent_name in [str(agent.name) for agent in existing]
def create_agent(
self,
name: Optional[str] = None,
# agent config
agent_type: Optional[AgentType] = AgentType.memgpt_agent,
# model configs
embedding_config: EmbeddingConfig = None,
llm_config: LLMConfig = None,
# memory
memory: Memory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_persona_text(DEFAULT_PERSONA)),
block_ids: Optional[List[str]] = None,
# TODO: change to this when we are ready to migrate all the tests/examples (matches the REST API)
# memory_blocks=[
# {"label": "human", "value": get_human_text(DEFAULT_HUMAN), "limit": 5000},
# {"label": "persona", "value": get_persona_text(DEFAULT_PERSONA), "limit": 5000},
# ],
# system
system: Optional[str] = None,
# tools
tool_ids: Optional[List[str]] = None,
tool_rules: Optional[List[BaseToolRule]] = None,
include_base_tools: Optional[bool] = True,
include_multi_agent_tools: bool = False,
include_base_tool_rules: bool = True,
# metadata
metadata: Optional[Dict] = {"human:": DEFAULT_HUMAN, "persona": DEFAULT_PERSONA},
description: Optional[str] = None,
initial_message_sequence: Optional[List[Message]] = None,
tags: Optional[List[str]] = None,
message_buffer_autoclear: bool = False,
response_format: Optional[ResponseFormatUnion] = None,
) -> AgentState:
"""Create an agent
Args:
name (str): Name of the agent
embedding_config (EmbeddingConfig): Embedding configuration
llm_config (LLMConfig): LLM configuration
memory_blocks (List[Dict]): List of configurations for the memory blocks (placed in core-memory)
system (str): System configuration
tools (List[str]): List of tools
tool_rules (Optional[List[BaseToolRule]]): List of tool rules
include_base_tools (bool): Include base tools
include_multi_agent_tools (bool): Include multi agent tools
metadata (Dict): Metadata
description (str): Description
tags (List[str]): Tags for filtering agents
Returns:
agent_state (AgentState): State of the created agent
"""
# construct list of tools
tool_ids = tool_ids or []
# check if default configs are provided
assert embedding_config or self._default_embedding_config, f"Embedding config must be provided"
assert llm_config or self._default_llm_config, f"LLM config must be provided"
# TODO: This should not happen here, we need to have clear separation between create/add blocks
for block in memory.get_blocks():
self.server.block_manager.create_or_update_block(block, actor=self.user)
# Also get any existing block_ids passed in
block_ids = block_ids or []
# create agent
# Create the base parameters
create_params = {
"description": description,
"metadata": metadata,
"memory_blocks": [],
"block_ids": [b.id for b in memory.get_blocks()] + block_ids,
"tool_ids": tool_ids,
"tool_rules": tool_rules,
"include_base_tools": include_base_tools,
"include_multi_agent_tools": include_multi_agent_tools,
"include_base_tool_rules": include_base_tool_rules,
"system": system,
"agent_type": agent_type,
"llm_config": llm_config if llm_config else self._default_llm_config,
"embedding_config": embedding_config if embedding_config else self._default_embedding_config,
"initial_message_sequence": initial_message_sequence,
"tags": tags,
"message_buffer_autoclear": message_buffer_autoclear,
"response_format": response_format,
}
# Only add name if it's not None
if name is not None:
create_params["name"] = name
agent_state = self.server.create_agent(
CreateAgent(**create_params),
actor=self.user,
)
# TODO: get full agent state
return self.server.agent_manager.get_agent_by_id(agent_state.id, actor=self.user)
def update_agent(
self,
agent_id: str,
name: Optional[str] = None,
description: Optional[str] = None,
system: Optional[str] = None,
tool_ids: Optional[List[str]] = None,
tags: Optional[List[str]] = None,
metadata: Optional[Dict] = None,
llm_config: Optional[LLMConfig] = None,
embedding_config: Optional[EmbeddingConfig] = None,
message_ids: Optional[List[str]] = None,
response_format: Optional[ResponseFormatUnion] = None,
):
"""
Update an existing agent
Args:
agent_id (str): ID of the agent
name (str): Name of the agent
description (str): Description of the agent
system (str): System configuration
tools (List[str]): List of tools
metadata (Dict): Metadata
llm_config (LLMConfig): LLM configuration
embedding_config (EmbeddingConfig): Embedding configuration
message_ids (List[str]): List of message IDs
tags (List[str]): Tags for filtering agents
Returns:
agent_state (AgentState): State of the updated agent
"""
# TODO: add the ability to reset linked block_ids
self.interface.clear()
agent_state = self.server.agent_manager.update_agent(
agent_id,
UpdateAgent(
name=name,
system=system,
tool_ids=tool_ids,
tags=tags,
description=description,
metadata=metadata,
llm_config=llm_config,
embedding_config=embedding_config,
message_ids=message_ids,
response_format=response_format,
),
actor=self.user,
)
return agent_state
def get_tools_from_agent(self, agent_id: str) -> List[Tool]:
"""
Get tools from an existing agent.
Args:
agent_id (str): ID of the agent
Returns:
List[Tool]: A list of Tool objs
"""
self.interface.clear()
return self.server.agent_manager.get_agent_by_id(agent_id=agent_id, actor=self.user).tools
def attach_tool(self, agent_id: str, tool_id: str) -> AgentState:
"""
Add tool to an existing agent
Args:
agent_id (str): ID of the agent
tool_id (str): A tool id
Returns:
agent_state (AgentState): State of the updated agent
"""
self.interface.clear()
agent_state = self.server.agent_manager.attach_tool(agent_id=agent_id, tool_id=tool_id, actor=self.user)
return agent_state
def detach_tool(self, agent_id: str, tool_id: str) -> AgentState:
"""
Removes tools from an existing agent
Args:
agent_id (str): ID of the agent
tool_id (str): The tool id
Returns:
agent_state (AgentState): State of the updated agent
"""
self.interface.clear()
agent_state = self.server.agent_manager.detach_tool(agent_id=agent_id, tool_id=tool_id, actor=self.user)
return agent_state
def rename_agent(self, agent_id: str, new_name: str) -> AgentState:
"""
Rename an agent
Args:
agent_id (str): ID of the agent
new_name (str): New name for the agent
Returns:
agent_state (AgentState): State of the updated agent
"""
return self.update_agent(agent_id, name=new_name)
def delete_agent(self, agent_id: str) -> None:
"""
Delete an agent
Args:
agent_id (str): ID of the agent to delete
"""
self.server.agent_manager.delete_agent(agent_id=agent_id, actor=self.user)
def get_agent_by_name(self, agent_name: str) -> AgentState:
"""
Get an agent by its name
Args:
agent_name (str): Name of the agent
Returns:
agent_state (AgentState): State of the agent
"""
self.interface.clear()
return self.server.agent_manager.get_agent_by_name(agent_name=agent_name, actor=self.user)
def get_agent(self, agent_id: str) -> AgentState:
"""
Get an agent's state by its ID.
Args:
agent_id (str): ID of the agent
Returns:
agent_state (AgentState): State representation of the agent
"""
self.interface.clear()
return self.server.agent_manager.get_agent_by_id(agent_id=agent_id, actor=self.user)
def get_agent_id(self, agent_name: str) -> Optional[str]:
"""
Get the ID of an agent by name (names are unique per user)
Args:
agent_name (str): Name of the agent
Returns:
agent_id (str): ID of the agent
"""
self.interface.clear()
assert agent_name, f"Agent name must be provided"
# TODO: Refactor this futher to not have downstream users expect Optionals - this should just error
try:
return self.server.agent_manager.get_agent_by_name(agent_name=agent_name, actor=self.user).id
except NoResultFound:
return None
# memory
def get_in_context_memory(self, agent_id: str) -> Memory:
"""
Get the in-context (i.e. core) memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
memory (Memory): In-context memory of the agent
"""
memory = self.server.get_agent_memory(agent_id=agent_id, actor=self.user)
return memory
def get_core_memory(self, agent_id: str) -> Memory:
return self.get_in_context_memory(agent_id)
def update_in_context_memory(self, agent_id: str, section: str, value: Union[List[str], str]) -> Memory:
"""
Update the in-context memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
memory (Memory): The updated in-context memory of the agent
"""
# TODO: implement this (not sure what it should look like)
memory = self.server.update_agent_core_memory(agent_id=agent_id, label=section, value=value, actor=self.user)
return memory
def get_archival_memory_summary(self, agent_id: str) -> ArchivalMemorySummary:
"""
Get a summary of the archival memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
summary (ArchivalMemorySummary): Summary of the archival memory
"""
return self.server.get_archival_memory_summary(agent_id=agent_id, actor=self.user)
def get_recall_memory_summary(self, agent_id: str) -> RecallMemorySummary:
"""
Get a summary of the recall memory of an agent
Args:
agent_id (str): ID of the agent
Returns:
summary (RecallMemorySummary): Summary of the recall memory
"""
return self.server.get_recall_memory_summary(agent_id=agent_id, actor=self.user)
def get_in_context_messages(self, agent_id: str) -> List[Message]:
"""
Get in-context messages of an agent
Args:
agent_id (str): ID of the agent
Returns:
messages (List[Message]): List of in-context messages
"""
return self.server.agent_manager.get_in_context_messages(agent_id=agent_id, actor=self.user)
# agent interactions
def send_messages(
self,
agent_id: str,
messages: List[Union[Message | MessageCreate]],
):
"""
Send pre-packed messages to an agent.
Args:
agent_id (str): ID of the agent
messages (List[Union[Message | MessageCreate]]): List of messages to send
Returns:
response (LettaResponse): Response from the agent
"""
self.interface.clear()
usage = self.server.send_messages(actor=self.user, agent_id=agent_id, input_messages=messages)
# format messages
return LettaResponse(messages=messages, usage=usage)
def send_message(
self,
message: str,
role: str,
name: Optional[str] = None,
agent_id: Optional[str] = None,
agent_name: Optional[str] = None,
stream_steps: bool = False,
stream_tokens: bool = False,
) -> LettaResponse:
"""
Send a message to an agent
Args:
message (str): Message to send
role (str): Role of the message
agent_id (str): ID of the agent
name(str): Name of the sender
stream (bool): Stream the response (default: `False`)
Returns:
response (LettaResponse): Response from the agent
"""
if not agent_id:
# lookup agent by name
assert agent_name, f"Either agent_id or agent_name must be provided"
agent_id = self.get_agent_id(agent_name=agent_name)
assert agent_id, f"Agent with name {agent_name} not found"
if stream_steps or stream_tokens:
# TODO: implement streaming with stream=True/False
raise NotImplementedError
self.interface.clear()
usage = self.server.send_messages(
actor=self.user,
agent_id=agent_id,
input_messages=[MessageCreate(role=MessageRole(role), content=message, name=name)],
)
## TODO: need to make sure date/timestamp is propely passed
## TODO: update self.interface.to_list() to return actual Message objects
## here, the message objects will have faulty created_by timestamps
# messages = self.interface.to_list()
# for m in messages:
# assert isinstance(m, Message), f"Expected Message object, got {type(m)}"
# letta_messages = []
# for m in messages:
# letta_messages += m.to_letta_messages()
# return LettaResponse(messages=letta_messages, usage=usage)
# format messages
messages = self.interface.to_list()
letta_messages = []
for m in messages:
letta_messages += m.to_letta_messages()
return LettaResponse(messages=letta_messages, usage=usage)
def user_message(self, agent_id: str, message: str) -> LettaResponse:
"""
Send a message to an agent as a user
Args:
agent_id (str): ID of the agent
message (str): Message to send
Returns:
response (LettaResponse): Response from the agent
"""
self.interface.clear()
return self.send_message(role="user", agent_id=agent_id, message=message)
def run_command(self, agent_id: str, command: str) -> LettaResponse:
"""
Run a command on the agent
Args:
agent_id (str): The agent ID
command (str): The command to run
Returns:
LettaResponse: The response from the agent
"""
self.interface.clear()
usage = self.server.run_command(user_id=self.user_id, agent_id=agent_id, command=command)
# NOTE: messages/usage may be empty, depending on the command
return LettaResponse(messages=self.interface.to_list(), usage=usage)
# archival memory
# humans / personas
def get_block_id(self, name: str, label: str) -> str | None:
return None
def create_human(self, name: str, text: str):
"""
Create a human block template (saved human string to pre-fill `ChatMemory`)
Args:
name (str): Name of the human block
text (str): Text of the human block
Returns:
human (Human): Human block
"""
return self.server.block_manager.create_or_update_block(Human(template_name=name, value=text), actor=self.user)
def create_persona(self, name: str, text: str):
"""
Create a persona block template (saved persona string to pre-fill `ChatMemory`)
Args:
name (str): Name of the persona block
text (str): Text of the persona block
Returns:
persona (Persona): Persona block
"""
return self.server.block_manager.create_or_update_block(Persona(template_name=name, value=text), actor=self.user)
def list_humans(self):
"""
List available human block templates
Returns:
humans (List[Human]): List of human blocks
"""
return []
def list_personas(self) -> List[Persona]:
"""
List available persona block templates
Returns:
personas (List[Persona]): List of persona blocks
"""
return []
def update_human(self, human_id: str, text: str):
"""
Update a human block template
Args:
human_id (str): ID of the human block
text (str): Text of the human block
Returns:
human (Human): Updated human block
"""
return self.server.block_manager.update_block(
block_id=human_id, block_update=UpdateHuman(value=text, is_template=True), actor=self.user
)
def update_persona(self, persona_id: str, text: str):
"""
Update a persona block template
Args:
persona_id (str): ID of the persona block
text (str): Text of the persona block
Returns:
persona (Persona): Updated persona block
"""
return self.server.block_manager.update_block(
block_id=persona_id, block_update=UpdatePersona(value=text, is_template=True), actor=self.user
)
def get_persona(self, id: str) -> Persona:
"""
Get a persona block template
Args:
id (str): ID of the persona block
Returns:
persona (Persona): Persona block
"""
assert id, f"Persona ID must be provided"
return Persona(**self.server.block_manager.get_block_by_id(id, actor=self.user).model_dump())
def get_human(self, id: str) -> Human:
"""
Get a human block template
Args:
id (str): ID of the human block
Returns:
human (Human): Human block
"""
assert id, f"Human ID must be provided"
return Human(**self.server.block_manager.get_block_by_id(id, actor=self.user).model_dump())
def get_persona_id(self, name: str) -> str | None:
"""
Get the ID of a persona block template
Args:
name (str): Name of the persona block
Returns:
id (str): ID of the persona block
"""
return None
def get_human_id(self, name: str) -> str | None:
"""
Get the ID of a human block template
Args:
name (str): Name of the human block
Returns:
id (str): ID of the human block
"""
return None
def delete_persona(self, id: str):
"""
Delete a persona block template
Args:
id (str): ID of the persona block
"""
self.delete_block(id)
def delete_human(self, id: str):
"""
Delete a human block template
Args:
id (str): ID of the human block
"""
self.delete_block(id)
# tools
def load_langchain_tool(self, langchain_tool: "LangChainBaseTool", additional_imports_module_attr_map: dict[str, str] = None) -> Tool:
tool_create = ToolCreate.from_langchain(
langchain_tool=langchain_tool,
additional_imports_module_attr_map=additional_imports_module_attr_map,
)
return self.server.tool_manager.create_or_update_langchain_tool(tool_create=tool_create, actor=self.user)
def load_composio_tool(self, action: "ActionType") -> Tool:
tool_create = ToolCreate.from_composio(action_name=action.name)
return self.server.tool_manager.create_or_update_composio_tool(tool_create=tool_create, actor=self.user)
def create_tool(
self,
func,
tags: Optional[List[str]] = None,
description: Optional[str] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
"""
Create a tool. This stores the source code of function on the server, so that the server can execute the function and generate an OpenAI JSON schemas for it when using with an agent.
Args:
func (callable): The function to create a tool for.
tags (Optional[List[str]], optional): Tags for the tool. Defaults to None.
description (str, optional): The description.
return_char_limit (int): The character limit for the tool's return value. Defaults to FUNCTION_RETURN_CHAR_LIMIT.
Returns:
tool (Tool): The created tool.
"""
# TODO: check if tool already exists
# TODO: how to load modules?
# parse source code/schema
source_code = parse_source_code(func)
source_type = "python"
name = func.__name__ # Initialize name using function's __name__
if not tags:
tags = []
# call server function
return self.server.tool_manager.create_tool(
Tool(
source_type=source_type,
source_code=source_code,
name=name,
tags=tags,
description=description,
return_char_limit=return_char_limit,
),
actor=self.user,
)
def create_or_update_tool(
self,
func,
tags: Optional[List[str]] = None,
description: Optional[str] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
"""
Creates or updates a tool. This stores the source code of function on the server, so that the server can execute the function and generate an OpenAI JSON schemas for it when using with an agent.
Args:
func (callable): The function to create a tool for.
tags (Optional[List[str]], optional): Tags for the tool. Defaults to None.
description (str, optional): The description.
return_char_limit (int): The character limit for the tool's return value. Defaults to FUNCTION_RETURN_CHAR_LIMIT.
Returns:
tool (Tool): The created tool.
"""
source_code = parse_source_code(func)
source_type = "python"
if not tags:
tags = []
# call server function
return self.server.tool_manager.create_or_update_tool(
Tool(
source_type=source_type,
source_code=source_code,
tags=tags,
description=description,
return_char_limit=return_char_limit,
),
actor=self.user,
)
def update_tool(
self,
id: str,
description: Optional[str] = None,
func: Optional[Callable] = None,
tags: Optional[List[str]] = None,
return_char_limit: int = FUNCTION_RETURN_CHAR_LIMIT,
) -> Tool:
"""
Update a tool with provided parameters (name, func, tags)
Args:
id (str): ID of the tool
func (callable): Function to wrap in a tool
tags (List[str]): Tags for the tool
return_char_limit (int): The character limit for the tool's return value. Defaults to FUNCTION_RETURN_CHAR_LIMIT.
Returns:
tool (Tool): Updated tool
"""
update_data = {
"source_type": "python", # Always include source_type
"source_code": parse_source_code(func) if func else None,
"tags": tags,
"description": description,
"return_char_limit": return_char_limit,
}
# Filter out any None values from the dictionary
update_data = {key: value for key, value in update_data.items() if value is not None}
return self.server.tool_manager.update_tool_by_id(tool_id=id, tool_update=ToolUpdate(**update_data), actor=self.user)
def list_tools(self, after: Optional[str] = None, limit: Optional[int] = 50) -> List[Tool]:
"""
List available tools for the user.
Returns:
tools (List[Tool]): List of tools
"""
# Get the current event loop or create a new one if there isn't one
try:
loop = asyncio.get_event_loop()
if loop.is_running():
# We're in an async context but can't await - use a new loop via run_coroutine_threadsafe
concurrent_future = asyncio.run_coroutine_threadsafe(
self.server.tool_manager.list_tools_async(actor=self.user, after=after, limit=limit), loop
)
return concurrent_future.result()
else:
# We have a loop but it's not running - we can just run the coroutine
return loop.run_until_complete(self.server.tool_manager.list_tools_async(actor=self.user, after=after, limit=limit))
except RuntimeError:
# No running event loop - create a new one with asyncio.run
return asyncio.run(self.server.tool_manager.list_tools_async(actor=self.user, after=after, limit=limit))
def get_tool(self, id: str) -> Optional[Tool]:
"""
Get a tool given its ID.
Args:
id (str): ID of the tool
Returns:
tool (Tool): Tool
"""
return self.server.tool_manager.get_tool_by_id(id, actor=self.user)
def delete_tool(self, id: str):
"""
Delete a tool given the ID.
Args:
id (str): ID of the tool
"""
return self.server.tool_manager.delete_tool_by_id(id, actor=self.user)
def get_tool_id(self, name: str) -> Optional[str]:
"""
Get the ID of a tool from its name. The client will use the org_id it is configured with.
Args:
name (str): Name of the tool
Returns:
id (str): ID of the tool (`None` if not found)
"""
tool = self.server.tool_manager.get_tool_by_name(tool_name=name, actor=self.user)
return tool.id if tool else None
def list_attached_tools(self, agent_id: str) -> List[Tool]:
"""
List all tools attached to an agent.
Args:
agent_id (str): ID of the agent
Returns:
List[Tool]: List of tools attached to the agent
"""
return self.server.agent_manager.list_attached_tools(agent_id=agent_id, actor=self.user)
def load_data(self, connector: DataConnector, source_name: str):
"""
Load data into a source
Args:
connector (DataConnector): Data connector
source_name (str): Name of the source
"""
self.server.load_data(user_id=self.user_id, connector=connector, source_name=source_name)
def load_file_to_source(self, filename: str, source_id: str, blocking=True):
"""
Load a file into a source
Args:
filename (str): Name of the file
source_id (str): ID of the source
blocking (bool): Block until the job is complete
Returns:
job (Job): Data loading job including job status and metadata
"""
job = Job(
user_id=self.user_id,
status=JobStatus.created,
metadata={"type": "embedding", "filename": filename, "source_id": source_id},
)
job = self.server.job_manager.create_job(pydantic_job=job, actor=self.user)
# TODO: implement blocking vs. non-blocking
self.server.load_file_to_source(source_id=source_id, file_path=filename, job_id=job.id, actor=self.user)
return job
def delete_file_from_source(self, source_id: str, file_id: str) -> None:
self.server.source_manager.delete_file(file_id, actor=self.user)
def get_job(self, job_id: str):
return self.server.job_manager.get_job_by_id(job_id=job_id, actor=self.user)
def delete_job(self, job_id: str):
return self.server.job_manager.delete_job_by_id(job_id=job_id, actor=self.user)
def list_jobs(self):
return self.server.job_manager.list_jobs(actor=self.user)
def list_active_jobs(self):
return self.server.job_manager.list_jobs(actor=self.user, statuses=[JobStatus.created, JobStatus.running])
def create_source(self, name: str, embedding_config: Optional[EmbeddingConfig] = None) -> Source:
"""
Create a source
Args:
name (str): Name of the source
Returns:
source (Source): Created source
"""
assert embedding_config or self._default_embedding_config, f"Must specify embedding_config for source"
source = Source(
name=name, embedding_config=embedding_config or self._default_embedding_config, organization_id=self.user.organization_id
)
return self.server.source_manager.create_source(source=source, actor=self.user)
def delete_source(self, source_id: str):
"""
Delete a source
Args:
source_id (str): ID of the source
"""
# TODO: delete source data
self.server.delete_source(source_id=source_id, actor=self.user)
def get_source(self, source_id: str) -> Source:
"""
Get a source given the ID.
Args:
source_id (str): ID of the source
Returns:
source (Source): Source
"""
return self.server.source_manager.get_source_by_id(source_id=source_id, actor=self.user)
def get_source_id(self, source_name: str) -> str:
"""
Get the ID of a source
Args:
source_name (str): Name of the source
Returns:
source_id (str): ID of the source
"""
return self.server.source_manager.get_source_by_name(source_name=source_name, actor=self.user).id
def attach_source(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None) -> AgentState:
"""
Attach a source to an agent
Args:
agent_id (str): ID of the agent
source_id (str): ID of the source
source_name (str): Name of the source
"""
if source_name:
source = self.server.source_manager.get_source_by_id(source_id=source_id, actor=self.user)
source_id = source.id
return self.server.agent_manager.attach_source(source_id=source_id, agent_id=agent_id, actor=self.user)
def detach_source(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None) -> AgentState:
"""
Detach a source from an agent by removing all `Passage` objects that were loaded from the source from archival memory.
Args:
agent_id (str): ID of the agent
source_id (str): ID of the source
source_name (str): Name of the source
Returns:
source (Source): Detached source
"""
if source_name:
source = self.server.source_manager.get_source_by_id(source_id=source_id, actor=self.user)
source_id = source.id
return self.server.agent_manager.detach_source(agent_id=agent_id, source_id=source_id, actor=self.user)
def list_sources(self) -> List[Source]:
"""
List available sources
Returns:
sources (List[Source]): List of sources
"""
return self.server.list_all_sources(actor=self.user)
def list_attached_sources(self, agent_id: str) -> List[Source]:
"""
List sources attached to an agent
Args:
agent_id (str): ID of the agent
Returns:
sources (List[Source]): List of sources
"""
return self.server.agent_manager.list_attached_sources(agent_id=agent_id, actor=self.user)
def list_files_from_source(self, source_id: str, limit: int = 1000, after: Optional[str] = None) -> List[FileMetadata]:
"""
List files from source.
Args:
source_id (str): ID of the source
limit (int): The # of items to return
after (str): The cursor for fetching the next page
Returns:
files (List[FileMetadata]): List of files
"""
return self.server.source_manager.list_files(source_id=source_id, limit=limit, after=after, actor=self.user)
def update_source(self, source_id: str, name: Optional[str] = None) -> Source:
"""
Update a source
Args:
source_id (str): ID of the source
name (str): Name of the source
Returns:
source (Source): Updated source
"""
# TODO should the arg here just be "source_update: Source"?
request = SourceUpdate(name=name)
return self.server.source_manager.update_source(source_id=source_id, source_update=request, actor=self.user)
# archival memory
def insert_archival_memory(self, agent_id: str, memory: str) -> List[Passage]:
"""
Insert archival memory into an agent
Args:
agent_id (str): ID of the agent
memory (str): Memory string to insert
Returns:
passages (List[Passage]): List of inserted passages
"""
return self.server.insert_archival_memory(agent_id=agent_id, memory_contents=memory, actor=self.user)
def delete_archival_memory(self, agent_id: str, memory_id: str):
"""
Delete archival memory from an agent
Args:
agent_id (str): ID of the agent
memory_id (str): ID of the memory
"""
self.server.delete_archival_memory(memory_id=memory_id, actor=self.user)
def get_archival_memory(
self, agent_id: str, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000
) -> List[Passage]:
"""
Get archival memory from an agent with pagination.
Args:
agent_id (str): ID of the agent
before (str): Get memories before a certain time
after (str): Get memories after a certain time
limit (int): Limit number of memories
Returns:
passages (List[Passage]): List of passages
"""
return self.server.get_agent_archival(user_id=self.user_id, agent_id=agent_id, limit=limit)
# recall memory
def get_messages(
self, agent_id: str, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000
) -> List[LettaMessage]:
"""
Get messages from an agent with pagination.
Args:
agent_id (str): ID of the agent
before (str): Get messages before a certain time
after (str): Get messages after a certain time
limit (int): Limit number of messages
Returns:
messages (List[Message]): List of messages
"""
self.interface.clear()
return self.server.get_agent_recall(
user_id=self.user_id,
agent_id=agent_id,
before=before,
after=after,
limit=limit,
reverse=True,
return_message_object=False,
)
def list_blocks(self, label: Optional[str] = None, templates_only: Optional[bool] = True) -> List[Block]:
"""
List available blocks
Args:
label (str): Label of the block
templates_only (bool): List only templates
Returns:
blocks (List[Block]): List of blocks
"""
return []
def create_block(
self, label: str, value: str, limit: Optional[int] = None, template_name: Optional[str] = None, is_template: bool = False
) -> Block: #
"""
Create a block
Args:
label (str): Label of the block
name (str): Name of the block
text (str): Text of the block
limit (int): Character of the block
Returns:
block (Block): Created block
"""
block = Block(label=label, template_name=template_name, value=value, is_template=is_template)
if limit:
block.limit = limit
return self.server.block_manager.create_or_update_block(block, actor=self.user)
def update_block(self, block_id: str, name: Optional[str] = None, text: Optional[str] = None, limit: Optional[int] = None) -> Block:
"""
Update a block
Args:
block_id (str): ID of the block
name (str): Name of the block
text (str): Text of the block
Returns:
block (Block): Updated block
"""
return self.server.block_manager.update_block(
block_id=block_id,
block_update=BlockUpdate(template_name=name, value=text, limit=limit if limit else self.get_block(block_id).limit),
actor=self.user,
)
def get_block(self, block_id: str) -> Block:
"""
Get a block
Args:
block_id (str): ID of the block
Returns:
block (Block): Block
"""
return self.server.block_manager.get_block_by_id(block_id, actor=self.user)
def delete_block(self, id: str) -> Block:
"""
Delete a block
Args:
id (str): ID of the block
Returns:
block (Block): Deleted block
"""
return self.server.block_manager.delete_block(id, actor=self.user)
def set_default_llm_config(self, llm_config: LLMConfig):
"""
Set the default LLM configuration for agents.
Args:
llm_config (LLMConfig): LLM configuration
"""
self._default_llm_config = llm_config
def set_default_embedding_config(self, embedding_config: EmbeddingConfig):
"""
Set the default embedding configuration for agents.
Args:
embedding_config (EmbeddingConfig): Embedding configuration
"""
self._default_embedding_config = embedding_config
def list_llm_configs(self) -> List[LLMConfig]:
"""
List available LLM configurations
Returns:
configs (List[LLMConfig]): List of LLM configurations
"""
return self.server.list_llm_models(actor=self.user)
def list_embedding_configs(self) -> List[EmbeddingConfig]:
"""
List available embedding configurations
Returns:
configs (List[EmbeddingConfig]): List of embedding configurations
"""
return self.server.list_embedding_models(actor=self.user)
def create_org(self, name: Optional[str] = None) -> Organization:
return self.server.organization_manager.create_organization(pydantic_org=Organization(name=name))
def list_orgs(self, after: Optional[str] = None, limit: Optional[int] = 50) -> List[Organization]:
return self.server.organization_manager.list_organizations(limit=limit, after=after)
def delete_org(self, org_id: str) -> Organization:
return self.server.organization_manager.delete_organization_by_id(org_id=org_id)
def create_sandbox_config(self, config: Union[LocalSandboxConfig, E2BSandboxConfig]) -> SandboxConfig:
"""
Create a new sandbox configuration.
"""
config_create = SandboxConfigCreate(config=config)
return self.server.sandbox_config_manager.create_or_update_sandbox_config(sandbox_config_create=config_create, actor=self.user)
def update_sandbox_config(self, sandbox_config_id: str, config: Union[LocalSandboxConfig, E2BSandboxConfig]) -> SandboxConfig:
"""
Update an existing sandbox configuration.
"""
sandbox_update = SandboxConfigUpdate(config=config)
return self.server.sandbox_config_manager.update_sandbox_config(
sandbox_config_id=sandbox_config_id, sandbox_update=sandbox_update, actor=self.user
)
def delete_sandbox_config(self, sandbox_config_id: str) -> None:
"""
Delete a sandbox configuration.
"""
return self.server.sandbox_config_manager.delete_sandbox_config(sandbox_config_id=sandbox_config_id, actor=self.user)
def list_sandbox_configs(self, limit: int = 50, after: Optional[str] = None) -> List[SandboxConfig]:
"""
List all sandbox configurations.
"""
return self.server.sandbox_config_manager.list_sandbox_configs(actor=self.user, limit=limit, after=after)
def create_sandbox_env_var(
self, sandbox_config_id: str, key: str, value: str, description: Optional[str] = None
) -> SandboxEnvironmentVariable:
"""
Create a new environment variable for a sandbox configuration.
"""
env_var_create = SandboxEnvironmentVariableCreate(key=key, value=value, description=description)
return self.server.sandbox_config_manager.create_sandbox_env_var(
env_var_create=env_var_create, sandbox_config_id=sandbox_config_id, actor=self.user
)
def update_sandbox_env_var(
self, env_var_id: str, key: Optional[str] = None, value: Optional[str] = None, description: Optional[str] = None
) -> SandboxEnvironmentVariable:
"""
Update an existing environment variable.
"""
env_var_update = SandboxEnvironmentVariableUpdate(key=key, value=value, description=description)
return self.server.sandbox_config_manager.update_sandbox_env_var(
env_var_id=env_var_id, env_var_update=env_var_update, actor=self.user
)
def delete_sandbox_env_var(self, env_var_id: str) -> None:
"""
Delete an environment variable by its ID.
"""
return self.server.sandbox_config_manager.delete_sandbox_env_var(env_var_id=env_var_id, actor=self.user)
def list_sandbox_env_vars(
self, sandbox_config_id: str, limit: int = 50, after: Optional[str] = None
) -> List[SandboxEnvironmentVariable]:
"""
List all environment variables associated with a sandbox configuration.
"""
return self.server.sandbox_config_manager.list_sandbox_env_vars(
sandbox_config_id=sandbox_config_id, actor=self.user, limit=limit, after=after
)
def update_agent_memory_block_label(self, agent_id: str, current_label: str, new_label: str) -> Memory:
"""Rename a block in the agent's core memory
Args:
agent_id (str): The agent ID
current_label (str): The current label of the block
new_label (str): The new label of the block
Returns:
memory (Memory): The updated memory
"""
block = self.get_agent_memory_block(agent_id, current_label)
return self.update_block(block.id, label=new_label)
def get_agent_memory_blocks(self, agent_id: str) -> List[Block]:
"""
Get all the blocks in the agent's core memory
Args:
agent_id (str): The agent ID
Returns:
blocks (List[Block]): The blocks in the agent's core memory
"""
agent = self.server.agent_manager.get_agent_by_id(agent_id=agent_id, actor=self.user)
return agent.memory.blocks
def get_agent_memory_block(self, agent_id: str, label: str) -> Block:
"""
Get a block in the agent's core memory by its label
Args:
agent_id (str): The agent ID
label (str): The label in the agent's core memory
Returns:
block (Block): The block corresponding to the label
"""
return self.server.agent_manager.get_block_with_label(agent_id=agent_id, block_label=label, actor=self.user)
def update_agent_memory_block(
self,
agent_id: str,
label: str,
value: Optional[str] = None,
limit: Optional[int] = None,
):
"""
Update a block in the agent's core memory by specifying its label
Args:
agent_id (str): The agent ID
label (str): The label of the block
value (str): The new value of the block
limit (int): The new limit of the block
Returns:
block (Block): The updated block
"""
block = self.get_agent_memory_block(agent_id, label)
data = {}
if value:
data["value"] = value
if limit:
data["limit"] = limit
return self.server.block_manager.update_block(block.id, actor=self.user, block_update=BlockUpdate(**data))
def update_block(
self,
block_id: str,
label: Optional[str] = None,
value: Optional[str] = None,
limit: Optional[int] = None,
):
"""
Update a block given the ID with the provided fields
Args:
block_id (str): ID of the block
label (str): Label to assign to the block
value (str): Value to assign to the block
limit (int): Token limit to assign to the block
Returns:
block (Block): Updated block
"""
data = {}
if value:
data["value"] = value
if limit:
data["limit"] = limit
if label:
data["label"] = label
return self.server.block_manager.update_block(block_id, actor=self.user, block_update=BlockUpdate(**data))
def attach_block(self, agent_id: str, block_id: str) -> AgentState:
"""
Attach a block to an agent.
Args:
agent_id (str): ID of the agent
block_id (str): ID of the block to attach
"""
return self.server.agent_manager.attach_block(agent_id=agent_id, block_id=block_id, actor=self.user)
def detach_block(self, agent_id: str, block_id: str) -> AgentState:
"""
Detach a block from an agent.
Args:
agent_id (str): ID of the agent
block_id (str): ID of the block to detach
"""
return self.server.agent_manager.detach_block(agent_id=agent_id, block_id=block_id, actor=self.user)
def get_run_messages(
self,
run_id: str,
before: Optional[str] = None,
after: Optional[str] = None,
limit: Optional[int] = 100,
ascending: bool = True,
role: Optional[MessageRole] = None,
) -> List[LettaMessageUnion]:
"""
Get messages associated with a job with filtering options.
Args:
run_id: ID of the run
before: Cursor for pagination
after: Cursor for pagination
limit: Maximum number of messages to return
ascending: Sort order by creation time
role: Filter by message role (user/assistant/system/tool)
Returns:
List of messages matching the filter criteria
"""
params = {
"before": before,
"after": after,
"limit": limit,
"ascending": ascending,
"role": role,
}
return self.server.job_manager.get_run_messages(run_id=run_id, actor=self.user, **params)
def get_run_usage(
self,
run_id: str,
) -> List[UsageStatistics]:
"""
Get usage statistics associated with a job.
Args:
run_id (str): ID of the run
Returns:
List[UsageStatistics]: List of usage statistics associated with the run
"""
usage = self.server.job_manager.get_job_usage(job_id=run_id, actor=self.user)
return [
UsageStatistics(completion_tokens=stat.completion_tokens, prompt_tokens=stat.prompt_tokens, total_tokens=stat.total_tokens)
for stat in usage
]
def get_run(self, run_id: str) -> Run:
"""
Get a run by ID.
Args:
run_id (str): ID of the run
Returns:
run (Run): Run
"""
return self.server.job_manager.get_job_by_id(job_id=run_id, actor=self.user)
def delete_run(self, run_id: str) -> None:
"""
Delete a run by ID.
Args:
run_id (str): ID of the run
"""
return self.server.job_manager.delete_job_by_id(job_id=run_id, actor=self.user)
def list_runs(self) -> List[Run]:
"""
List all runs.
Returns:
runs (List[Run]): List of runs
"""
return self.server.job_manager.list_jobs(actor=self.user, job_type=JobType.RUN)
def list_active_runs(self) -> List[Run]:
"""
List all active runs.
Returns:
runs (List[Run]): List of active runs
"""
return self.server.job_manager.list_jobs(actor=self.user, job_type=JobType.RUN, statuses=[JobStatus.created, JobStatus.running])
def get_tags(
self,
after: Optional[str] = None,
limit: Optional[int] = None,
query_text: Optional[str] = None,
) -> List[str]:
"""
Get all tags.
Returns:
tags (List[str]): List of tags
"""
return self.server.agent_manager.list_tags(actor=self.user, after=after, limit=limit, query_text=query_text)
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