import logging import time from typing import Callable, Dict, Generator, List, Optional, Union import requests import letta.utils from letta.constants import BASE_TOOLS, DEFAULT_HUMAN, DEFAULT_PERSONA from letta.data_sources.connectors import DataConnector from letta.functions.functions import parse_source_code from letta.memory import get_memory_functions from letta.schemas.agent import AgentState, AgentType, CreateAgent, UpdateAgentState from letta.schemas.block import ( Block, CreateBlock, CreateHuman, CreatePersona, Human, Persona, UpdateBlock, UpdateHuman, UpdatePersona, ) from letta.schemas.embedding_config import EmbeddingConfig # new schemas from letta.schemas.enums import JobStatus, MessageRole from letta.schemas.file import FileMetadata from letta.schemas.job import Job from letta.schemas.letta_request import LettaRequest 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, UpdateMessage from letta.schemas.openai.chat_completions import ToolCall from letta.schemas.passage import Passage from letta.schemas.source import Source, SourceCreate, SourceUpdate from letta.schemas.tool import Tool, ToolCreate, ToolUpdate from letta.server.rest_api.interface import QueuingInterface from letta.server.server import SyncServer from letta.utils import get_human_text, get_persona_text 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, auto_save: bool = False, debug: bool = False, ): self.auto_save = auto_save 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: Memory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_persona_text(DEFAULT_PERSONA)), system: Optional[str] = None, tools: Optional[List[str]] = None, include_base_tools: Optional[bool] = True, metadata: Optional[Dict] = {"human:": DEFAULT_HUMAN, "persona": DEFAULT_PERSONA}, description: Optional[str] = None, ) -> AgentState: raise NotImplementedError def update_agent( self, agent_id: str, name: Optional[str] = None, description: Optional[str] = None, system: Optional[str] = None, tools: 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, ): raise NotImplementedError def get_tools_from_agent(self, agent_id: str): raise NotImplementedError def add_tool_to_agent(self, agent_id: str, tool_id: str): raise NotImplementedError def remove_tool_from_agent(self, agent_id: str, tool_id: str): raise NotImplementedError def rename_agent(self, agent_id: str, new_name: str): raise NotImplementedError def delete_agent(self, agent_id: str): 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, include_full_message: Optional[bool] = False, ) -> LettaResponse: raise NotImplementedError def user_message(self, agent_id: str, message: str, include_full_message: Optional[bool] = False) -> 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 create_tool( self, func, name: Optional[str] = None, update: Optional[bool] = True, tags: Optional[List[str]] = None, ) -> Tool: raise NotImplementedError def update_tool( self, id: str, name: Optional[str] = None, func: Optional[Callable] = None, tags: Optional[List[str]] = None, ) -> Tool: raise NotImplementedError def list_tools(self, cursor: 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 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) -> 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_to_agent(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None): raise NotImplementedError def detach_source_from_agent(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None): 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, cursor: 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, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000 ) -> List[Passage]: raise NotImplementedError def get_messages( self, agent_id: str, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000 ) -> List[Message]: raise NotImplementedError def list_models(self) -> List[LLMConfig]: raise NotImplementedError def list_embedding_models(self) -> List[EmbeddingConfig]: 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: str, api_prefix: str = "v1", debug: bool = False, default_llm_config: Optional[LLMConfig] = None, default_embedding_config: Optional[EmbeddingConfig] = None, ): """ Initializes a new instance of Client class. Args: auto_save (bool): Whether to automatically save changes. user_id (str): The user ID. debug (bool): Whether to print debug information. default """ super().__init__(debug=debug) self.base_url = base_url self.api_prefix = api_prefix self.headers = {"accept": "application/json", "authorization": f"Bearer {token}"} self._default_llm_config = default_llm_config self._default_embedding_config = default_embedding_config def list_agents(self) -> List[AgentState]: response = requests.get(f"{self.base_url}/{self.api_prefix}/agents", headers=self.headers) 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)), # system system: Optional[str] = None, # tools tools: Optional[List[str]] = None, include_base_tools: Optional[bool] = True, # metadata metadata: Optional[Dict] = {"human:": DEFAULT_HUMAN, "persona": DEFAULT_PERSONA}, description: Optional[str] = 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 tools (List[str]): List of tools include_base_tools (bool): Include base tools metadata (Dict): Metadata description (str): Description Returns: agent_state (AgentState): State of the created agent """ # TODO: implement this check once name lookup works # if name: # exist_agent_id = self.get_agent_id(agent_name=name) # raise ValueError(f"Agent with name {name} already exists") # construct list of tools tool_names = [] if tools: tool_names += tools if include_base_tools: tool_names += BASE_TOOLS # add memory tools memory_functions = get_memory_functions(memory) for func_name, func in memory_functions.items(): tool = self.create_tool(func, name=func_name, tags=["memory", "letta-base"], update=True) tool_names.append(tool.name) # 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" # create agent request = CreateAgent( name=name, description=description, metadata_=metadata, memory=memory, tools=tool_names, 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, ) response = requests.post(f"{self.base_url}/{self.api_prefix}/agents", json=request.model_dump(), headers=self.headers) if response.status_code != 200: raise ValueError(f"Status {response.status_code} - Failed to create agent: {response.text}") return AgentState(**response.json()) def update_message( self, agent_id: str, message_id: str, role: Optional[MessageRole] = None, text: Optional[str] = None, name: Optional[str] = None, tool_calls: Optional[List[ToolCall]] = None, tool_call_id: Optional[str] = None, ) -> Message: request = UpdateMessage( id=message_id, role=role, text=text, name=name, tool_calls=tool_calls, tool_call_id=tool_call_id, ) response = requests.patch( f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages/{message_id}", json=request.model_dump(), headers=self.headers ) if response.status_code != 200: raise ValueError(f"Failed to update message: {response.text}") return Message(**response.json()) def update_agent( self, agent_id: str, name: Optional[str] = None, description: Optional[str] = None, system: Optional[str] = None, tools: 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, ): """ 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 memory (Memory): Memory configuration Returns: agent_state (AgentState): State of the updated agent """ request = UpdateAgentState( id=agent_id, name=name, system=system, tools=tools, description=description, metadata_=metadata, llm_config=llm_config, embedding_config=embedding_config, message_ids=message_ids, memory=memory, ) 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 add_tool_to_agent(self, agent_id: str, tool_id: str): """ 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}/add-tool/{tool_id}", headers=self.headers) if response.status_code != 200: raise ValueError(f"Failed to update agent: {response.text}") return AgentState(**response.json()) def remove_tool_from_agent(self, agent_id: str, tool_id: str): """ 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}/remove-tool/{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): """ Rename an agent Args: agent_id (str): ID of the agent new_name (str): New name for the agent """ return self.update_agent(agent_id, name=new_name) def delete_agent(self, agent_id: str): """ 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 raise NotImplementedError # 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}/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}/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}/memory/archival", headers=self.headers) if response.status_code != 200: raise ValueError(f"Failed to get archival memory summary: {response.text}") return ArchivalMemorySummary(**response.json()) 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}/memory/recall", headers=self.headers) if response.status_code != 200: raise ValueError(f"Failed to get recall memory summary: {response.text}") return RecallMemorySummary(**response.json()) 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}/memory/messages", headers=self.headers) if response.status_code != 200: raise ValueError(f"Failed to get in-context messages: {response.text}") return [Message(**message) for message in response.json()] # agent interactions def user_message(self, agent_id: str, message: str, include_full_message: Optional[bool] = False) -> 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, message, role="user", include_full_message=include_full_message) 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", 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", 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_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[Message]: """ 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 [Message(**message) for message in response.json()] def send_message( self, agent_id: str, message: str, role: str, name: Optional[str] = None, stream_steps: bool = False, stream_tokens: bool = False, include_full_message: Optional[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), text=message, name=name)] # TODO: figure out how to handle stream_steps and stream_tokens # When streaming steps is True, stream_tokens must be False request = LettaRequest(messages=messages, stream_steps=stream_steps, stream_tokens=stream_tokens, return_message_object=True) if stream_tokens or stream_steps: from letta.client.streaming import _sse_post request.return_message_object = False return _sse_post(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages", request.model_dump(), self.headers) else: 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_message() response.messages = messages 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, name: str, text: str) -> Block: # request = CreateBlock(label=label, name=name, value=text) 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) -> Block: request = UpdateBlock(id=block_id, name=name, value=text) 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) -> 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 text (str): Text of the human block Returns: human (Human): Human block """ return self.create_block(label="human", name=name, text=text) 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, 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", name=name, text=text) 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, 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): """ 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) -> Source: """ Create a source Args: name (str): Name of the source Returns: source (Source): Created source """ payload = {"name": name} 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, cursor: 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 cursor (Optional[str]): Pagination cursor for fetching the next page Returns: List[FileMetadata]: List of files """ # Prepare query parameters for pagination params = {"limit": limit, "cursor": cursor} # 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(id=source_id, 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_to_agent(self, source_id: str, agent_id: str): """ 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.post(f"{self.base_url}/{self.api_prefix}/sources/{source_id}/attach", params=params, headers=self.headers) assert response.status_code == 200, f"Failed to attach source to agent: {response.text}" def detach_source(self, source_id: str, agent_id: str): """Detach a source from an agent""" params = {"agent_id": str(agent_id)} response = requests.post(f"{self.base_url}/{self.api_prefix}/sources/{source_id}/detach", params=params, headers=self.headers) assert response.status_code == 200, f"Failed to detach source from agent: {response.text}" return Source(**response.json()) # server configuration commands def list_models(self): """ List available LLM models Returns: models (List[LLMConfig]): List of LLM models """ 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 models: {response.text}") return [LLMConfig(**model) for model in response.json()] def list_embedding_models(self): """ List available embedding models Returns: models (List[EmbeddingConfig]): List of embedding models """ 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 models: {response.text}") return [EmbeddingConfig(**model) for model in 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/name/{tool_name}", 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 response.json() def create_tool( self, func: Callable, name: Optional[str] = None, update: Optional[bool] = True, # TODO: actually use this tags: Optional[List[str]] = None, ) -> 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. update (bool, optional): Update the tool if it already exists. Defaults to True. Returns: tool (Tool): The created tool. """ # TODO: check tool update code # TODO: check if tool already exists # TODO: how to load modules? # parse source code/schema source_code = parse_source_code(func) source_type = "python" # TODO: Check if tool already exists # if name: # tool_id = self.get_tool_id(tool_name=name) # if tool_id: # raise ValueError(f"Tool with name {name} (id={tool_id}) already exists") # call server function request = ToolCreate(source_type=source_type, source_code=source_code, name=name, 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 update_tool( self, id: str, name: Optional[str] = None, func: Optional[Callable] = None, tags: Optional[List[str]] = None, ) -> 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 Returns: tool (Tool): Updated tool """ if func: source_code = parse_source_code(func) else: source_code = None source_type = "python" request = ToolUpdate(id=id, source_type=source_type, source_code=source_code, tags=tags, name=name) 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 create_tool( # self, # func, # name: Optional[str] = None, # update: Optional[bool] = True, # TODO: actually use this # tags: Optional[List[str]] = None, # ): # """Create a tool # Args: # func (callable): The function to create a tool for. # tags (Optional[List[str]], optional): Tags for the tool. Defaults to None. # update (bool, optional): Update the tool if it already exists. Defaults to True. # Returns: # Tool object # """ # # TODO: check if tool already exists # # TODO: how to load modules? # # parse source code/schema # source_code = parse_source_code(func) # json_schema = generate_schema(func, name) # source_type = "python" # json_schema["name"] # # create data # data = {"source_code": source_code, "source_type": source_type, "tags": tags, "json_schema": json_schema, "update": update} # try: # CreateToolRequest(**data) # validate data # except Exception as e: # raise ValueError(f"Failed to create tool: {e}, invalid input {data}") # # make REST request # response = requests.post(f"{self.base_url}/{self.api_prefix}/tools", json=data, headers=self.headers) # if response.status_code != 200: # raise ValueError(f"Failed to create tool: {response.text}") # return ToolModel(**response.json()) def list_tools(self, cursor: Optional[str] = None, limit: Optional[int] = 50) -> List[Tool]: """ List available tools for the user. Returns: tools (List[Tool]): List of tools """ params = {} if cursor: params["cursor"] = str(cursor) 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 get_tool_id(self, name: str) -> Optional[str]: """ Get a tool ID by its name. Args: id (str): ID of the tool Returns: tool (Tool): Tool """ response = requests.get(f"{self.base_url}/{self.api_prefix}/tools/name/{name}", 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 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()] class LocalClient(AbstractClient): """ A local client for Letta, which corresponds to a single user. Attributes: auto_save (bool): Whether to automatically save changes. 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, auto_save: bool = False, user_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: auto_save (bool): Whether to automatically save changes. user_id (str): The user ID. debug (bool): Whether to print debug information. """ self.auto_save = auto_save # 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 user_id that `LocalClient` is associated with if user_id: self.user_id = user_id else: # get default user self.user_id = self.server.get_default_user().id # agents def list_agents(self) -> List[AgentState]: self.interface.clear() # TODO: fix the server function # return self.server.list_agents(user_id=self.user_id) return self.server.ms.list_agents(user_id=self.user_id) 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)), # system system: Optional[str] = None, # tools tools: Optional[List[str]] = None, include_base_tools: Optional[bool] = True, # metadata metadata: Optional[Dict] = {"human:": DEFAULT_HUMAN, "persona": DEFAULT_PERSONA}, description: Optional[str] = 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 tools (List[str]): List of tools include_base_tools (bool): Include base tools metadata (Dict): Metadata description (str): Description Returns: agent_state (AgentState): State of the created agent """ if name and self.agent_exists(agent_name=name): raise ValueError(f"Agent with name {name} already exists (user_id={self.user_id})") # construct list of tools tool_names = [] if tools: tool_names += tools if include_base_tools: tool_names += BASE_TOOLS # add memory tools memory_functions = get_memory_functions(memory) for func_name, func in memory_functions.items(): tool = self.create_tool(func, name=func_name, tags=["memory", "letta-base"], update=True) tool_names.append(tool.name) self.interface.clear() # 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" # create agent agent_state = self.server.create_agent( CreateAgent( name=name, description=description, metadata_=metadata, memory=memory, tools=tool_names, 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, ), user_id=self.user_id, ) return agent_state def update_message( self, agent_id: str, message_id: str, role: Optional[MessageRole] = None, text: Optional[str] = None, name: Optional[str] = None, tool_calls: Optional[List[ToolCall]] = None, tool_call_id: Optional[str] = None, ) -> Message: message = self.server.update_agent_message( agent_id=agent_id, request=UpdateMessage( id=message_id, role=role, text=text, name=name, tool_calls=tool_calls, tool_call_id=tool_call_id, ), ) return message def update_agent( self, agent_id: str, name: Optional[str] = None, description: Optional[str] = None, system: Optional[str] = None, tools: 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, ): """ 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 memory (Memory): Memory configuration Returns: agent_state (AgentState): State of the updated agent """ self.interface.clear() agent_state = self.server.update_agent( UpdateAgentState( id=agent_id, name=name, system=system, tools=tools, description=description, metadata_=metadata, llm_config=llm_config, embedding_config=embedding_config, message_ids=message_ids, memory=memory, ), user_id=self.user_id, ) 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.get_tools_from_agent(agent_id=agent_id, user_id=self.user_id) def add_tool_to_agent(self, agent_id: str, tool_id: str): """ 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.add_tool_to_agent(agent_id=agent_id, tool_id=tool_id, user_id=self.user_id) return agent_state def remove_tool_from_agent(self, agent_id: str, tool_id: str): """ 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.remove_tool_from_agent(agent_id=agent_id, tool_id=tool_id, user_id=self.user_id) return agent_state def rename_agent(self, agent_id: str, new_name: str): """ Rename an agent Args: agent_id (str): ID of the agent new_name (str): New name for the agent """ self.update_agent(agent_id, name=new_name) def delete_agent(self, agent_id: str): """ Delete an agent Args: agent_id (str): ID of the agent to delete """ self.server.delete_agent(user_id=self.user_id, agent_id=agent_id) def get_agent_by_name(self, agent_name: str, user_id: 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.get_agent(agent_name=agent_name, user_id=user_id, agent_id=None) 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 """ # TODO: include agent_name self.interface.clear() return self.server.get_agent_state(user_id=self.user_id, agent_id=agent_id) 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" return self.server.get_agent_id(name=agent_name, user_id=self.user_id) # 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) 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(user_id=self.user_id, agent_id=agent_id, new_memory_contents={section: value}) 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) 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) 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.get_in_context_messages(agent_id=agent_id) # agent interactions def send_messages( self, agent_id: str, messages: List[Union[Message | MessageCreate]], include_full_message: Optional[bool] = False, ): """ 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(user_id=self.user_id, agent_id=agent_id, messages=messages) # auto-save if self.auto_save: self.save() # format messages messages = self.interface.to_list() if include_full_message: letta_messages = messages else: letta_messages = [] for m in messages: letta_messages += m.to_letta_message() return LettaResponse(messages=letta_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, include_full_message: Optional[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( user_id=self.user_id, agent_id=agent_id, messages=[MessageCreate(role=MessageRole(role), text=message, name=name)], ) # auto-save if self.auto_save: self.save() ## 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_message() # return LettaResponse(messages=letta_messages, usage=usage) # format messages messages = self.interface.to_list() if include_full_message: letta_messages = messages else: letta_messages = [] for m in messages: letta_messages += m.to_letta_message() return LettaResponse(messages=letta_messages, usage=usage) def user_message(self, agent_id: str, message: str, include_full_message: Optional[bool] = False) -> 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, include_full_message=include_full_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) # auto-save if self.auto_save: self.save() # NOTE: messages/usage may be empty, depending on the command return LettaResponse(messages=self.interface.to_list(), usage=usage) def save(self): self.server.save_agents() # archival memory # humans / personas def get_block_id(self, name: str, label: str) -> str: block = self.server.get_blocks(name=name, label=label, user_id=self.user_id, template=True) if not block: return None return block[0].id 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.create_block(CreateHuman(name=name, value=text, user_id=self.user_id), user_id=self.user_id) 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.create_block(CreatePersona(name=name, value=text, user_id=self.user_id), user_id=self.user_id) def list_humans(self): """ List available human block templates Returns: humans (List[Human]): List of human blocks """ return self.server.get_blocks(label="human", user_id=self.user_id, template=True) def list_personas(self) -> List[Persona]: """ List available persona block templates Returns: personas (List[Persona]): List of persona blocks """ return self.server.get_blocks(label="persona", user_id=self.user_id, template=True) 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.update_block(UpdateHuman(id=human_id, value=text, user_id=self.user_id, template=True)) 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.update_block(UpdatePersona(id=persona_id, value=text, user_id=self.user_id, template=True)) 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.get_block(id).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.get_block(id).model_dump()) 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 """ persona = self.server.get_blocks(name=name, label="persona", user_id=self.user_id, template=True) if not persona: return None return persona[0].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 """ human = self.server.get_blocks(name=name, label="human", user_id=self.user_id, template=True) if not human: return None return human[0].id def delete_persona(self, id: str): """ Delete a persona block template Args: id (str): ID of the persona block """ self.server.delete_block(id) def delete_human(self, id: str): """ Delete a human block template Args: id (str): ID of the human block """ self.server.delete_block(id) # tools # TODO: merge this into create_tool def add_tool(self, tool: Tool, update: Optional[bool] = True) -> Tool: """ Adds a tool directly. Args: tool (Tool): The tool to add. update (bool, optional): Update the tool if it already exists. Defaults to True. Returns: None """ if self.tool_with_name_and_user_id_exists(tool): if update: return self.server.update_tool( ToolUpdate( id=tool.id, description=tool.description, source_type=tool.source_type, source_code=tool.source_code, tags=tool.tags, json_schema=tool.json_schema, name=tool.name, ), self.user_id, ) else: raise ValueError(f"Tool with id={tool.id} and name={tool.name}already exists") else: # call server function return self.server.create_tool( ToolCreate( id=tool.id, description=tool.description, source_type=tool.source_type, source_code=tool.source_code, name=tool.name, json_schema=tool.json_schema, tags=tool.tags, ), user_id=self.user_id, update=update, ) # TODO: Use the above function `add_tool` here as there is duplicate logic def create_tool( self, func, name: Optional[str] = None, update: Optional[bool] = True, # TODO: actually use this tags: Optional[List[str]] = None, terminal: Optional[bool] = False, ) -> 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. update (bool, optional): Update the tool if it already exists. Defaults to True. terminal (bool, optional): Whether the tool is a terminal tool (no more agent steps). Defaults to False. 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" if not tags: tags = [] # call server function return self.server.create_tool( # ToolCreate(source_type=source_type, source_code=source_code, name=tool_name, json_schema=json_schema, tags=tags), ToolCreate(source_type=source_type, source_code=source_code, name=name, tags=tags, terminal=terminal), user_id=self.user_id, update=update, ) def update_tool( self, id: str, name: Optional[str] = None, func: Optional[callable] = None, tags: Optional[List[str]] = None, ) -> 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 Returns: tool (Tool): Updated tool """ if func: source_code = parse_source_code(func) else: source_code = None source_type = "python" return self.server.update_tool( ToolUpdate(id=id, source_type=source_type, source_code=source_code, tags=tags, name=name), self.user_id ) def list_tools(self, cursor: Optional[str] = None, limit: Optional[int] = 50) -> List[Tool]: """ List available tools for the user. Returns: tools (List[Tool]): List of tools """ return self.server.list_tools(cursor=cursor, limit=limit, user_id=self.user_id) 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 """ return self.server.get_tool(id) def delete_tool(self, id: str): """ Delete a tool given the ID. Args: id (str): ID of the tool """ return self.server.delete_tool(id) def get_tool_id(self, name: str) -> Optional[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) """ return self.server.get_tool_id(name, self.user_id) def tool_with_name_and_user_id_exists(self, tool: Tool) -> bool: """ Check if the tool with name and user_id exists Args: tool (Tool): the tool Returns: (bool): True if the id exists, False otherwise. """ return self.server.tool_with_name_and_user_id_exists(tool, self.user_id) 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 """ metadata_ = {"type": "embedding", "filename": filename, "source_id": source_id} job = self.server.create_job(user_id=self.user_id, metadata=metadata_) # TODO: implement blocking vs. non-blocking self.server.load_file_to_source(source_id=source_id, file_path=filename, job_id=job.id) return job def delete_file_from_source(self, source_id: str, file_id: str): self.server.delete_file_from_source(source_id, file_id, user_id=self.user_id) def get_job(self, job_id: str): return self.server.get_job(job_id=job_id) def delete_job(self, job_id: str): return self.server.delete_job(job_id) def list_jobs(self): return self.server.list_jobs(user_id=self.user_id) def list_active_jobs(self): return self.server.list_active_jobs(user_id=self.user_id) def create_source(self, name: str) -> Source: """ Create a source Args: name (str): Name of the source Returns: source (Source): Created source """ request = SourceCreate(name=name) return self.server.create_source(request=request, user_id=self.user_id) 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, user_id=self.user_id) 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.get_source(source_id=source_id, user_id=self.user_id) 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.get_source_id(source_name=source_name, user_id=self.user_id) def attach_source_to_agent(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None): """ 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 """ self.server.attach_source_to_agent(source_id=source_id, source_name=source_name, agent_id=agent_id, user_id=self.user_id) def detach_source_from_agent(self, agent_id: str, source_id: Optional[str] = None, source_name: Optional[str] = None): """ 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 """ return self.server.detach_source_from_agent(source_id=source_id, source_name=source_name, agent_id=agent_id, user_id=self.user_id) def list_sources(self) -> List[Source]: """ List available sources Returns: sources (List[Source]): List of sources """ return self.server.list_all_sources(user_id=self.user_id) 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.list_attached_sources(agent_id=agent_id) def list_files_from_source(self, source_id: str, limit: int = 1000, cursor: Optional[str] = None) -> List[FileMetadata]: """ List files from source. Args: source_id (str): ID of the source limit (int): The # of items to return cursor (str): The cursor for fetching the next page Returns: files (List[FileMetadata]): List of files """ return self.server.list_files_from_source(source_id=source_id, limit=limit, cursor=cursor) 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(id=source_id, name=name) return self.server.update_source(request=request, user_id=self.user_id) # 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(user_id=self.user_id, agent_id=agent_id, memory_contents=memory) 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(user_id=self.user_id, agent_id=agent_id, memory_id=memory_id) 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_cursor(user_id=self.user_id, agent_id=agent_id, before=before, after=after, limit=limit) # recall memory def get_messages( self, agent_id: str, before: Optional[str] = None, after: Optional[str] = None, limit: Optional[int] = 1000 ) -> List[Message]: """ 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_cursor( user_id=self.user_id, agent_id=agent_id, before=before, after=after, limit=limit, reverse=True, return_message_object=True, ) def list_models(self) -> List[LLMConfig]: """ List available LLM models Returns: models (List[LLMConfig]): List of LLM models """ return self.server.list_models() def list_embedding_models(self) -> List[EmbeddingConfig]: """ List available embedding models Returns: models (List[EmbeddingConfig]): List of embedding models """ return [self.server.server_embedding_config] 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 self.server.get_blocks(label=label, template=templates_only) def create_block(self, name: str, text: str, label: Optional[str] = None) -> Block: # """ Create a block Args: label (str): Label of the block name (str): Name of the block text (str): Text of the block Returns: block (Block): Created block """ return self.server.create_block(CreateBlock(label=label, name=name, value=text, user_id=self.user_id), user_id=self.user_id) def update_block(self, block_id: str, name: Optional[str] = None, text: Optional[str] = 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.update_block(UpdateBlock(id=block_id, name=name, value=text)) 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.get_block(block_id) 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.delete_block(id) 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() 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()