from datetime import datetime from typing import Dict, List, Optional import numpy as np from sqlalchemy import Select, func, literal, select, union_all from letta.constants import BASE_MEMORY_TOOLS, BASE_TOOLS, MAX_EMBEDDING_DIM from letta.embeddings import embedding_model from letta.log import get_logger from letta.orm import Agent as AgentModel from letta.orm import AgentPassage from letta.orm import Block as BlockModel from letta.orm import Source as SourceModel from letta.orm import SourcePassage, SourcesAgents from letta.orm import Tool as ToolModel from letta.orm.errors import NoResultFound from letta.orm.sqlite_functions import adapt_array from letta.schemas.agent import AgentState as PydanticAgentState from letta.schemas.agent import AgentType, CreateAgent, UpdateAgent from letta.schemas.block import Block as PydanticBlock from letta.schemas.embedding_config import EmbeddingConfig from letta.schemas.llm_config import LLMConfig from letta.schemas.message import Message as PydanticMessage from letta.schemas.passage import Passage as PydanticPassage from letta.schemas.source import Source as PydanticSource from letta.schemas.tool_rule import ToolRule as PydanticToolRule from letta.schemas.user import User as PydanticUser from letta.services.block_manager import BlockManager from letta.services.helpers.agent_manager_helper import ( _process_relationship, _process_tags, check_supports_structured_output, compile_system_message, derive_system_message, initialize_message_sequence, package_initial_message_sequence, ) from letta.services.message_manager import MessageManager from letta.services.source_manager import SourceManager from letta.services.tool_manager import ToolManager from letta.settings import settings from letta.utils import enforce_types, get_utc_time, united_diff logger = get_logger(__name__) # Agent Manager Class class AgentManager: """Manager class to handle business logic related to Agents.""" def __init__(self): from letta.server.server import db_context self.session_maker = db_context self.block_manager = BlockManager() self.tool_manager = ToolManager() self.source_manager = SourceManager() self.message_manager = MessageManager() # ====================================================================================================================== # Basic CRUD operations # ====================================================================================================================== @enforce_types def create_agent( self, agent_create: CreateAgent, actor: PydanticUser, ) -> PydanticAgentState: system = derive_system_message(agent_type=agent_create.agent_type, system=agent_create.system) if not agent_create.llm_config or not agent_create.embedding_config: raise ValueError("llm_config and embedding_config are required") # Check tool rules are valid if agent_create.tool_rules: check_supports_structured_output(model=agent_create.llm_config.model, tool_rules=agent_create.tool_rules) # create blocks (note: cannot be linked into the agent_id is created) block_ids = list(agent_create.block_ids or []) # Create a local copy to avoid modifying the original for create_block in agent_create.memory_blocks: block = self.block_manager.create_or_update_block(PydanticBlock(**create_block.model_dump()), actor=actor) block_ids.append(block.id) # TODO: Remove this block once we deprecate the legacy `tools` field # create passed in `tools` tool_names = [] if agent_create.include_base_tools: tool_names.extend(BASE_TOOLS + BASE_MEMORY_TOOLS) if agent_create.tools: tool_names.extend(agent_create.tools) # Remove duplicates tool_names = list(set(tool_names)) tool_ids = agent_create.tool_ids or [] for tool_name in tool_names: tool = self.tool_manager.get_tool_by_name(tool_name=tool_name, actor=actor) if tool: tool_ids.append(tool.id) # Remove duplicates tool_ids = list(set(tool_ids)) # Create the agent agent_state = self._create_agent( name=agent_create.name, system=system, agent_type=agent_create.agent_type, llm_config=agent_create.llm_config, embedding_config=agent_create.embedding_config, block_ids=block_ids, tool_ids=tool_ids, source_ids=agent_create.source_ids or [], tags=agent_create.tags or [], description=agent_create.description, metadata_=agent_create.metadata_, tool_rules=agent_create.tool_rules, actor=actor, ) # TODO: See if we can merge this into the above SQL create call for performance reasons # Generate a sequence of initial messages to put in the buffer init_messages = initialize_message_sequence( agent_state=agent_state, memory_edit_timestamp=get_utc_time(), include_initial_boot_message=True ) if agent_create.initial_message_sequence is not None: # We always need the system prompt up front system_message_obj = PydanticMessage.dict_to_message( agent_id=agent_state.id, user_id=agent_state.created_by_id, model=agent_state.llm_config.model, openai_message_dict=init_messages[0], ) # Don't use anything else in the pregen sequence, instead use the provided sequence init_messages = [system_message_obj] init_messages.extend( package_initial_message_sequence(agent_state.id, agent_create.initial_message_sequence, agent_state.llm_config.model, actor) ) else: init_messages = [ PydanticMessage.dict_to_message( agent_id=agent_state.id, user_id=agent_state.created_by_id, model=agent_state.llm_config.model, openai_message_dict=msg ) for msg in init_messages ] return self.append_to_in_context_messages(init_messages, agent_id=agent_state.id, actor=actor) @enforce_types def _create_agent( self, actor: PydanticUser, name: str, system: str, agent_type: AgentType, llm_config: LLMConfig, embedding_config: EmbeddingConfig, block_ids: List[str], tool_ids: List[str], source_ids: List[str], tags: List[str], description: Optional[str] = None, metadata_: Optional[Dict] = None, tool_rules: Optional[List[PydanticToolRule]] = None, ) -> PydanticAgentState: """Create a new agent.""" with self.session_maker() as session: # Prepare the agent data data = { "name": name, "system": system, "agent_type": agent_type, "llm_config": llm_config, "embedding_config": embedding_config, "organization_id": actor.organization_id, "description": description, "metadata_": metadata_, "tool_rules": tool_rules, } # Create the new agent using SqlalchemyBase.create new_agent = AgentModel(**data) _process_relationship(session, new_agent, "tools", ToolModel, tool_ids, replace=True) _process_relationship(session, new_agent, "sources", SourceModel, source_ids, replace=True) _process_relationship(session, new_agent, "core_memory", BlockModel, block_ids, replace=True) _process_tags(new_agent, tags, replace=True) new_agent.create(session, actor=actor) # Convert to PydanticAgentState and return return new_agent.to_pydantic() @enforce_types def update_agent(self, agent_id: str, agent_update: UpdateAgent, actor: PydanticUser) -> PydanticAgentState: agent_state = self._update_agent(agent_id=agent_id, agent_update=agent_update, actor=actor) # Rebuild the system prompt if it's different if agent_update.system and agent_update.system != agent_state.system: agent_state = self.rebuild_system_prompt(agent_id=agent_state.id, actor=actor, force=True, update_timestamp=False) return agent_state @enforce_types def _update_agent(self, agent_id: str, agent_update: UpdateAgent, actor: PydanticUser) -> PydanticAgentState: """ Update an existing agent. Args: agent_id: The ID of the agent to update. agent_update: UpdateAgent object containing the updated fields. actor: User performing the action. Returns: PydanticAgentState: The updated agent as a Pydantic model. """ with self.session_maker() as session: # Retrieve the existing agent agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) # Update scalar fields directly scalar_fields = {"name", "system", "llm_config", "embedding_config", "message_ids", "tool_rules", "description", "metadata_"} for field in scalar_fields: value = getattr(agent_update, field, None) if value is not None: setattr(agent, field, value) # Update relationships using _process_relationship and _process_tags if agent_update.tool_ids is not None: _process_relationship(session, agent, "tools", ToolModel, agent_update.tool_ids, replace=True) if agent_update.source_ids is not None: _process_relationship(session, agent, "sources", SourceModel, agent_update.source_ids, replace=True) if agent_update.block_ids is not None: _process_relationship(session, agent, "core_memory", BlockModel, agent_update.block_ids, replace=True) if agent_update.tags is not None: _process_tags(agent, agent_update.tags, replace=True) # Commit and refresh the agent agent.update(session, actor=actor) # Convert to PydanticAgentState and return return agent.to_pydantic() @enforce_types def list_agents( self, actor: PydanticUser, tags: Optional[List[str]] = None, match_all_tags: bool = False, cursor: Optional[str] = None, limit: Optional[int] = 50, **kwargs, ) -> List[PydanticAgentState]: """ List agents that have the specified tags. """ with self.session_maker() as session: agents = AgentModel.list( db_session=session, tags=tags, match_all_tags=match_all_tags, cursor=cursor, limit=limit, organization_id=actor.organization_id if actor else None, **kwargs, ) return [agent.to_pydantic() for agent in agents] @enforce_types def get_agent_by_id(self, agent_id: str, actor: PydanticUser) -> PydanticAgentState: """Fetch an agent by its ID.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) return agent.to_pydantic() @enforce_types def get_agent_by_name(self, agent_name: str, actor: PydanticUser) -> PydanticAgentState: """Fetch an agent by its ID.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, name=agent_name, actor=actor) return agent.to_pydantic() @enforce_types def delete_agent(self, agent_id: str, actor: PydanticUser) -> None: """ Deletes an agent and its associated relationships. Ensures proper permission checks and cascades where applicable. Args: agent_id: ID of the agent to be deleted. actor: User performing the action. Raises: NoResultFound: If agent doesn't exist """ with self.session_maker() as session: # Retrieve the agent agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) agent.hard_delete(session) # ====================================================================================================================== # In Context Messages Management # ====================================================================================================================== # TODO: There are several assumptions here that are not explicitly checked # TODO: 1) These message ids are valid # TODO: 2) These messages are ordered from oldest to newest # TODO: This can be fixed by having an actual relationship in the ORM for message_ids # TODO: This can also be made more efficient, instead of getting, setting, we can do it all in one db session for one query. @enforce_types def get_in_context_messages(self, agent_id: str, actor: PydanticUser) -> List[PydanticMessage]: message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids return self.message_manager.get_messages_by_ids(message_ids=message_ids, actor=actor) @enforce_types def get_system_message(self, agent_id: str, actor: PydanticUser) -> PydanticMessage: message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids return self.message_manager.get_message_by_id(message_id=message_ids[0], actor=actor) @enforce_types def rebuild_system_prompt(self, agent_id: str, actor: PydanticUser, force=False, update_timestamp=True) -> PydanticAgentState: """Rebuilds the system message with the latest memory object and any shared memory block updates Updates to core memory blocks should trigger a "rebuild", which itself will create a new message object Updates to the memory header should *not* trigger a rebuild, since that will simply flood recall storage with excess messages """ agent_state = self.get_agent_by_id(agent_id=agent_id, actor=actor) curr_system_message = self.get_system_message( agent_id=agent_id, actor=actor ) # this is the system + memory bank, not just the system prompt curr_system_message_openai = curr_system_message.to_openai_dict() # note: we only update the system prompt if the core memory is changed # this means that the archival/recall memory statistics may be someout out of date curr_memory_str = agent_state.memory.compile() if curr_memory_str in curr_system_message_openai["content"] and not force: # NOTE: could this cause issues if a block is removed? (substring match would still work) logger.debug( f"Memory hasn't changed for agent id={agent_id} and actor=({actor.id}, {actor.name}), skipping system prompt rebuild" ) return agent_state # If the memory didn't update, we probably don't want to update the timestamp inside # For example, if we're doing a system prompt swap, this should probably be False if update_timestamp: memory_edit_timestamp = get_utc_time() else: # NOTE: a bit of a hack - we pull the timestamp from the message created_by memory_edit_timestamp = curr_system_message.created_at # update memory (TODO: potentially update recall/archival stats separately) new_system_message_str = compile_system_message( system_prompt=agent_state.system, in_context_memory=agent_state.memory, in_context_memory_last_edit=memory_edit_timestamp, ) diff = united_diff(curr_system_message_openai["content"], new_system_message_str) if len(diff) > 0: # there was a diff logger.info(f"Rebuilding system with new memory...\nDiff:\n{diff}") # Swap the system message out (only if there is a diff) message = PydanticMessage.dict_to_message( agent_id=agent_id, user_id=actor.id, model=agent_state.llm_config.model, openai_message_dict={"role": "system", "content": new_system_message_str}, ) message = self.message_manager.create_message(message, actor=actor) message_ids = [message.id] + agent_state.message_ids[1:] # swap index 0 (system) return self.set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor) else: return agent_state @enforce_types def set_in_context_messages(self, agent_id: str, message_ids: List[str], actor: PydanticUser) -> PydanticAgentState: return self.update_agent(agent_id=agent_id, agent_update=UpdateAgent(message_ids=message_ids), actor=actor) @enforce_types def trim_older_in_context_messages(self, num: int, agent_id: str, actor: PydanticUser) -> PydanticAgentState: message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids new_messages = [message_ids[0]] + message_ids[num:] # 0 is system message return self.set_in_context_messages(agent_id=agent_id, message_ids=new_messages, actor=actor) @enforce_types def prepend_to_in_context_messages(self, messages: List[PydanticMessage], agent_id: str, actor: PydanticUser) -> PydanticAgentState: message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids new_messages = self.message_manager.create_many_messages(messages, actor=actor) message_ids = [message_ids[0]] + [m.id for m in new_messages] + message_ids[1:] return self.set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor) @enforce_types def append_to_in_context_messages(self, messages: List[PydanticMessage], agent_id: str, actor: PydanticUser) -> PydanticAgentState: messages = self.message_manager.create_many_messages(messages, actor=actor) message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids or [] message_ids += [m.id for m in messages] return self.set_in_context_messages(agent_id=agent_id, message_ids=message_ids, actor=actor) # ====================================================================================================================== # Source Management # ====================================================================================================================== @enforce_types def attach_source(self, agent_id: str, source_id: str, actor: PydanticUser) -> None: """ Attaches a source to an agent. Args: agent_id: ID of the agent to attach the source to source_id: ID of the source to attach actor: User performing the action Raises: ValueError: If either agent or source doesn't exist IntegrityError: If the source is already attached to the agent """ with self.session_maker() as session: # Verify both agent and source exist and user has permission to access them agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) # The _process_relationship helper already handles duplicate checking via unique constraint _process_relationship( session=session, agent=agent, relationship_name="sources", model_class=SourceModel, item_ids=[source_id], allow_partial=False, replace=False, # Extend existing sources rather than replace ) # Commit the changes agent.update(session, actor=actor) @enforce_types def list_attached_sources(self, agent_id: str, actor: PydanticUser) -> List[PydanticSource]: """ Lists all sources attached to an agent. Args: agent_id: ID of the agent to list sources for actor: User performing the action Returns: List[str]: List of source IDs attached to the agent """ with self.session_maker() as session: # Verify agent exists and user has permission to access it agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) # Use the lazy-loaded relationship to get sources return [source.to_pydantic() for source in agent.sources] @enforce_types def detach_source(self, agent_id: str, source_id: str, actor: PydanticUser) -> None: """ Detaches a source from an agent. Args: agent_id: ID of the agent to detach the source from source_id: ID of the source to detach actor: User performing the action """ with self.session_maker() as session: # Verify agent exists and user has permission to access it agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) # Remove the source from the relationship agent.sources = [s for s in agent.sources if s.id != source_id] # Commit the changes agent.update(session, actor=actor) # ====================================================================================================================== # Block management # ====================================================================================================================== @enforce_types def get_block_with_label( self, agent_id: str, block_label: str, actor: PydanticUser, ) -> PydanticBlock: """Gets a block attached to an agent by its label.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) for block in agent.core_memory: if block.label == block_label: return block.to_pydantic() raise NoResultFound(f"No block with label '{block_label}' found for agent '{agent_id}'") @enforce_types def update_block_with_label( self, agent_id: str, block_label: str, new_block_id: str, actor: PydanticUser, ) -> PydanticAgentState: """Updates which block is assigned to a specific label for an agent.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) new_block = BlockModel.read(db_session=session, identifier=new_block_id, actor=actor) if new_block.label != block_label: raise ValueError(f"New block label '{new_block.label}' doesn't match required label '{block_label}'") # Remove old block with this label if it exists agent.core_memory = [b for b in agent.core_memory if b.label != block_label] # Add new block agent.core_memory.append(new_block) agent.update(session, actor=actor) return agent.to_pydantic() @enforce_types def attach_block(self, agent_id: str, block_id: str, actor: PydanticUser) -> PydanticAgentState: """Attaches a block to an agent.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) block = BlockModel.read(db_session=session, identifier=block_id, actor=actor) agent.core_memory.append(block) agent.update(session, actor=actor) return agent.to_pydantic() @enforce_types def detach_block( self, agent_id: str, block_id: str, actor: PydanticUser, ) -> PydanticAgentState: """Detaches a block from an agent.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) original_length = len(agent.core_memory) agent.core_memory = [b for b in agent.core_memory if b.id != block_id] if len(agent.core_memory) == original_length: raise NoResultFound(f"No block with id '{block_id}' found for agent '{agent_id}' with actor id: '{actor.id}'") agent.update(session, actor=actor) return agent.to_pydantic() @enforce_types def detach_block_with_label( self, agent_id: str, block_label: str, actor: PydanticUser, ) -> PydanticAgentState: """Detaches a block with the specified label from an agent.""" with self.session_maker() as session: agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) original_length = len(agent.core_memory) agent.core_memory = [b for b in agent.core_memory if b.label != block_label] if len(agent.core_memory) == original_length: raise NoResultFound(f"No block with label '{block_label}' found for agent '{agent_id}' with actor id: '{actor.id}'") agent.update(session, actor=actor) return agent.to_pydantic() # ====================================================================================================================== # Passage Management # ====================================================================================================================== def _build_passage_query( self, actor: PydanticUser, agent_id: Optional[str] = None, file_id: Optional[str] = None, query_text: Optional[str] = None, start_date: Optional[datetime] = None, end_date: Optional[datetime] = None, cursor: Optional[str] = None, source_id: Optional[str] = None, embed_query: bool = False, ascending: bool = True, embedding_config: Optional[EmbeddingConfig] = None, agent_only: bool = False, ) -> Select: """Helper function to build the base passage query with all filters applied. Returns the query before any limit or count operations are applied. """ embedded_text = None if embed_query: assert embedding_config is not None, "embedding_config must be specified for vector search" assert query_text is not None, "query_text must be specified for vector search" embedded_text = embedding_model(embedding_config).get_text_embedding(query_text) embedded_text = np.array(embedded_text) embedded_text = np.pad(embedded_text, (0, MAX_EMBEDDING_DIM - embedded_text.shape[0]), mode="constant").tolist() with self.session_maker() as session: # Start with base query for source passages source_passages = None if not agent_only: # Include source passages if agent_id is not None: source_passages = ( select(SourcePassage, literal(None).label("agent_id")) .join(SourcesAgents, SourcesAgents.source_id == SourcePassage.source_id) .where(SourcesAgents.agent_id == agent_id) .where(SourcePassage.organization_id == actor.organization_id) ) else: source_passages = select(SourcePassage, literal(None).label("agent_id")).where( SourcePassage.organization_id == actor.organization_id ) if source_id: source_passages = source_passages.where(SourcePassage.source_id == source_id) if file_id: source_passages = source_passages.where(SourcePassage.file_id == file_id) # Add agent passages query agent_passages = None if agent_id is not None: agent_passages = ( select( AgentPassage.id, AgentPassage.text, AgentPassage.embedding_config, AgentPassage.metadata_, AgentPassage.embedding, AgentPassage.created_at, AgentPassage.updated_at, AgentPassage.is_deleted, AgentPassage._created_by_id, AgentPassage._last_updated_by_id, AgentPassage.organization_id, literal(None).label("file_id"), literal(None).label("source_id"), AgentPassage.agent_id, ) .where(AgentPassage.agent_id == agent_id) .where(AgentPassage.organization_id == actor.organization_id) ) # Combine queries if source_passages is not None and agent_passages is not None: combined_query = union_all(source_passages, agent_passages).cte("combined_passages") elif agent_passages is not None: combined_query = agent_passages.cte("combined_passages") elif source_passages is not None: combined_query = source_passages.cte("combined_passages") else: raise ValueError("No passages found") # Build main query from combined CTE main_query = select(combined_query) # Apply filters if start_date: main_query = main_query.where(combined_query.c.created_at >= start_date) if end_date: main_query = main_query.where(combined_query.c.created_at <= end_date) if source_id: main_query = main_query.where(combined_query.c.source_id == source_id) if file_id: main_query = main_query.where(combined_query.c.file_id == file_id) # Vector search if embedded_text: if settings.letta_pg_uri_no_default: # PostgreSQL with pgvector main_query = main_query.order_by(combined_query.c.embedding.cosine_distance(embedded_text).asc()) else: # SQLite with custom vector type query_embedding_binary = adapt_array(embedded_text) if ascending: main_query = main_query.order_by( func.cosine_distance(combined_query.c.embedding, query_embedding_binary).asc(), combined_query.c.created_at.asc(), combined_query.c.id.asc(), ) else: main_query = main_query.order_by( func.cosine_distance(combined_query.c.embedding, query_embedding_binary).asc(), combined_query.c.created_at.desc(), combined_query.c.id.asc(), ) else: if query_text: main_query = main_query.where(func.lower(combined_query.c.text).contains(func.lower(query_text))) # Handle cursor-based pagination if cursor: cursor_query = select(combined_query.c.created_at).where(combined_query.c.id == cursor).scalar_subquery() if ascending: main_query = main_query.where(combined_query.c.created_at > cursor_query) else: main_query = main_query.where(combined_query.c.created_at < cursor_query) # Add ordering if not already ordered by similarity if not embed_query: if ascending: main_query = main_query.order_by( combined_query.c.created_at.asc(), combined_query.c.id.asc(), ) else: main_query = main_query.order_by( combined_query.c.created_at.desc(), combined_query.c.id.asc(), ) return main_query @enforce_types def list_passages( self, actor: PydanticUser, agent_id: Optional[str] = None, file_id: Optional[str] = None, limit: Optional[int] = 50, query_text: Optional[str] = None, start_date: Optional[datetime] = None, end_date: Optional[datetime] = None, cursor: Optional[str] = None, source_id: Optional[str] = None, embed_query: bool = False, ascending: bool = True, embedding_config: Optional[EmbeddingConfig] = None, agent_only: bool = False, ) -> List[PydanticPassage]: """Lists all passages attached to an agent.""" with self.session_maker() as session: main_query = self._build_passage_query( actor=actor, agent_id=agent_id, file_id=file_id, query_text=query_text, start_date=start_date, end_date=end_date, cursor=cursor, source_id=source_id, embed_query=embed_query, ascending=ascending, embedding_config=embedding_config, agent_only=agent_only, ) # Add limit if limit: main_query = main_query.limit(limit) # Execute query results = list(session.execute(main_query)) passages = [] for row in results: data = dict(row._mapping) if data["agent_id"] is not None: # This is an AgentPassage - remove source fields data.pop("source_id", None) data.pop("file_id", None) passage = AgentPassage(**data) else: # This is a SourcePassage - remove agent field data.pop("agent_id", None) passage = SourcePassage(**data) passages.append(passage) return [p.to_pydantic() for p in passages] @enforce_types def passage_size( self, actor: PydanticUser, agent_id: Optional[str] = None, file_id: Optional[str] = None, query_text: Optional[str] = None, start_date: Optional[datetime] = None, end_date: Optional[datetime] = None, cursor: Optional[str] = None, source_id: Optional[str] = None, embed_query: bool = False, ascending: bool = True, embedding_config: Optional[EmbeddingConfig] = None, agent_only: bool = False, ) -> int: """Returns the count of passages matching the given criteria.""" with self.session_maker() as session: main_query = self._build_passage_query( actor=actor, agent_id=agent_id, file_id=file_id, query_text=query_text, start_date=start_date, end_date=end_date, cursor=cursor, source_id=source_id, embed_query=embed_query, ascending=ascending, embedding_config=embedding_config, agent_only=agent_only, ) # Convert to count query count_query = select(func.count()).select_from(main_query.subquery()) return session.scalar(count_query) or 0 # ====================================================================================================================== # Tool Management # ====================================================================================================================== @enforce_types def attach_tool(self, agent_id: str, tool_id: str, actor: PydanticUser) -> PydanticAgentState: """ Attaches a tool to an agent. Args: agent_id: ID of the agent to attach the tool to. tool_id: ID of the tool to attach. actor: User performing the action. Raises: NoResultFound: If the agent or tool is not found. Returns: PydanticAgentState: The updated agent state. """ with self.session_maker() as session: # Verify the agent exists and user has permission to access it agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) # Use the _process_relationship helper to attach the tool _process_relationship( session=session, agent=agent, relationship_name="tools", model_class=ToolModel, item_ids=[tool_id], allow_partial=False, # Ensure the tool exists replace=False, # Extend the existing tools ) # Commit and refresh the agent agent.update(session, actor=actor) return agent.to_pydantic() @enforce_types def detach_tool(self, agent_id: str, tool_id: str, actor: PydanticUser) -> PydanticAgentState: """ Detaches a tool from an agent. Args: agent_id: ID of the agent to detach the tool from. tool_id: ID of the tool to detach. actor: User performing the action. Raises: NoResultFound: If the agent or tool is not found. Returns: PydanticAgentState: The updated agent state. """ with self.session_maker() as session: # Verify the agent exists and user has permission to access it agent = AgentModel.read(db_session=session, identifier=agent_id, actor=actor) # Filter out the tool to be detached remaining_tools = [tool for tool in agent.tools if tool.id != tool_id] if len(remaining_tools) == len(agent.tools): # Tool ID was not in the relationship logger.warning(f"Attempted to remove unattached tool id={tool_id} from agent id={agent_id} by actor={actor}") # Update the tools relationship agent.tools = remaining_tools # Commit and refresh the agent agent.update(session, actor=actor) return agent.to_pydantic()