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messagenode

Class info

Classes

Name Children Inherits
AggregatedTalkStats
llmling_agent.talk.stats
Statistics aggregated from multiple connections.
    ChatMessage
    llmling_agent.messaging.messages
    Common message format for all UI types.
      MessageNode
      llmling_agent.messaging.messagenode
      Base class for all message processing nodes.
      TaskManager
      llmling_agent.utils.tasks
      Mixin for managing async tasks.

        🛈 DocStrings

        Base class for message processing nodes.

        MessageNode

        Bases: ABC

        Base class for all message processing nodes.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        class MessageNode[TDeps, TResult](ABC):
    """Base class for all message processing nodes."""

    message_received = Signal(ChatMessage)
    """Signal emitted when node receives a message."""

    message_sent = Signal(ChatMessage)
    """Signal emitted when node creates a message."""

    def __init__(
        self,
        name: str | None = None,
        description: str | None = None,
        input_provider: InputProvider | None = None,
        mcp_servers: Sequence[str | MCPServerConfig] | None = None,
        agent_pool: AgentPool[Any] | None = None,
        enable_logging: bool = True,
    ) -> None:
        """Initialize message node."""
        super().__init__()
        from llmling_agent.mcp_server.manager import MCPManager
        from llmling_agent.messaging import EventManager
        from llmling_agent.messaging.connection_manager import ConnectionManager

        self.task_manager = TaskManager()
        self._name = name or self.__class__.__name__
        self.log = logger.bind(agent_name=self._name)
        self.agent_pool = agent_pool
        self.description = description
        self.connections = ConnectionManager(self)
        self._events = EventManager(self, enable_events=True)
        name_ = f"node_{self._name}"
        self.mcp = MCPManager(
            name_, servers=mcp_servers, input_provider=input_provider, owner=self.name
        )
        self.enable_db_logging = enable_logging
        self.conversation_id = str(uuid4())
        # Connect to the combined signal to capture all messages
        # TODO: need to check this
        # node.message_received.connect(self.log_message)

    async def __aenter__(self) -> Self:
        """Initialize base message node."""
        if self.enable_db_logging:
            await self.context.storage.log_conversation(
                conversation_id=self.conversation_id,
                node_name=self.name,
            )
        try:
            await self._events.__aenter__()
            await self.mcp.__aenter__()
        except Exception as e:
            await self.__aexit__(type(e), e, e.__traceback__)
            msg = f"Failed to initialize {self.name}"
            raise RuntimeError(msg) from e
        else:
            return self

    async def __aexit__(
        self,
        exc_type: type[BaseException] | None,
        exc_val: BaseException | None,
        exc_tb: TracebackType | None,
    ) -> None:
        """Clean up base resources."""
        await self._events.__aexit__(exc_type, exc_val, exc_tb)
        await self.mcp.__aexit__(exc_type, exc_val, exc_tb)
        await self.task_manager.cleanup_tasks()

    @property
    def connection_stats(self) -> AggregatedTalkStats:
        """Get stats for all active connections of this node."""
        stats = [talk.stats for talk in self.connections.get_connections()]
        return AggregatedTalkStats(stats=stats)

    @property
    def context(self) -> NodeContext:
        """Get node context."""
        raise NotImplementedError

    @property
    def name(self) -> str:
        """Get agent name."""
        return self._name or "llmling-agent"

    @name.setter
    def name(self, value: str) -> None:
        self._name = value

    @overload
    def __rshift__(
        self, other: MessageNode[Any, Any] | ProcessorCallback[Any]
    ) -> Talk[TResult]: ...

    @overload
    def __rshift__(
        self, other: Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]]
    ) -> TeamTalk[TResult]: ...

    def __rshift__(
        self,
        other: MessageNode[Any, Any]
        | ProcessorCallback[Any]
        | Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
    ) -> Talk[Any] | TeamTalk[Any]:
        """Connect agent to another agent or group.

        Example:
            agent >> other_agent  # Connect to single agent
            agent >> (agent2 & agent3)  # Connect to group
            agent >> "other_agent"  # Connect by name (needs pool)
        """
        return self.connect_to(other)

    @overload
    def connect_to(
        self,
        target: MessageNode[Any, Any] | ProcessorCallback[Any],
        *,
        queued: Literal[True],
        queue_strategy: Literal["concat"],
    ) -> Talk[str]: ...

    @overload
    def connect_to(
        self,
        target: MessageNode[Any, Any] | ProcessorCallback[Any],
        *,
        connection_type: ConnectionType = "run",
        name: str | None = None,
        priority: int = 0,
        delay: timedelta | None = None,
        queued: bool = False,
        queue_strategy: QueueStrategy = "latest",
        transform: AnyTransformFn[Any] | None = None,
        filter_condition: AsyncFilterFn | None = None,
        stop_condition: AsyncFilterFn | None = None,
        exit_condition: AsyncFilterFn | None = None,
    ) -> Talk[TResult]: ...

    @overload
    def connect_to(
        self,
        target: Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
        *,
        queued: Literal[True],
        queue_strategy: Literal["concat"],
    ) -> TeamTalk[str]: ...

    @overload
    def connect_to(
        self,
        target: Sequence[MessageNode[Any, TResult] | ProcessorCallback[TResult]],
        *,
        connection_type: ConnectionType = "run",
        name: str | None = None,
        priority: int = 0,
        delay: timedelta | None = None,
        queued: bool = False,
        queue_strategy: QueueStrategy = "latest",
        transform: AnyTransformFn[Any] | None = None,
        filter_condition: AsyncFilterFn | None = None,
        stop_condition: AsyncFilterFn | None = None,
        exit_condition: AsyncFilterFn | None = None,
    ) -> TeamTalk[TResult]: ...

    @overload
    def connect_to(
        self,
        target: Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
        *,
        connection_type: ConnectionType = "run",
        name: str | None = None,
        priority: int = 0,
        delay: timedelta | None = None,
        queued: bool = False,
        queue_strategy: QueueStrategy = "latest",
        transform: AnyTransformFn[Any] | None = None,
        filter_condition: AsyncFilterFn | None = None,
        stop_condition: AsyncFilterFn | None = None,
        exit_condition: AsyncFilterFn | None = None,
    ) -> TeamTalk: ...

    def connect_to(
        self,
        target: MessageNode[Any, Any]
        | ProcessorCallback[Any]
        | Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
        *,
        connection_type: ConnectionType = "run",
        name: str | None = None,
        priority: int = 0,
        delay: timedelta | None = None,
        queued: bool = False,
        queue_strategy: QueueStrategy = "latest",
        transform: AnyTransformFn[Any] | None = None,
        filter_condition: AsyncFilterFn | None = None,
        stop_condition: AsyncFilterFn | None = None,
        exit_condition: AsyncFilterFn | None = None,
    ) -> Talk[Any] | TeamTalk:
        """Create connection(s) to target(s)."""
        # Handle callable case
        from llmling_agent.agent import Agent
        from llmling_agent.delegation.base_team import BaseTeam

        if callable(target):
            target = Agent.from_callback(target)
            if pool := self.context.pool:
                pool.register(target.name, target)
        # we are explicit here just to make disctinction clear, we only want sequences
        # of message units
        if isinstance(target, Sequence) and not isinstance(target, BaseTeam):
            targets: list[MessageNode[Any, Any]] = []
            for t in target:
                match t:
                    case _ if callable(t):
                        other = Agent.from_callback(t)
                        if pool := self.context.pool:
                            pool.register(other.name, other)
                        targets.append(other)
                    case MessageNode():
                        targets.append(t)
                    case _:
                        msg = f"Invalid node type: {type(t)}"
                        raise TypeError(msg)
        else:
            targets = target  # type: ignore
        return self.connections.create_connection(
            self,
            targets,
            connection_type=connection_type,
            priority=priority,
            name=name,
            delay=delay,
            queued=queued,
            queue_strategy=queue_strategy,
            transform=transform,
            filter_condition=filter_condition,
            stop_condition=stop_condition,
            exit_condition=exit_condition,
        )

    async def disconnect_all(self) -> None:
        """Disconnect from all nodes."""
        for target in list(self.connections.get_targets()):
            self.stop_passing_results_to(target)

    def stop_passing_results_to(self, other: MessageNode[Any, Any]) -> None:
        """Stop forwarding results to another node."""
        self.connections.disconnect(other)

    @abstractmethod
    async def run(self, *prompts: Any, **kwargs: Any) -> ChatMessage[TResult]:
        """Execute node with prompts. Implementation-specific run logic."""

    async def get_message_history(self, limit: int | None = None) -> list[ChatMessage[Any]]:
        """Get message history from storage."""
        if not self.enable_db_logging:
            return []  # No history if not logging

        from llmling_agent_config.session import SessionQuery

        query = SessionQuery(name=self.conversation_id, limit=limit)
        return await self.context.storage.filter_messages(query)

    async def log_message(self, message: ChatMessage[Any]) -> None:
        """Handle message from chat signal."""
        if self.enable_db_logging:
            await self.context.storage.log_message(message)  # pyright: ignore

    @abstractmethod
    async def get_stats(self) -> MessageStats | AggregatedMessageStats:
        """Get message statistics for this node."""

    @abstractmethod
    def run_iter(self, *prompts: Any, **kwargs: Any) -> AsyncIterator[ChatMessage[Any]]:
        """Yield messages during execution."""

        connection_stats property 

        connection_stats: AggregatedTalkStats

        Get stats for all active connections of this node.

        context property 

        context: NodeContext

        Get node context.

        message_received class-attribute instance-attribute 

        message_received = Signal(ChatMessage)

        Signal emitted when node receives a message.

        message_sent class-attribute instance-attribute 

        message_sent = Signal(ChatMessage)

        Signal emitted when node creates a message.

        name property writable 

        name: str

        Get agent name.

        __aenter__ async 

        __aenter__() -> Self

        Initialize base message node.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        async def __aenter__(self) -> Self:
    """Initialize base message node."""
    if self.enable_db_logging:
        await self.context.storage.log_conversation(
            conversation_id=self.conversation_id,
            node_name=self.name,
        )
    try:
        await self._events.__aenter__()
        await self.mcp.__aenter__()
    except Exception as e:
        await self.__aexit__(type(e), e, e.__traceback__)
        msg = f"Failed to initialize {self.name}"
        raise RuntimeError(msg) from e
    else:
        return self

        __aexit__ async 

        __aexit__(
    exc_type: type[BaseException] | None,
    exc_val: BaseException | None,
    exc_tb: TracebackType | None,
) -> None

        Clean up base resources.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        async def __aexit__(
    self,
    exc_type: type[BaseException] | None,
    exc_val: BaseException | None,
    exc_tb: TracebackType | None,
) -> None:
    """Clean up base resources."""
    await self._events.__aexit__(exc_type, exc_val, exc_tb)
    await self.mcp.__aexit__(exc_type, exc_val, exc_tb)
    await self.task_manager.cleanup_tasks()

        __init__ 

        __init__(
    name: str | None = None,
    description: str | None = None,
    input_provider: InputProvider | None = None,
    mcp_servers: Sequence[str | MCPServerConfig] | None = None,
    agent_pool: AgentPool[Any] | None = None,
    enable_logging: bool = True,
) -> None

        Initialize message node.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        def __init__(
    self,
    name: str | None = None,
    description: str | None = None,
    input_provider: InputProvider | None = None,
    mcp_servers: Sequence[str | MCPServerConfig] | None = None,
    agent_pool: AgentPool[Any] | None = None,
    enable_logging: bool = True,
) -> None:
    """Initialize message node."""
    super().__init__()
    from llmling_agent.mcp_server.manager import MCPManager
    from llmling_agent.messaging import EventManager
    from llmling_agent.messaging.connection_manager import ConnectionManager

    self.task_manager = TaskManager()
    self._name = name or self.__class__.__name__
    self.log = logger.bind(agent_name=self._name)
    self.agent_pool = agent_pool
    self.description = description
    self.connections = ConnectionManager(self)
    self._events = EventManager(self, enable_events=True)
    name_ = f"node_{self._name}"
    self.mcp = MCPManager(
        name_, servers=mcp_servers, input_provider=input_provider, owner=self.name
    )
    self.enable_db_logging = enable_logging
    self.conversation_id = str(uuid4())

        __rshift__ 

        __rshift__(other: MessageNode[Any, Any] | ProcessorCallback[Any]) -> Talk[TResult]

        __rshift__(
    other: Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
) -> TeamTalk[TResult]

        __rshift__(
    other: (
        MessageNode[Any, Any]
        | ProcessorCallback[Any]
        | Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]]
    ),
) -> Talk[Any] | TeamTalk[Any]

        Connect agent to another agent or group.

        Example

        agent >> other_agent # Connect to single agent agent >> (agent2 & agent3) # Connect to group agent >> "other_agent" # Connect by name (needs pool)

        Source code in src/llmling_agent/messaging/messagenode.py 
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        def __rshift__(
    self,
    other: MessageNode[Any, Any]
    | ProcessorCallback[Any]
    | Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
) -> Talk[Any] | TeamTalk[Any]:
    """Connect agent to another agent or group.

    Example:
        agent >> other_agent  # Connect to single agent
        agent >> (agent2 & agent3)  # Connect to group
        agent >> "other_agent"  # Connect by name (needs pool)
    """
    return self.connect_to(other)

        connect_to 

        connect_to(
    target: MessageNode[Any, Any] | ProcessorCallback[Any],
    *,
    queued: Literal[True],
    queue_strategy: Literal["concat"]
) -> Talk[str]

        connect_to(
    target: MessageNode[Any, Any] | ProcessorCallback[Any],
    *,
    connection_type: ConnectionType = "run",
    name: str | None = None,
    priority: int = 0,
    delay: timedelta | None = None,
    queued: bool = False,
    queue_strategy: QueueStrategy = "latest",
    transform: AnyTransformFn[Any] | None = None,
    filter_condition: AsyncFilterFn | None = None,
    stop_condition: AsyncFilterFn | None = None,
    exit_condition: AsyncFilterFn | None = None
) -> Talk[TResult]

        connect_to(
    target: Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
    *,
    queued: Literal[True],
    queue_strategy: Literal["concat"]
) -> TeamTalk[str]

        connect_to(
    target: Sequence[MessageNode[Any, TResult] | ProcessorCallback[TResult]],
    *,
    connection_type: ConnectionType = "run",
    name: str | None = None,
    priority: int = 0,
    delay: timedelta | None = None,
    queued: bool = False,
    queue_strategy: QueueStrategy = "latest",
    transform: AnyTransformFn[Any] | None = None,
    filter_condition: AsyncFilterFn | None = None,
    stop_condition: AsyncFilterFn | None = None,
    exit_condition: AsyncFilterFn | None = None
) -> TeamTalk[TResult]

        connect_to(
    target: Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
    *,
    connection_type: ConnectionType = "run",
    name: str | None = None,
    priority: int = 0,
    delay: timedelta | None = None,
    queued: bool = False,
    queue_strategy: QueueStrategy = "latest",
    transform: AnyTransformFn[Any] | None = None,
    filter_condition: AsyncFilterFn | None = None,
    stop_condition: AsyncFilterFn | None = None,
    exit_condition: AsyncFilterFn | None = None
) -> TeamTalk

        connect_to(
    target: (
        MessageNode[Any, Any]
        | ProcessorCallback[Any]
        | Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]]
    ),
    *,
    connection_type: ConnectionType = "run",
    name: str | None = None,
    priority: int = 0,
    delay: timedelta | None = None,
    queued: bool = False,
    queue_strategy: QueueStrategy = "latest",
    transform: AnyTransformFn[Any] | None = None,
    filter_condition: AsyncFilterFn | None = None,
    stop_condition: AsyncFilterFn | None = None,
    exit_condition: AsyncFilterFn | None = None
) -> Talk[Any] | TeamTalk

        Create connection(s) to target(s).

        Source code in src/llmling_agent/messaging/messagenode.py 
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        def connect_to(
    self,
    target: MessageNode[Any, Any]
    | ProcessorCallback[Any]
    | Sequence[MessageNode[Any, Any] | ProcessorCallback[Any]],
    *,
    connection_type: ConnectionType = "run",
    name: str | None = None,
    priority: int = 0,
    delay: timedelta | None = None,
    queued: bool = False,
    queue_strategy: QueueStrategy = "latest",
    transform: AnyTransformFn[Any] | None = None,
    filter_condition: AsyncFilterFn | None = None,
    stop_condition: AsyncFilterFn | None = None,
    exit_condition: AsyncFilterFn | None = None,
) -> Talk[Any] | TeamTalk:
    """Create connection(s) to target(s)."""
    # Handle callable case
    from llmling_agent.agent import Agent
    from llmling_agent.delegation.base_team import BaseTeam

    if callable(target):
        target = Agent.from_callback(target)
        if pool := self.context.pool:
            pool.register(target.name, target)
    # we are explicit here just to make disctinction clear, we only want sequences
    # of message units
    if isinstance(target, Sequence) and not isinstance(target, BaseTeam):
        targets: list[MessageNode[Any, Any]] = []
        for t in target:
            match t:
                case _ if callable(t):
                    other = Agent.from_callback(t)
                    if pool := self.context.pool:
                        pool.register(other.name, other)
                    targets.append(other)
                case MessageNode():
                    targets.append(t)
                case _:
                    msg = f"Invalid node type: {type(t)}"
                    raise TypeError(msg)
    else:
        targets = target  # type: ignore
    return self.connections.create_connection(
        self,
        targets,
        connection_type=connection_type,
        priority=priority,
        name=name,
        delay=delay,
        queued=queued,
        queue_strategy=queue_strategy,
        transform=transform,
        filter_condition=filter_condition,
        stop_condition=stop_condition,
        exit_condition=exit_condition,
    )

        disconnect_all async 

        disconnect_all() -> None

        Disconnect from all nodes.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        async def disconnect_all(self) -> None:
    """Disconnect from all nodes."""
    for target in list(self.connections.get_targets()):
        self.stop_passing_results_to(target)

        get_message_history async 

        get_message_history(limit: int | None = None) -> list[ChatMessage[Any]]

        Get message history from storage.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        async def get_message_history(self, limit: int | None = None) -> list[ChatMessage[Any]]:
    """Get message history from storage."""
    if not self.enable_db_logging:
        return []  # No history if not logging

    from llmling_agent_config.session import SessionQuery

    query = SessionQuery(name=self.conversation_id, limit=limit)
    return await self.context.storage.filter_messages(query)

        get_stats abstractmethod async 

        get_stats() -> MessageStats | AggregatedMessageStats

        Get message statistics for this node.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        @abstractmethod
async def get_stats(self) -> MessageStats | AggregatedMessageStats:
    """Get message statistics for this node."""

        log_message async 

        log_message(message: ChatMessage[Any]) -> None

        Handle message from chat signal.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        async def log_message(self, message: ChatMessage[Any]) -> None:
    """Handle message from chat signal."""
    if self.enable_db_logging:
        await self.context.storage.log_message(message)  # pyright: ignore

        run abstractmethod async 

        run(*prompts: Any, **kwargs: Any) -> ChatMessage[TResult]

        Execute node with prompts. Implementation-specific run logic.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        @abstractmethod
async def run(self, *prompts: Any, **kwargs: Any) -> ChatMessage[TResult]:
    """Execute node with prompts. Implementation-specific run logic."""

        run_iter abstractmethod 

        run_iter(*prompts: Any, **kwargs: Any) -> AsyncIterator[ChatMessage[Any]]

        Yield messages during execution.

        Source code in src/llmling_agent/messaging/messagenode.py 
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        @abstractmethod
def run_iter(self, *prompts: Any, **kwargs: Any) -> AsyncIterator[ChatMessage[Any]]:
    """Yield messages during execution."""

        stop_passing_results_to 

        stop_passing_results_to(other: MessageNode[Any, Any]) -> None

        Stop forwarding results to another node.

        Source code in src/llmling_agent/messaging/messagenode.py 
        288
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        def stop_passing_results_to(self, other: MessageNode[Any, Any]) -> None:
    """Stop forwarding results to another node."""
    self.connections.disconnect(other)