Conversations

Messages

class wayflowcore.messagelist.Message(content='', message_type=None, tool_requests=None, tool_result=None, is_error=False, display_only=False, sender=None, recipients=None, time_created=None, time_updated=None, contents=None, role=None, _prompt_cache_key=None, _reasoning_content=None, __metadata_info__=None)

Messages are an exchange medium between the user, LLM agent, and controller logic. This helps to determine who provided what information.

Parameters:

• content (str) – Content of the message.

• message_type (Optional[MessageType]) – A message type out of the following ones: SYSTEM, AGENT, USER, THOUGHT, INTERNAL, TOOL_REQUEST, TOOL_RESULT.

• tool_requests (Optional[List[ToolRequest]]) – A list of ToolRequest objects representing the tools invoked as part of this message. Each request includes the tool’s name, arguments, and a unique identifier.

• tool_result (Optional[ToolResult]) – A ToolResult object representing the outcome of a tool invocation. It includes the returned content and a reference to the related tool request ID.

• display_only (bool) – If True, the message is excluded from any context. Its only purpose is to be displayed in the chat UI (e.g debugging message)

• sender (Optional[str]) – Sender of the message in str format.

• recipients (Optional[Set[str]]) – Recipients of the message in str format.

• time_created (Optional[datetime]) – Creation timestamp of the message.

• time_updated (Optional[datetime]) – Update timestamp of the message.

• contents (Optional[List[MessageContent]]) – Message content. Is a list of chunks with potentially different types

• role (Optional[Literal['user', 'system', 'assistant']]) – Role of the sender of the message. Can be user, system or assistant

• is_error (bool) –

• _prompt_cache_key (str | None) –

• _reasoning_content (Dict[str, Any] | None) –

• __metadata_info__ (Dict[str, Any]) –

property content: str

Text content getter

contents: List[MessageContent]

copy(**kwargs)

Create a copy of the given message.

Return type:

Message

Parameters:

kwargs (Any) –

display_only: bool = False

property hash: str

property is_error: bool

property message_type: MessageType

Getter to guarantee backward compatibility

recipients: Set[str]

role: Literal['user', 'assistant', 'system']

sender: Optional[str] = None

time_created: datetime

time_updated: datetime

tool_requests: Optional[List[ToolRequest]] = None

tool_result: Optional[ToolResult] = None

class wayflowcore.messagelist.MessageType(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Type of messages

AGENT = 'AGENT'

DISPLAY_ONLY = 'DISPLAY_ONLY'

ERROR = 'ERROR'

INTERNAL = 'INTERNAL'

SYSTEM = 'SYSTEM'

THOUGHT = 'THOUGHT'

TOOL_REQUEST = 'TOOL_REQUEST'

TOOL_RESULT = 'TOOL_RESULT'

USER = 'USER'

class wayflowcore.messagelist.MessageContent

Abstract base class for message content chunks.

All message content types (such as text and images) should derive from this class and specify a class-level ‘type’ field to distinguish content variant. Subclasses may also add additional fields for content-specific data.

Parameters:

type – Identifier for the content type, to be implemented by subclasses.

type: ClassVar[str]

class wayflowcore.messagelist.TextContent(content='')

Represents the content of a text message.

Parameters:

• content (str) – The textual content of the message.

• type – Identifier for the text content type.

content: str = ''

type: ClassVar[Literal['text']] = 'text'

class wayflowcore.messagelist.ImageContent(base64_content)

Represents the content of an image message, storing image data as a base64-encoded string.

Parameters:

• base64_content (str) – A base64-encoded string representing the image data.

• type – Identifier for the image content type.

Examples

>>> import requests
>>> from wayflowcore.messagelist import Message, TextContent, ImageContent
>>> from wayflowcore.models import Prompt
>>> # Download the Oracle logo as bytes
>>> url = "https://www.oracle.com/a/ocom/img/oracle-logo.png"
>>> response = requests.get(url)
>>> img_content = ImageContent.from_bytes(response.content, format="png")
>>> prompt = Prompt(messages=[Message(contents = [TextContent("Which company's logo is this?") , img_content])])
>>> completion = multimodal_llm.generate(prompt)
>>> # LlmCompletion(message=Message(content="That is the logo for **Oracle Corporation**."))

base64_content: str

classmethod from_bytes(bytes_content, format)

Return type:

ImageContent

Parameters:

• bytes_content (bytes) –

• format (str) –

type: ClassVar[str] = 'image'

class wayflowcore.messagelist.MessageList(messages=<factory>, *, id=<factory>, __metadata_info__=<factory>)

Object that carries a list of messages. We may only append to this object, not remove

Parameters:

• messages (List[Message]) – list of messages to start from.

• id (str) –

• __metadata_info__ (Dict[str, Any]) –

append_agent_message(agent_input, is_error=False)

Append a new message object of type MessageType.AGENT to the messages list.

Parameters:

• agent_input (str) – message to append.

• is_error (bool) –

Return type:

None

append_message(message)

Add a message to a message list.

Parameters:

message (Message) – Message to append to the message list.

Return type:

None

append_tool_result(tool_result)

Append a new message object of type MessageType.TOOL_RESULT to the messages list.

Parameters:

tool_result (ToolResult) – message to append.

Return type:

None

append_user_message(user_input)

Append a new message object of type MessageType.USER to the messages list.

Parameters:

user_input (Union[str, List[MessageContent]]) – message to append.

Return type:

None

copy()

Create a copy of the given message list.

Return type:

MessageList

classmethod from_messages(messages=None)

Return type:

MessageList

Parameters:

messages (None | str | Message | List[Message]) –

get_last_message(strict=False)

Returns the last message from the conversation. If strict=True, raises an exception if no messages exist.

Return type:

Optional[Message]

Parameters:

strict (bool) –

get_messages()

Returns a copy of the messages list

Return type:

List[Message]

messages: List[Message]

ExecutionStatus

class wayflowcore.executors.executionstatus.ExecutionStatus(*, id=<factory>, __metadata_info__=<factory>, _conversation_id=None)

Execution status returned by the Assistant. This indicates if the assistant yielded, finished the conversation, …

Parameters:

• id (str) –

• __metadata_info__ (Dict[str, Any]) –

• _conversation_id (str | None) –

class wayflowcore.executors.executionstatus.UserMessageRequestStatus(*, id=<factory>, __metadata_info__=<factory>, _conversation_id=None, message, _user_response=None)

Execution status for when the assistant answered and will be waiting for the next user input

Parameters:

• id (str) –

• __metadata_info__ (Dict[str, Any]) –

• _conversation_id (str | None) –

• message (Message) –

• _user_response (Message | None) –

message: Message

The message from the assistant to which the user needs to answer to.

submit_user_response(response)

Submit the answer to this user message request.

Return type:

None

Parameters:

response (str | Message) –

class wayflowcore.executors.executionstatus.FinishedStatus(output_values, complete_step_name=None, *, id=<factory>, __metadata_info__=<factory>, _conversation_id=None)

Execution status for when the conversation is finished. Contains the outputs of the conversation

Parameters:

• output_values (Dict[str, Any]) –

• complete_step_name (str | None) –

• id (str) –

• __metadata_info__ (Dict[str, Any]) –

• _conversation_id (str | None) –

complete_step_name: Optional[str] = None

The name of the last step reached if the flow returning this execution status transitioned to a CompleteStep, otherwise None.

output_values: Dict[str, Any]

The outputs produced by the agent or flow returning this execution status.

class wayflowcore.executors.executionstatus.ToolRequestStatus(*, id=<factory>, __metadata_info__=<factory>, _conversation_id=None, tool_requests, _tool_results=None)

Execution status for when the assistant is asking the user to call a tool and send back its result

Parameters:

• id (str) –

• __metadata_info__ (Dict[str, Any]) –

• _conversation_id (str | None) –

• tool_requests (List[ToolRequest]) –

• _tool_results (List[ToolResult] | None) –

submit_tool_result(tool_result)

Submit the tool results to the given tool requests.

Return type:

None

Parameters:

tool_result (ToolResult) –

submit_tool_results(tool_results)

Submit the tool results to the given tool requests.

Return type:

None

Parameters:

tool_results (List[ToolResult]) –

tool_requests: List['ToolRequest']

The tool requests for the client tools that the client need to run.

Conversation

Base class for conversations. Can manipulate a conversation object, and can be serialized/deserialized.

class wayflowcore.conversationalcomponent.ConversationalComponent(name, description, input_descriptors, output_descriptors, runner, conversation_class, id=None, __metadata_info__=None)

Parameters:

• name (str) –

• description (str | None) –

• input_descriptors (List[Property]) –

• output_descriptors (List[Property]) –

• runner (Type[ConversationExecutor]) –

• conversation_class (Any) –

• id (str | None) –

• __metadata_info__ (Dict[str, Any] | None) –

property llms: List[LlmModel]

abstract start_conversation(inputs=None, messages=None)

Return type:

Conversation

Parameters:

• inputs (Dict[str, Any] | None) –

• messages (None | str | Message | List[Message] | MessageList) –

class wayflowcore.conversation.Conversation(component, state, inputs, message_list, status, conversation_id='', status_handled=False, *, id=<factory>, __metadata_info__=<factory>, name='', description=None)

Parameters:

• component (ConversationalComponent) –

• state (ConversationExecutionState) –

• inputs (Dict[str, Any]) –

• message_list (MessageList) –

• status (ExecutionStatus | None) –

• conversation_id (str) –

• status_handled (bool) –

• id (str) –

• __metadata_info__ (Dict[str, Any]) –

• name (str) –

• description (str | None) –

append_agent_message(agent_input, is_error=False)

Append a new message object of type MessageType.AGENT to the messages list.

Parameters:

• agent_input (str) – message to append.

• is_error (bool) –

Return type:

None

append_message(message)

Append a message to the messages list of this Conversation object.

Parameters:

message (Message) – message to append.

Return type:

None

append_tool_result(tool_result)

Append a new message object of type MessageType.TOOL_RESULT to the messages list.

Parameters:

tool_result (ToolResult) – message to append.

Return type:

None

append_user_message(user_input)

Append a new message object of type MessageType.USER to the messages list.

Parameters:

user_input (Union[str, List[MessageContent]]) – str or list of message contents to append as a user message.

Return type:

None

component: ConversationalComponent

conversation_id: str = ''

abstract property current_step_name: str

execute(execution_interrupts=None)

Execute the conversation and get its ExecutionStatus based on the outcome.

The Execution status is returned by the Assistant and indicates if the assistant yielded, finished the conversation.

Return type:

ExecutionStatus

Parameters:

execution_interrupts (Sequence[ExecutionInterrupt] | None) –

async execute_async(execution_interrupts=None)

Execute the conversation and get its ExecutionStatus based on the outcome.

The Execution status is returned by the Assistant and indicates if the assistant yielded, finished the conversation.

Return type:

ExecutionStatus

Parameters:

execution_interrupts (Sequence[ExecutionInterrupt] | None) –

get_last_message()

Get the last message from the messages List.

Return type:

Optional[Message]

get_messages()

Return all Message objects of the messages list in a python list.

Return type:

List[Message]

inputs: Dict[str, Any]

message_list: MessageList

property plan: ExecutionPlan | None

state: ConversationExecutionState

status: Optional[ExecutionStatus]

status_handled: bool = False

Whether the current status associated to this conversation was already handled or not (messages/tool results were added to the conversation)

token_usage: TokenUsage

Execution Plan

class wayflowcore.planning.ExecutionPlan(plan=None)

Parameters:

plan (List[Task] | None) –

static from_str(plan_text)

Return type:

ExecutionPlan

Parameters:

plan_text (str) –

to_str()

Return type:

str

class wayflowcore.planning.Task(id, description, status=TaskStatus.PENDING, tool=None)

Parameters:

• id (str) –

• description (str) –

• status (TaskStatus) –

• tool (str | None) –

description: str

static from_str(line)

Return type:

Optional[Task]

Parameters:

line (str) –

id: str

status: TaskStatus = 'PENDING'

to_str()

Return type:

str

tool: Optional[str] = None

class wayflowcore.planning.TaskStatus(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Status of a task

CANCELLED = 'CANCELLED'

ERROR = 'ERROR'

IN_PROGRESS = 'IN_PROGRESS'

NEEDS_REFINEMENT = 'NEEDS_REFINEMENT'

PENDING = 'PENDING'

SUCCESS = 'SUCCESS'