ChatMessage
ChatMessage
is the central abstraction to represent a message for a LLM. It contains role, metadata and several types of content, including text, tool calls and tool calls results.
To create a ChatMessage
instance, use from_user
, from_system
, from_assistant
, and from_tool
class methods.
The content of the ChatMessage
can then be inspected using the text
, texts
, tool_call
, tool_calls
, tool_call_result
, and tool_call_results
properties.
If you are looking for the details of this data class methods and parameters, head over to our API documentation.
Types of Content
ChatMessage
currently supports TextContent
, ToolCall
and ToolCallResult
types of content:
@dataclass
class TextContent:
"""
The textual content of a chat message.
:param text: The text content of the message.
"""
text: str
@dataclass
class ToolCall:
"""
Represents a Tool call prepared by the model, usually contained in an assistant message.
:param tool_name: The name of the Tool to call.
:param arguments: The arguments to call the Tool with.
:param id: The ID of the Tool call.
"""
tool_name: str
arguments: Dict[str, Any]
id: Optional[str] = None # noqa: A003
@dataclass
class ToolCallResult:
"""
Represents the result of a Tool invocation.
:param result: The result of the Tool invocation.
:param origin: The Tool call that produced this result.
:param error: Whether the Tool invocation resulted in an error.
"""
result: str
origin: ToolCall
error: bool
Working with a ChatMessage
The following examples demonstrate how to create a ChatMessage
and inspect its properties.
from_user with TextContent
from haystack.dataclasses import ChatMessage
user_message = ChatMessage.from_user("What is the capital of Australia?")
print(user_message)
>>> ChatMessage(
>>> _role=<ChatRole.USER: 'user'>,
>>> _content=[TextContent(text='What is the capital of Australia?')],
>>> _name=None,
>>> _meta={}
>>>)
print(user_message.text)
>>> What is the capital of Australia?
print(user_message.texts)
>>> ['What is the capital of Australia?']
from_assistant with TextContent
from haystack.dataclasses import ChatMessage
assistant_message = ChatMessage.from_assistant("How can I assist you today?")
print(assistant_message)
>>> ChatMessage(
>>> _role=<ChatRole.ASSISTANT: 'assistant'>,
>>> _content=[TextContent(text='How can I assist you today?')],
>>> _name=None,
>>> _meta={}
>>>)
print(assistant_message.text)
>>> How can I assist you today?
print(assistant_message.texts)
>>> ['How can I assist you today?']
from_assistant with ToolCall
from haystack.dataclasses import ChatMessage, ToolCall
tool_call = ToolCall(tool_name="weather_tool", arguments={"location": "Rome"})
assistant_message_w_tool_call = ChatMessage.from_assistant(tool_calls=[tool_call])
print(assistant_message_w_tool_call)
>>> ChatMessage(
>>> _role=<ChatRole.ASSISTANT: 'assistant'>,
>>> _content=[ToolCall(tool_name='weather_tool', arguments={'location': 'Rome'}, id=None)],
>>> _name=None,
>>> _meta={}
>>>)
print(assistant_message_w_tool_call.text)
>>> None
print(assistant_message_w_tool_call.texts)
>>> []
print(assistant_message_w_tool_call.tool_call)
>>> ToolCall(tool_name='weather_tool', arguments={'location': 'Rome'}, id=None)
print(assistant_message_w_tool_call.tool_calls)
>>> [ToolCall(tool_name='weather_tool', arguments={'location': 'Rome'}, id=None)]
print(assistant_message_w_tool_call.tool_call_result)
>>> None
print(assistant_message_w_tool_call.tool_call_results)
>>> []
from_tool
from haystack.dataclasses import ChatMessage
tool_message = ChatMessage.from_tool(tool_result="temperature: 25°C", origin=tool_call, error=False)
print(tool_message)
>>> ChatMessage(
>>> _role=<ChatRole.TOOL: 'tool'>,
>>> _content=[ToolCallResult(
>>> result='temperature: 25°C',
>>> origin=ToolCall(tool_name='weather_tool', arguments={'location': 'Rome'}, id=None),
>>> error=False
>>> )],
>>> _name=None,
>>> _meta={}
>>>)
print(tool_message.text)
>>> None
print(tool_message.texts)
>>> []
print(tool_message.tool_call)
>>> None
print(tool_message.tool_calls)
>>> []
print(tool_message.tool_call_result)
>>> ToolCallResult(
>>> result='temperature: 25°C',
>>> origin=ToolCall(tool_name='weather_tool', arguments={'location': 'Rome'}, id=None),
>>> error=False
>>> )
print(tool_message.tool_call_results)
>>> [
>>> ToolCallResult(
>>> result='temperature: 25°C',
>>> origin=ToolCall(tool_name='weather_tool', arguments={'location': 'Rome'}, id=None),
>>> error=False
>>> )
>>> ]
Migrating from Legacy ChatMessage (before v2.9)
In Haystack 2.9, we updated the ChatMessage
data class for greater flexibility and support for multiple content types: text, tool calls, and tool call results.
There are some breaking changes involved, so we recommend reviewing this guide to migrate smoothly.
Creating a ChatMessage
You can no longer directly initialize ChatMessage
using role
, content
, and meta
.
- Use the following class methods instead:
from_assistant
,from_user
,from_system
, andfrom_tool
. - Replace the
content
parameter withtext
.
from haystack.dataclasses import ChatMessage
# LEGACY - DOES NOT WORK IN 2.9.0
message = ChatMessage(role=ChatRole.USER, content="Hello!")
# Use the class method instead
message = ChatMessage.from_user("Hello!")
Accessing ChatMessage Attributes
- The legacy
content
attribute is now internal (_content
). - Inspect
ChatMessage
attributes using the following properties:role
meta
name
text
andtexts
tool_call
andtool_calls
tool_call_result
andtool_calls_results
from haystack.dataclasses import ChatMessage
message = ChatMessage.from_user("Hello!")
# LEGACY - DOES NOT WORK IN 2.9.0
print(message.content)
# Use the appropriate property instead
print(message.text)
Updated 22 days ago