What is BaseMessage?

The BaseMessage class is the backbone for all message objects in the CAMEL chat system. It offers a consistent structure for agent communication and easy conversion between message types.
Explore and run every code sample directly in this Colab notebook.

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Creating a `BaseMessage`

To create a BaseMessage instance, supply these arguments:
  • role_name: Name of the user or assistant
  • role_type: RoleType.ASSISTANT or RoleType.USER
  • content: The actual message text
  • meta_dict (optional): Additional metadata
  • video_bytes (optional): Attach video bytes
  • image_list (optional): List of PIL Image objects
  • image_detail (optional): Level of image detail (default: “auto”)
  • video_detail (optional): Level of video detail (default: “low”)
Example:
from camel.messages import BaseMessage
from camel.types import RoleType

message = BaseMessage(
role_name="test_user",
role_type=RoleType.USER,
content="test content"
)

Convenient Constructors

Easily create messages for user or assistant agents:
user_message = BaseMessage.make_user_message(
    role_name="user_name",
    content="test content for user",
)

assistant_message = BaseMessage.make_assistant_message(
    role_name="assistant_name",
    content="test content for assistant",
)

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Methods in the BaseMessage Class

Flexible Message Manipulation

The BaseMessage class lets you:
  • Create a new instance with updated content:
    new_message = message.create_new_instance(“new test content”)
  • Convert to OpenAI message formats:
    openai_message = message.to_openai_message(role_at_backend=OpenAIBackendRole.USER)
    openai_system_message = message.to_openai_system_message()
    openai_user_message = message.to_openai_user_message()
    openai_assistant_message = message.to_openai_assistant_message()
  • Convert to a Python dictionary:
    message_dict = message.to_dict()
These methods allow you to transform a BaseMessage into the right format for different LLM APIs and agent flows.

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Using BaseMessage with ChatAgent

Rich Message Example

You can send multimodal messages (including images) to your agents:
from io import BytesIO
import requests
from PIL import Image

from camel.agents import ChatAgent
from camel.messages import BaseMessage

# Download an image
url = "https://raw.githubusercontent.com/camel-ai/camel/master/misc/logo_light.png"
img = Image.open(BytesIO(requests.get(url).content))

# Build system and user messages
sys_msg = BaseMessage.make_assistant_message(
    role_name="Assistant",
    content="You are a helpful assistant.",
)

user_msg = BaseMessage.make_user_message(
    role_name="User", content="what's in the image?", image_list=[img]
)

# Create agent and send message
camel_agent = ChatAgent(system_message=sys_msg)
response = camel_agent.step(user_msg)
print(response.msgs[0].content)
The image features a logo for “CAMEL-AI.” It includes a stylized purple camel graphic alongside the text “CAMEL-AI,” which is also in purple. The design appears modern and is likely related to artificial intelligence.

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Conclusion

Summary

The BaseMessage class is essential for structured, clear, and flexible communication in the CAMEL-AI ecosystem—making it simple to create, convert, and handle messages across any workflow.
For further details, check out the key modules documentation.