Message#

1. Concept#

The BaseMessage class is the base class for message objects used in the CAMEL chat system. It is designed to provide a consistent structure for the messages in the system and allow for easy conversion between different message types.

All the codes are also available on colab notebook here.

2. Get Started#

2.1 Creating a `BaseMessage` Instance#

To create a BaseMessage instance, you need to provide the following arguments:

role_name: The name of the user or assistant role.
role_type: The type of role, either RoleType.ASSISTANT or RoleType.USER.
meta_dict: An optional metadata dictionary for the message.
content: The content of the message.

Below are optional arguments you can pass:

video_bytes: Optional bytes of a video associated with the message.
image_list: Optional list of PIL Image objects associated with the message.
image_detail: Detail level of the images associated with the message. Default is “auto”.
video_detail: Detail level of the videos associated with the message. Default is “low”.

Here’s an example of creating a BaseMessage instance:

from camel.messages import BaseMessage
from camel.types import RoleType

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

Additionally, the BaseMessage class provides class methods to easily create user and assistant agent messages:

Creating a user agent message:

from camel.messages import BaseMessage

user_message = BaseMessage.make_user_message(
    role_name="user_name", 
    content="test content for user",
)

Creating an assistant agent message:

from camel.messages import BaseMessage

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

2.2 Using the Methods of the `BaseMessage` Class#

The BaseMessage class offers several methods:

Creating a new instance with updated content:

new_message = message.create_new_instance("new test content")
print(isinstance(new_message, BaseMessage))
>>> True

Converting to an OpenAIMessage object:

openai_message = message.to_openai_message(role_at_backend=OpenAIBackendRole.USER)
print(openai_message == {"role": "user", "content": "test content"})
>>> True

Converting to an OpenAISystemMessage object:

openai_system_message = message.to_openai_system_message()
print(openai_system_message == {"role": "system", "content": "test content"})
>>> True

Converting to an OpenAIUserMessage object:

openai_user_message = message.to_openai_user_message()
print(openai_user_message == {"role": "user", "content": "test content"})
>>> True

Converting to an OpenAIAssistantMessage object:

openai_assistant_message = message.to_openai_assistant_message()
print(openai_assistant_message == {"role": "assistant", "content": "test content"})
>>> True

Converting to a dictionary:

message_dict = message.to_dict()
print(message_dict == {
    "role_name": "test_user",
    "role_type": "USER",
    "content": "test content"
})
>>> True

These methods allow you to convert a BaseMessage instance into different message types depending on your needs.

3. Give `BaseMessage` to `ChatAgent`#

from io import BytesIO

import requests
from PIL import Image

from camel.agents import ChatAgent
from camel.messages import BaseMessage
# URL of the image
url = "https://raw.githubusercontent.com/camel-ai/camel/master/misc/logo_light.png"
response = requests.get(url)
img = Image.open(BytesIO(response.content))

# Define system message
sys_msg = BaseMessage.make_assistant_message(
    role_name="Assistant",
    content="You are a helpful assistant.",
)

# Set agent
camel_agent = ChatAgent(system_message=sys_msg)

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

# Get response information
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.

4. Conclusion#

In this session, we introduced the BaseMessage class and its conversion to different types of messages. These components play essential roles in the CAMEL chat system, facilitating the creation, management, and interpretation of messages with clarity.

Message

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