agentscope.models.model module

The model wrapper base class.

class ModelWrapperBase(config_name: str | None = None, model_name: str | None = None, **kwargs: Any)

Bases: object

The base class for model wrapper.

format(*args: Msg | Sequence[Msg]) → List[dict] | str

Format the input messages into the format that the model API required.

static format_for_common_chat_models(*args: Msg | Sequence[Msg]) → List[dict]

A common format strategy for chat models, which will format the input messages into a system message (if provided) and a user message.

Note this strategy maybe not suitable for all scenarios, and developers are encouraged to implement their own prompt engineering strategies.

The following is an example:

prompt1 = model.format(
    Msg("system", "You're a helpful assistant", role="system"),
    Msg("Bob", "Hi, how can I help you?", role="assistant"),
    Msg("user", "What's the date today?", role="user")
)

prompt2 = model.format(
    Msg("Bob", "Hi, how can I help you?", role="assistant"),
    Msg("user", "What's the date today?", role="user")
)

The prompt will be as follows:

# prompt1
[
    {
        "role": "system",
        "content": "You're a helpful assistant"
    },
    {
        "role": "user",
        "content": (
            "## Conversation History\n"
            "Bob: Hi, how can I help you?\n"
            "user: What's the date today?"
        )
    }
]

# prompt2
[
    {
        "role": "user",
        "content": (
            "## Conversation History\n"
            "Bob: Hi, how can I help you?\n"
            "user: What's the date today?"
        )
    }
]

Parameters:

args (Union[Msg, Sequence[Msg]]) – The input arguments to be formatted, where each argument should be a Msg object, or a list of Msg objects. In distribution, placeholder is also allowed.

Returns:

The formatted messages.

Return type:

List[dict]

config_name: str

The name of the model configuration.

model_name: str

The name of the model, which is used in model api calling.

model_type: str

The type of the model wrapper, which is to identify the model wrapper class in model configuration.