agentscope.service.text_processing.summarization module

Service for text processing

agentscope.service.text_processing.summarization.summarization(model: ModelWrapperBase, text: str, system_prompt: str = '\nYou are a helpful agent to summarize the text.\nYou need to keep all the key information of the text in the summary.\n', max_return_token: int = -1, token_limit_prompt: str = '\nSummarize the text after TEXT in less than {} tokens:\n') → ServiceResponse[source]

Summarize the input text.

Summarization function (Notice: current version of token limitation is built with Open AI API)

Parameters:

model (ModelWrapperBase) – Model used to summarize provided text.
text (str) – Text to be summarized by the model.
system_prompt (str, defaults to _DEFAULT_SYSTEM_PROMPT) – Prompts as instruction for the system, will be as an instruction for the model.
max_return_token (int, defaults to -1) – Whether provide additional prompting instruction to limit the number of tokens in summarization returned by the model.
token_limit_prompt (str, defaults to _DEFAULT_TOKEN_LIMIT_PROMPT) – Prompt to instruct the model follow token limitation.

Returns:

If the model successfully summarized the text, and the summarization satisfies the provided token limitation, return ServiceResponse with ServiceExecStatus.SUCCESS; otherwise return ServiceResponse with ServiceExecStatus.ERROR (if the summary is return successfully but exceed the token limits, the content contains the summary as well).

Return type:

ServiceResponse

Example:

The default message with text to be summarized:

[
    {
        "role": "system",
        "name": "system",
        "content": "You are a helpful agent to summarize the text.\
        You need to keep all the key information of the text in the\
        summary."
    },
    {
        "role": "user",
        "name": "user",
        "content": text
    },
]

Messages will be processed by model.format() before feeding to models.