agentchat.contrib.capabilities.text_compressors

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TextCompressor

class TextCompressor(Protocol)

Defines a protocol for text compression to optimize agent interactions.

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compress_text

def compress_text(text: str, **compression_params) -> dict[str, Any]

This method takes a string as input and returns a dictionary containing the compressed text and other relevant information. The compressed text should be stored under the ‘compressed_text’ key in the dictionary. To calculate the number of saved tokens, the dictionary should include ‘origin_tokens’ and ‘compressed_tokens’ keys.

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LLMLingua

class LLMLingua()

Compresses text messages using LLMLingua for improved efficiency in processing and response generation.

NOTE: The effectiveness of compression and the resultant token savings can vary based on the content of the messages and the specific configurations used for the PromptCompressor.

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__init__

def __init__(prompt_compressor_kwargs: dict = dict(
    model_name="microsoft/llmlingua-2-bert-base-multilingual-cased-meetingbank",
    use_llmlingua2=True,
    device_map="cpu",
),
             structured_compression: bool = False) -> None

Arguments:

• prompt_compressor_kwargs dict - A dictionary of keyword arguments for the PromptCompressor. Defaults to a dictionary with model_name set to “microsoft/llmlingua-2-bert-base-multilingual-cased-meetingbank”, use_llmlingua2 set to True, and device_map set to “cpu”.
• structured_compression bool - A flag indicating whether to use structured compression. If True, the structured_compress_prompt method of the PromptCompressor is used. Otherwise, the compress_prompt method is used. Defaults to False. dictionary.

Raises:

• ImportError - If the llmlingua library is not installed.