from llmlingua import PromptCompressor

compressor = PromptCompressor(
    model_name="microsoft/llmlingua-2-bert-base-multilingual-cased-meetingbank",
    use_llmlingua2=True
)

original_prompt = """John: So, um, I've been thinking about the project, you know, and I believe we need to, uh, make some changes. I mean, we want the project to succeed, right? So, like, I think we should consider maybe revising the timeline.

Sarah: I totally agree, John. I mean, we have to be realistic, you know. The timeline is, like, too tight. You know what I mean? We should definitely extend it.

"""

results = compressor.compress_prompt_llmlingua2(
    original_prompt,
    rate=0.6,
    force_tokens=['\n', '.', '!', '?', ','],
    chunk_end_tokens=['.', '\n'],
    return_word_label=True,
    drop_consecutive=True
)

print(results.keys())
print(f"Compressed prompt: {results['compressed_prompt']}")