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| import gradio as gr | |
| from memsum import MemSum | |
| import re | |
| model_path = "model/MemSum_Final/model.pt" | |
| summarizer = MemSum(model_path, "model/glove/vocabulary_200dim.pkl") | |
| def preprocess(text): | |
| text = text.replace('- ', '') | |
| text = re.sub(r'[\n\s]+', ' ', text) | |
| return text | |
| sent_tokenize = lambda txt: re.split(r'(?<=[.!?])\s(?=[A-Z])', txt) | |
| def summarize(text): | |
| text = sent_tokenize( preprocess(text) ) | |
| summary = "\n\n".join( summarizer.summarize(text) ) | |
| return summary | |
| input = gr.Textbox(label="Input text", placeholder="Court opinion text goes here...") | |
| output = gr.Textbox(label="Summary", placeholder="Output summary will appear here...") | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| # Legal MemSum Demo | |
| Copy an opinion text from your favorite source and paste it into the textbox below. | |
| """) | |
| gr.Interface(fn=summarize, inputs=input, outputs=output) | |
| gr.Markdown( | |
| """ | |
| Note: The version hosted here on Huggingface uses a different tokenizer than in our Github repository. We recommend using that | |
| https://github.com/bauerem/legal_memsum . <br> | |
| Please reach out to us if you are interested in a modified version of this. | |
| """) | |
| demo.launch() |