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| #!/usr/bin/env python | |
| # coding: utf-8 | |
| # In[1]: | |
| import gradio as gr | |
| from transformers import pipeline | |
| import requests | |
| from bs4 import BeautifulSoup | |
| # In[9]: | |
| pipe = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6") | |
| def get_abstract(url): | |
| page = requests.get(url) | |
| soup = BeautifulSoup(page.content, "html.parser") | |
| abstract = soup.find(id="eng-abstract").text | |
| return abstract | |
| def summarize(input): | |
| abstract = get_abstract(input) | |
| summary = pipe(abstract) | |
| return summary[0]["summary_text"] | |
| demo = gr.Interface( | |
| fn=summarize, | |
| inputs=gr.Textbox(placeholder="PubMed URL", label="PubMed URL"), | |
| outputs=gr.Textbox(placeholder="Your Summary will appear here", label="Summary"), | |
| title="PubMed Summarizer📝", | |
| examples=["https://pubmed.ncbi.nlm.nih.gov/36258852/", "https://pubmed.ncbi.nlm.nih.gov/34747661/"]) | |
| demo.launch() | |
| # In[ ]: | |