app.py

import logging
import pandas as pd
import gradio as gr
import ipywidgets as widgets
from pymed import PubMed

def search_pubmed(search_term, keywords, max_results):
    # Validate the input
    if max_results < 1:
        raise ValueError("Max Results must be a positive integer")
    
    # Connect to PubMed database
    pubmed = PubMed(tool="MyTool", email="aalamel@clemson.edu")
    results = pubmed.query(search_term, max_results=max_results)
    
    # Prepare the lists to store article information
    articleList = []
    articleInfo = []

    # Try to retrieve the articles and process them
    try:
        for article in results:
            articleDict = article.toDict()
            articleList.append(articleDict)
    except Exception as e:
        # Log the error if it occurs
        logging.error("Error while processing articles: {}".format(e))
        raise

    # Store the information of each article in articleInfo
    for article in articleList:
        pubmedId = article['pubmed_id'].partition('\n')[0]
        articleInfo.append({u'pubmed_id': pubmedId,
                          u'title': article['title'],
                          u'abstract': article['abstract']
                          })

    # Convert the article information to a Pandas dataframe
    cardio_abstract = pd.DataFrame.from_dict(articleInfo)
    
    # Filter the dataframe based on the selected keywords
    cardio_abstract = cardio_abstract[keywords]
    
    # Return the filtered dataframe
    return cardio_abstract

def download_csv(b):
    download_button.description = "Downloading..."
    download_button.disabled = True
    dataframe.to_csv("pubmed_results.csv", index=False)
    download_button.description = "Download CSV"
    download_button.disabled = False

inputs = [gr.inputs.Textbox(label="Search Term"),
gr.inputs.Checkbox(["pubmed_id", "title", "abstract"], label="Keywords"),
gr.inputs.Slider(minimum=1, maximum=10000, default=100, label="Max Results")]

outputs = [gr.outputs.Dataframe(type="pandas")]

interface = gr.Interface(search_pubmed, inputs, outputs, title="PubMed Search")

result = interface.launch(share=True)
dataframe = result[0]

download_button = widgets.Button(description="Download CSV")
download_button.on_click(download_csv)
display(download_button)