Create app.py

app.py

@@ -0,0 +1,67 @@
+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)