Code Editor for app.py

import streamlit as st
import pandas as pd
from scholarly import scholarly
import datetime

st.title("Research Paper Finder")

# Input fields
keywords = st.text_input("Enter keywords (separate multiple keywords with commas)")
journals = st.text_input("Enter journal names (separate multiple journals with commas)")

if st.button("Search Papers"):
    if keywords and journals:
        st.info("Searching for papers... This may take a few moments.")
        
        # Process inputs
        keyword_list = [k.strip() for k in keywords.split(",")]
        journal_list = [j.strip() for j in journals.split(",")]
        
        # Initialize results list
        results = []
        
        # Search for each keyword
        for keyword in keyword_list:
            search_query = scholarly.search_pubs(keyword)
            
            # Get first 10 results for each keyword
            try:
                for i in range(10):
                    publication = next(search_query)
                    
                    # Check if the publication is from one of the specified journals
                    pub_journal = publication.get('journal', '').lower()
                    if any(journal.lower() in pub_journal for journal in journal_list):
                        # Extract relevant information
                        result = {
                            'Title': publication.get('title', 'N/A'),
                            'Authors': ', '.join(publication.get('author', [])),
                            'Journal': publication.get('journal', 'N/A'),
                            'Year': publication.get('year', 'N/A'),
                            'Conference': publication.get('conference', 'N/A'),
                            'Link': publication.get('url', 'N/A')
                        }
                        results.append(result)
            except StopIteration:
                continue
        
        if results:
            # Create DataFrame
            df = pd.DataFrame(results)
            
            # Display results in the app
            st.subheader("Search Results")
            st.dataframe(df)
            
            # Create Excel file
            excel_file = df.to_excel(index=False)
            
            # Generate timestamp for filename
            timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
            filename = f"research_papers_{timestamp}.xlsx"
            
            # Save to Excel and provide download button
            df.to_excel(filename, index=False)
            
            with open(filename, 'rb') as f:
                st.download_button(
                    label="Download Results as Excel",
                    data=f,
                    file_name=filename,
                    mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                )
        else:
            st.warning("No matching papers found in the specified journals.")
    else:
        st.error("Please enter both keywords and journal names.")