Upload 2 files

app.py

@@ -78,7 +78,6 @@ st.markdown("""
 </ul>
 <a href="https://docs.google.com/spreadsheets/d/1YFuE3ZC31QIGy0YLNK_2v89y0NbektheXXI1QDNA3Ng/edit?usp=sharing" target="_blank">Check the template from here</a>            
 <br>
-
 """,unsafe_allow_html=True)
 st.markdown("""
 <br>
@@ -93,7 +92,6 @@ st.markdown("-----------------------------------------------------")
 st.markdown("""
     <h2 style='color: navy;'>Sales Core team - Apollo -</h2>
     <h3 style='color: darkslategray;'>Data Processing Functions</h3>
-
     <h4 style='color: darkcyan;'>Company-Specific Client Function</h4>
     <p style='color: slategray;'>Upload a CSV with company names and websites.</p>
     <ul>
@@ -110,7 +108,6 @@ st.markdown("""
         </ul>
       </li>
     </ul>
-
     <h4 style='color: darkcyan;'>User-Specific Client Function</h4>
     <p style='color: slategray;'>Upload a CSV with personal and company information.</p>
     <ul>
@@ -127,7 +124,6 @@ st.markdown("""
         </ul>
       </li>
     </ul>
-
     <h4 style='color: darkcyan;'>Both Features Function</h4>
     <p style='color: slategray;'>Combine user and company-specific data processing.</p>
     <ul>
@@ -164,5 +160,4 @@ st.markdown(
     <img src="{logo_url}" class="logo">
     """,
     unsafe_allow_html=True,
-)
-
+)

clients.py

@@ -2,7 +2,6 @@
 # -*- coding: utf-8 -*-
 """
 Created on Mon Jan  1 11:20:18 2024
-
 @author: mohanadafiffy
 """
 import os 
@@ -10,7 +9,8 @@ import streamlit as st
 import pandas as pd
 import requests
 import os
-
+from dotenv import load_dotenv 
+load_dotenv()
 host=os.getenv("backend")
 
 CompanyBackendService=host+'/receive_companies/'
@@ -25,7 +25,6 @@ def add_https_to_urls(df, column_name):
     Adds 'https://' to URLs in the specified column of a DataFrame if they don't already start with a valid protocol.
     Corrects URLs starting with 'http:/' or 'https:/'.
     Handles missing values, trims whitespace, and is case-insensitive.
-
     Parameters:
     df (pandas.DataFrame): The DataFrame containing the URLs.
     column_name (str): The name of the column with URLs.
@@ -75,7 +74,12 @@ def CompanySpecificClient(email_receiver):
                     company_column= st.selectbox("Select the column for Company Name for Emails:", all_columns,key="CompanyName")
                 else:
                     company_column = 'Company Name for Emails'
-                    
+
+                if 'Apollo description' not in df.columns:
+                    all_columns = df.columns.tolist()
+                    Apollo_description= st.selectbox("Select the column for Apollo description:", all_columns,key="ApolloDescription")
+                else:
+                    Apollo_description = 'Apollo description'                    
                 if opt_out_scraping:
                     if 'Company Description' not in df.columns:
                         all_columns = df.columns.tolist()
@@ -89,8 +93,6 @@ def CompanySpecificClient(email_receiver):
             except Exception as E :
                 st.error("An error occured while processing the file")
        
-            # Fetch the filtered data
-            
                 
             
         prompt_notes= st.text_input("If applicable please mention the network name",key="CompanyPromptNotes")
@@ -108,14 +110,14 @@ def CompanySpecificClient(email_receiver):
         df = input_data_companies
         if not opt_out_scraping:
             df[website_column] = df[website_column].astype(str)
-            df=df[[website_column,company_column]]
-            df.columns = ["Website","Company Name for Emails"]
+            df=df[[website_column,company_column,Apollo_description]]
+            df.columns = ["Website","Company Name for Emails","Apollo description"]
             df = df.drop_duplicates(subset="Website", keep='first')
             df = df.dropna().loc[~(df == '').all(axis=1)]
         else:
             df[website_column] = df[website_column].astype(str)
-            df=df[[website_column,company_column,"scraped_content"]]
-            df.columns = ["Website","Company Name for Emails","scraped_content"]
+            df=df[[website_column,company_column,Apollo_description,"scraped_content"]]
+            df.columns = ["Website","Company Name for Emails","Apollo description","scraped_content"]
             df = df.drop_duplicates(subset="Website", keep='first')
             df = df.dropna().loc[~(df == '').all(axis=1)]
             
@@ -500,4 +502,4 @@ def BH_industry(email_receiver,calendly_link,sender_name):
             st.info(f"We're processing your request. You can close the app now. An email will be sent to {email_receiver} once the process is finished.")
         else:
             st.error("Data transmission failed. Please verify that your file contains the labels 'Company Website' and 'Company Name'. Additionally, ensure that your file is valid and contains records and try again , if the problem persists please contact us at mohanad@omdena.com") 
-    return None             
+    return None