Update app.py

app.py

@@ -1,153 +1,151 @@
-import streamlit as st 
-st.info("weekend resources saving , if you want a list urgently contact Mohanad")
-# import streamlit as st
-# import pandas as pd
-# import requests
-# import os
+import streamlit as st
+import pandas as pd
+import requests
+import os
 
-# def main():
+def main():
 
-#     BackendService=os.getenv("backend") 
-#     input_data=None    
-#     submitted=None
-#     # Wrap everything inside a form
-#     with st.sidebar:
+    BackendService=os.getenv("backend") 
+    input_data=None    
+    submitted=None
+    # Wrap everything inside a form
+    with st.sidebar:
        
-#         uploaded_file = st.file_uploader("Kindly upload a CSV file that includes the names and websites of the companies", type=["csv"])
-#         opt_out_scraping = st.checkbox("Opt out of scraping")
-#         if uploaded_file is not None:
-#             try:
-#                 # Detect file type and read accordingly
-#                 file_type = uploaded_file.name.split('.')[-1]
-#                 if file_type == 'csv':
-#                     df = pd.read_csv(uploaded_file)
-#                 elif file_type == 'xlsx':
-#                     df = pd.read_excel(uploaded_file)
+        uploaded_file = st.file_uploader("Kindly upload a CSV file that includes the names and websites of the companies", type=["csv"])
+        opt_out_scraping = st.checkbox("Opt out of scraping")
+        if uploaded_file is not None:
+            try:
+                # Detect file type and read accordingly
+                file_type = uploaded_file.name.split('.')[-1]
+                if file_type == 'csv':
+                    df = pd.read_csv(uploaded_file)
+                elif file_type == 'xlsx':
+                    df = pd.read_excel(uploaded_file)
     
-#                # Limiting the dataframe for processing
+               # Limiting the dataframe for processing
     
-#                 # Check if 'Website' column exists
-#                 if 'Website' not in df.columns:
-#                     all_columns = df.columns.tolist()
-#                     website_column  = st.selectbox("Select the column for Website:", all_columns)
-#                 else:
-#                     website_column  = 'Website'
+                # Check if 'Website' column exists
+                if 'Website' not in df.columns:
+                    all_columns = df.columns.tolist()
+                    website_column  = st.selectbox("Select the column for Website:", all_columns)
+                else:
+                    website_column  = 'Website'
                     
                     
-#                     # Check if 'Company Name for Emails' column exists
-#                 if 'Company Name for Emails' not in df.columns:
-#                     all_columns = df.columns.tolist()
-#                     company_column= st.selectbox("Select the column for Company Name for Emails:", all_columns)
-#                 else:
-#                     company_column = 'Company Name for Emails'
+                    # Check if 'Company Name for Emails' column exists
+                if 'Company Name for Emails' not in df.columns:
+                    all_columns = df.columns.tolist()
+                    company_column= st.selectbox("Select the column for Company Name for Emails:", all_columns)
+                else:
+                    company_column = 'Company Name for Emails'
                     
-#                 if opt_out_scraping:
-#                     if 'Description' not in df.columns:
-#                         all_columns = df.columns.tolist()
-#                         description_column = st.selectbox("Select the column for Description:", all_columns)
-#                         df.rename(columns={description_column: 'scraped_content'}, inplace=True)
-#                     else:
-#                         df.rename(columns={'Description': 'scraped_content'}, inplace=True)     
+                if opt_out_scraping:
+                    if 'Description' not in df.columns:
+                        all_columns = df.columns.tolist()
+                        description_column = st.selectbox("Select the column for Description:", all_columns)
+                        df.rename(columns={description_column: 'scraped_content'}, inplace=True)
+                    else:
+                        df.rename(columns={'Description': 'scraped_content'}, inplace=True)     
                     
-#                 input_data=df  
+                input_data=df  
                 
-#             except Exception as E :
-#                 st.error("An error occured while processing the file")
+            except Exception as E :
+                st.error("An error occured while processing the file")
        
-#         with st.form(key='my_form'):
-#             # Fetch the filtered data
-#             prompt_notes= st.text_input("If applicable please mention the network name")
+        with st.form(key='my_form'):
+            # Fetch the filtered data
+            prompt_notes= st.text_input("If applicable please mention the network name")
             
-#            # List of predefined email addresses
-#             email_options = [
-#                 "[email protected]",
-#                 "[email protected]",
-#                 "[email protected]",
-#                 "[email protected]",
-#                 "[email protected]",
-#                 "[email protected]",
-#                 "[email protected]"
-#             ]
+           # List of predefined email addresses
+            email_options = [
+                "[email protected]",
+                "[email protected]",
+                "[email protected]",
+                "[email protected]",
+                "[email protected]",
+                "[email protected]",
+                "[email protected]"
+            ]
             
-#             # Streamlit select box for choosing an email
-#             email_receiver = st.selectbox("Please select an email address", email_options)
+            # Streamlit select box for choosing an email
+            email_receiver = st.selectbox("Please select an email address", email_options)
             
 
-#     # If the button is clicked, it will return True for this run
-#             button_clicked = st.form_submit_button("Submit")
+    # If the button is clicked, it will return True for this run
+            button_clicked = st.form_submit_button("Submit")
             
-#             # 2. Update session state for the button
-#             if button_clicked:
-#                 submitted = True
-#                 # Set the session state to the new value
-#                 prompt_notes = prompt_notes 
-# # 3. Use the session state variable to determine if the button was previously clicked
-#     if submitted and input_data is not None:
-#         df = input_data
-#         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.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.drop_duplicates(subset="Website", keep='first')
-#             df = df.dropna().loc[~(df == '').all(axis=1)]
+            # 2. Update session state for the button
+            if button_clicked:
+                submitted = True
+                # Set the session state to the new value
+                prompt_notes = prompt_notes 
+# 3. Use the session state variable to determine if the button was previously clicked
+    if submitted and input_data is not None:
+        df = input_data
+        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.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.drop_duplicates(subset="Website", keep='first')
+            df = df.dropna().loc[~(df == '').all(axis=1)]
             
             
-#         st.write(df)
-#         # Convert DataFrame to CSV for transmission
-#         csv = df.to_csv(index=False)
+        st.write(df)
+        # Convert DataFrame to CSV for transmission
+        csv = df.to_csv(index=False)
     
-#         # Construct the data to send
-#         data_to_send = {"prompt_notes": prompt_notes, "dataframe": csv,"email_receiver":email_receiver}
+        # Construct the data to send
+        data_to_send = {"prompt_notes": prompt_notes, "dataframe": csv,"email_receiver":email_receiver}
     
-#         # Sending the POST request to FastAPI
-#         response = requests.post(BackendService, json=data_to_send)
+        # Sending the POST request to FastAPI
+        response = requests.post(BackendService, json=data_to_send)
     
-#         if response.status_code == 200:
-#             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 [email protected]")
+        if response.status_code == 200:
+            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 [email protected]")
             
 
-# if __name__ == "__main__":
-#     st.markdown(
-#     """
-#     <style>
-#     .higher-title {
-#         font-size:35px !important;
-#         color: #4A90E2;  /* Shade of blue */
-#         text-align: center;
-#         font-weight: bold;
-#         margin-top: -20px;  /* Adjust this value to control the height */
-#     }
-#     </style>
-#     """, 
-#     unsafe_allow_html=True,
-# )
+if __name__ == "__main__":
+    st.markdown(
+    """
+    <style>
+    .higher-title {
+        font-size:35px !important;
+        color: #4A90E2;  /* Shade of blue */
+        text-align: center;
+        font-weight: bold;
+        margin-top: -20px;  /* Adjust this value to control the height */
+    }
+    </style>
+    """, 
+    unsafe_allow_html=True,
+)
 
-#     st.markdown('<p class="higher-title">SalesIntel AI</p>', unsafe_allow_html=True)
+    st.markdown('<p class="higher-title">SalesIntel AI</p>', unsafe_allow_html=True)
     
     
     
-#     logo_url = "https://i.imgur.com/WYnv26e.jpeg"  # Replace this with your image's direct URL
-#     st.markdown(
-#         f"""
-#         <style>
-#         .logo {{
-#             position: fixed;
-#             bottom: 5px;
-#             right: 5px;
-#             width: 100px;  # Adjust width as needed
-#         }}
-#         </style>
-#         <img src="{logo_url}" class="logo">
-#         """,
-#         unsafe_allow_html=True,
-#     )
-#     main()
+    logo_url = "https://i.imgur.com/WYnv26e.jpeg"  # Replace this with your image's direct URL
+    st.markdown(
+        f"""
+        <style>
+        .logo {{
+            position: fixed;
+            bottom: 5px;
+            right: 5px;
+            width: 100px;  # Adjust width as needed
+        }}
+        </style>
+        <img src="{logo_url}" class="logo">
+        """,
+        unsafe_allow_html=True,
+    )
+    main()