snapshot

classes/Linkedin.py

@@ -138,7 +138,7 @@ class Linkedin:
         if  (self.linkedin_f or (self.linkedin_metrics and self.linkedin_metrics.name) or (self.linkedin_post and self.linkedin_post.name)) and session == "clicked":
                 try:
                         combined_text = ""
-                        with st.spinner('Uploading Linkedin Files...', show_time=True):
+                        with st.spinner('Linkedin...', show_time=True):
                             st.write('')
                             # INITIALIZING SESSIONS
                             #combined_text += f"Client Summary: {st.session_state.nature}\n"

classes/Off_Page.py

@@ -3,12 +3,14 @@ from urllib.parse import urlparse
 import streamlit as st
 import requests
 from dotenv import load_dotenv
+import os
 import time
 from helper.telemetry import collect_telemetry
 from helper.upload_File import uploadFile
 from helper.button_behaviour import hide_button, unhide_button
 from helper.initialize_analyze_session import initialize_analyze_session
 import pandas as pd
+import asyncio
 import json
 
 class SeoOffPageAnalyst:
@@ -30,10 +32,6 @@ class SeoOffPageAnalyst:
         #st.header(self.analyst_name)
         if 'off_page_file_uploaded' not in st.session_state:
             st.session_state['off_page_file_uploaded'] = ''
-        if 'website_audience' not in st.session_state:
-            st.session_state['website_audience'] = ''
-        if 'uploaded_files' not in st.session_state:
-            st.session_state['uploaded_files'] = ''
     
     def request_model(self, payload_txt, headers):
         response = requests.post(self.model_url, json=payload_txt, headers=headers)
@@ -52,95 +50,55 @@ class SeoOffPageAnalyst:
          session = st.session_state['analyze']
          if self.uploaded_files and session == 'clicked':
                     combined_text = ""
-                    website_audience = ""
-                    with st.spinner('Uploading Off Page...', show_time=True):
+                    with st.spinner('SEO Off Page Analyst...', show_time=True):
                         st.write('')
+                        for file_info in st.session_state['uploaded_files'].values():
+                            '''
+                            if file_info['type'] == 'pdf':
+                                combined_text += file_info['content'] + "\n"
+                            '''
                         try:
-                            for file_info in st.session_state['uploaded_files'].values():
-                                '''
-                                if file_info['type'] == 'pdf':
-                                    combined_text += file_info['content'] + "\n"
-                                '''
-                            try:
-                                if file_info['type'] == 'csv':                                    
-                                    # Load CSV
-                                    df = pd.read_csv(StringIO(file_info['content'].to_csv(index=True)))
+                            if file_info['type'] == 'csv':                                    
+                                # Load CSV
+                                df = pd.read_csv(StringIO(file_info['content'].to_csv(index=True)))
+                                
+                                # Count total rows
+                                num_rows = len(df)
+                                
+                                # Extract unique domains from 'Source url'
+                                df['Source Domain'] = df['Source url'].apply(lambda x: urlparse(x).netloc)
+                                unique_domains = df['Source Domain'].nunique()
                                     
-                                    # Count total rows
-                                    num_rows = len(df)
-                                    
-                                    # Extract unique domains from 'Source url'
-                                    df['Source Domain'] = df['Source url'].apply(lambda x: urlparse(x).netloc)
-                                    unique_domains = df['Source Domain'].nunique()
-                                        
-                                    combined_text += f"Total Backlinks Count: {num_rows}\n"
-                                    combined_text += f"Referring Domain: {unique_domains}"
-                                    #st.info("Backlinks - SEMRush Uploaded Successfuly", icon="ℹ️")
-                            except KeyError:
-                                st.info("Incorrect CSV format. Please upload a valid CSV file.")
-                                pass
-                            except UnboundLocalError:
-                                 pass
-                        except AttributeError:
-                                 pass
+                                combined_text += f"Total Backlinks Count: {num_rows}\n"
+                                combined_text += f"Referring Domain: {unique_domains}"
+                                st.info("Backlinks - SEMRush Uploaded Successfuly", icon="ℹ️")
                         except KeyError:
-                             pass
-                        '''
-                        try:
-                            # Check if upload_website_audience exists in session state and is a dictionary
-                            if 'upload_website_audience' in st.session_state and isinstance(st.session_state['upload_website_audience'], dict):
-                                for file_name, file_info in st.session_state['upload_website_audience'].items():
-                                    try:
-                                        if file_info['type'] == 'csv':
-                                            # Since file_info['content'] is already a DataFrame (from your earlier code)
-                                            # No need to convert back from string to DataFrame
-                                            df = file_info['content']
-                                            
-                                            # Process your DataFrame here
-                                            # Instead of reading from StringIO, just use the DataFrame directly
-                                            website_audience += f"Website Audience Acquisition {df}\n"
-                                            
-                                            #st.info("Website Audience Acquisition Uploaded Successfully", icon="ℹ️")
-                                    except KeyError:
-                                        pass
-                                        #st.info(f"Incorrect format for {file_name}. Please upload a valid CSV file.")
-                        except Exception as e:
-                            st.error(f"Error processing data: {str(e)}")
-                        
-                        '''
+                            st.info("Incorrect CSV format. Please upload a valid CSV file.")
                         # OUTPUT FOR SEO ANALYST
-
+                        payload_txt = {"question": combined_text}
+                        headers = {
+                            "Content-Type": "application/json",
+                            "x-api-key": f"{os.getenv('x-api-key')}"
+                        }
                         #result = self.request_model(payload_txt, headers)
                         
                         #end_time = time.time()
                         #time_lapsed = end_time - start_time
                         
-                        debug_info = {'data_field' : 'Backlinks', 'result': combined_text}
-                        debug_info_website_audience = {'data_field' : 'Website Audience Acquisition', 'result': website_audience}
+                        debug_info = {'data_field' : 'Backlinks', 'result': payload_txt}
                         #debug_info = {'url_uuid': self.model_url.split("-")[-1],'time_lapsed' : time_lapsed, 'files': [*st.session_state['uploaded_files']],'payload': payload_txt, 'result': result}
+                        collect_telemetry(debug_info)
                         
-                        if self.uploaded_files:
-                            st.session_state['off_page_file_uploaded'] = 'uploaded'
-                            collect_telemetry(debug_info)
-                        #if self.website_audience:
-                        #    st.session_state['website_audience'] = 'uploaded'
-                        #    collect_telemetry(debug_info_website_audience)
-
+                        st.session_state["off_page_file_uploaded"] = 'uploaded'
                         
                         #with st.expander("Debug information", icon="⚙"):
                         #    st.write(debug_info)
                         st.session_state['analyzing'] = False
-    
     def row1(self):
             #st.write(self.data_src)
             self.uploaded_files = st.file_uploader('Backlinks - SEMRush', type='csv', accept_multiple_files=True, key="seo_off")
-            #self.website_audience = st.file_uploader('Website Audience Acquisition - GA4', type='csv', accept_multiple_files=True, key="website_audiences")
-            #self.website_audience = st.text_input("Website Audience Acquisition:", placeholder='Enter Website Audience Acquisition')
-
             if self.uploaded_files:
                 upload.multiple_upload_file(self.uploaded_files)
-            #if self.website_audience:
-            #     upload.upload_website_audience(self.website_audience)
                 
             #st.write("") # FOR THE HIDE BUTTON
             #st.write("") # FOR THE HIDE BUTTON

classes/On_Page.py

@@ -84,7 +84,7 @@ class SeoOn:
                 if (self.first_meaningful_paint or self.uploaded_files) and session == 'clicked':
                     first_meaningful_paint = ""
                     crawl_file = ""
-                    with st.spinner('Uploading On Page...', show_time=True):
+                    with st.spinner('SEO On Page Analyst...', show_time=True):
                         st.write('')
                         '''
                         try:
@@ -119,8 +119,6 @@ class SeoOn:
                                         pass
                         except KeyError:
                             pass
-                        except AttributeError:
-                            pass
                         try:
                             first_meaningful_paint += f"\nFirst Meaningful Paint: {self.first_meaningful_paint}"
                         except KeyError:

classes/On_Page_Crawl.py

@@ -78,7 +78,7 @@ class SeoOnCrawl:
         session = st.session_state.analyze
         if self.uploaded_files and session == 'clicked':
                     combined_text = ""
-                    with st.spinner('Uploading Crawl File...', show_time=True):
+                    with st.spinner('SEO On Page Analyst...', show_time=True):
                         st.write('')
                         try:
                             for file_info in st.session_state['uploaded_files'].values():

classes/Seo.py

@@ -50,6 +50,43 @@ class Seo:
             st.session_state['df_traffic'] = ''
         if 'df_seo' not in st.session_state:
             st.session_state['df_seo'] = ''
+           
+    def request_model(self, payload_txt):
+        response = requests.post(self.model_url, json=payload_txt)
+        response.raise_for_status()
+        output = response.json()
+        
+        categories = []
+        current_footprint = []
+        number_of_backlinks = []
+
+        for key, value in output.items():
+            if key == 'json':
+                for item in value:
+                    categories.append(item.get('category', 'N/A').replace('_', ' ').title())
+                    current_footprint.append(item.get('current_footprint', 'N/A'))
+                    number_of_backlinks.append(item.get('best_of_breed_solution', 'N/A'))    
+
+        output = ""
+        for i in range(len(categories)):
+            output += f"\n\n---\n **Category:** {categories[i]}"
+            output += f"\n\n **Current Footprint:** {current_footprint[i]}\n\n"
+            output += f"**Number of Backlinks:** {number_of_backlinks[i]}"
+
+        data = {
+            "": [str(category) for category in categories],
+            "Current Footprint": [str(footprint) for footprint in current_footprint],
+            "Best of Breed Solutions": [str(backlink) for backlink in number_of_backlinks]
+        }
+        df_output = pd.DataFrame(data)
+        with st.expander("AI Analysis", expanded=True, icon="🤖"):
+            st.table(df_output.style.set_table_styles(
+                [{'selector': 'th:first-child, td:first-child', 'props': [('width', '20px')]},
+                {'selector': 'th, td', 'props': [('width', '150px'), ('text-align', 'center')]}]
+            ).set_properties(**{'text-align': 'center'}))
+
+        
+        return output
       
     def detect_encoding(self, uploaded_file):
         result = chardet.detect(uploaded_file.read(100000))
@@ -121,6 +158,8 @@ class Seo:
             pass
     
     def process (self):
+        start_time = time.time()
+
         session = st.session_state.analyze
         if ((self.uploaded_file or self.others or self.uploaded_file_seo) or (self.page_index or self.bounce_rate)) and  session == 'clicked':
                     seo_keywords = ""
@@ -128,7 +167,7 @@ class Seo:
                     traffic_aqcuisition = ""
                     pages_index = ""
                     bounce_rate = ""
-                    with st.spinner('Uploading Seo Files...', show_time=True):
+                    with st.spinner('Seo Analyst...', show_time=True):
                         st.write('')
                         
                         # INITIALIZING SESSIONS
@@ -158,13 +197,8 @@ class Seo:
                             
                         except AttributeError:
                             pass
-                        except KeyError as e:
-                            # Check if 'df_traffic' is the missing key (no file uploaded)
-                            if self.uploaded_file_seo:
-                                pass
-                            else:
-                                # This would be triggered if df_traffic exists but the other keys are missing
-                                st.info("Incorrect Traffic Channels SEMRush format. Please upload a valid SEMRush file.")
+                        except KeyError:
+                            st.info("Incorrect SEMRush format. Please upload a valid SEMRush file.")
                         
                         try:
                             df_seo = st.session_state['df_seo']
@@ -192,15 +226,17 @@ class Seo:
                             traffic_aqcuisition += f"Traffics: {traffics}"
                             traffic_aqcuisition += f"\nPaid Traffic: {ga4_paid_social}\nOrganic Traffic: {ga4_organic_traffic}\nDirect Traffic: {ga4_direct_traffic}\nReferral Traffic: {ga4_referral_traffic}"
                         except KeyError:
-                            
-                            if self.others:
-                                pass
-                            else:
-                                # This would be triggered if df_traffic exists but the other keys are missing
-                                #st.info("Incorrect Traffic Acquisition GA4 format. Please upload a valid GA4 file.")
-                                pass
+                            pass
                         except TypeError:
-                            st.info("Incorrect Traffic Acquisition GA4 format. Please upload a valid GA4 file.")
+                            st.info("Incorrect GA4 format. Please upload a valid GA4 file.")
+
+                        # OUTPUT FOR SEO ANALYST
+                        payload_txt_seo_keywords = {"question": seo_keywords}
+                        payload_txt_traffic_channels = {"question": traffic_channels}
+                        payload_txt_traffic_aqcuisition = {"question": traffic_aqcuisition}
+                        payload_txt_pages_index = {"question": pages_index}
+                        payload_txt_bounce_rate = {"question": bounce_rate}
+
 
                         #result = self.request_model(payload_txt_seo_keywords)
                         #end_time = time.time()

classes/Seo_Backlinks.py

@@ -214,7 +214,7 @@ class SeoBacklinks:
                 hide_button()
                 if self.uploaded_files:
                     combined_text = ""
-                    with st.spinner('Uploading Backlinks...', show_time=True):
+                    with st.spinner('Analyzing...', show_time=True):
                         st.write('')
                         '''
                         # INITIALIZING SESSIONS

classes/Social_Media_FB.py

@@ -147,7 +147,7 @@ class Facebook:
         if ((self.fb_organic_post and self.fb_organic_post.name) or (self.fb_ads_campaign and self.fb_ads_campaign.name) or (self.facebooks) or (self.facebook_rr)) and session == 'clicked':
                 try:
                         combined_text = ""
-                        with st.spinner('Uploading FB Files...', show_time=True):
+                        with st.spinner('Social Media Analyst...', show_time=True):
                             st.write('')
                             # INITIALIZING SESSIONS
                             #combined_text += f"Client Summary: {st.session_state.nature}\n"

classes/Social_Media_IG.py

@@ -110,7 +110,7 @@ class Instagram:
         if (self.instagram or self.instagram_er or self.instagram_pf) and session == 'clicked':
                         try:
                             combined_text = ""
-                            with st.spinner('Uploading IG Files...', show_time=True):
+                            with st.spinner('Instagram...', show_time=True):
                                     st.write('')
                                     try:
                                         combined_text += f"\nInstagram Followers: {self.instagram}"

classes/Tiktok.py

@@ -109,7 +109,7 @@ class Tiktok:
         if (self.tiktok_f or self.tiktok_er or self.tiktok_pf) and session == 'clicked':
                     try:
                         combined_text = ""
-                        with st.spinner('Uploading Tiktok Files...', show_time=True):
+                        with st.spinner('Tiktok...', show_time=True):
                                 st.write('')
                                 # INITIALIZING SESSIONS
                                 #combined_text += f"Client Summary: {st.session_state.nature}\n"

classes/Twitter.py

@@ -121,7 +121,7 @@ class Twitter:
         if (self.twitter or self.twitter_er or self.twitter_pf) and session == 'clicked':
                     try:
                         combined_text = ""
-                        with st.spinner('Uploading Twitter Files...', show_time=True):
+                        with st.spinner('Twitter...', show_time=True):
                                 st.write('')
                                 # INITIALIZING SESSIONS
                                 combined_text += f"Client Summary: {st.session_state.nature}\n"

classes/Youtube.py

@@ -109,7 +109,7 @@ class YouTube:
         if ((self.youtube or self.youtube_er or self.youtube_pf) and session) == 'clicked':
                     try:
                         combined_text = ""
-                        with st.spinner('Uploading YT Files...', show_time=True):
+                        with st.spinner('Youtube...', show_time=True):
                                 st.write('')
                                 # INITIALIZING SESSIONS
                                 #combined_text += f"Client Summary: {st.session_state.nature}\n"

classes/amazon.py

@@ -31,7 +31,7 @@ class Amazon:
                 st.switch_page("./pages/home.py")
         except Exception:
             pass
-
+        '''
         if 'product_title_amazon' not in st.session_state:
             st.session_state['product_title_amazon'] = ''
         if 'images_amazon' not in st.session_state:
@@ -40,25 +40,20 @@ class Amazon:
             st.session_state['bullet_points_amazon'] = ''
         if 'product_description_amazon' not in st.session_state:
             st.session_state['product_description_amazon'] = ''
-        '''
-        if 'amazon_marketplace_questionnaires' not in st.session_state:
-            st.session_state['amazon_marketplace_questionnaires'] = ''
 
     def process(self):
         session = st.session_state.analyze
-        if (self.amazon_marketplace_questionnaires) and session == 'clicked':
+        if (self.product_title_amazon or self.images_amazon or self.bullet_points_amazon or self.product_description_amazon) and session == 'clicked':
                     try:
-                        #product_title_amazon = ""
-                        #images_amazon = ""
-                        #bullet_points_amazon = ""
-                        #product_description_amazon = ""
-                        amazon_marketplace_questionnaires = ""
+                        product_title_amazon = ""
+                        images_amazon = ""
+                        bullet_points_amazon = ""
+                        product_description_amazon = ""
 
-                        with st.spinner('Uploading Amazon Files...', show_time=True):
+                        with st.spinner('Aamzon...', show_time=True):
                                 st.write('')
                                 # INITIALIZING SESSIONS
                                 #combined_text += f"Client Summary: {st.session_state.nature}\n"
-                                '''
                                 try:
                                     product_title_amazon += f"\nProduct Title: {self.product_title_amazon}"
                                 except KeyError:
@@ -75,11 +70,6 @@ class Amazon:
                                     product_description_amazon += f"\nProduct Description: {self.product_description_amazon}"
                                 except KeyError:
                                     pass
-                                '''
-                                try:
-                                    amazon_marketplace_questionnaires += f"Marketplace Questionnaires - Amazon: {self.amazon_marketplace_questionnaires}"
-                                except KeyError:
-                                    pass
                                 
                                 # OUTPUT FOR SEO ANALYST
                                 #payload_txt = {"question": combined_text}
@@ -87,13 +77,11 @@ class Amazon:
                                 
                                 #end_time = time.time()
                                 #time_lapsed = end_time - start_time
-                                '''
+                                
                                 debug_info_product_title_amazon = {'data_field' : 'Product Title - Amazon', 'result': self.product_title_amazon}
                                 debug_info_images_amazon = {'data_field' : 'Images - Amazon', 'result': self.images_amazon}
                                 debug_info_bullet_points_amazon = {'data_field' : 'Bullet Points - Amazon', 'result': self.bullet_points_amazon}
                                 debug_product_description_amazon = {'data_field' : 'Product Description - Amazon', 'result': self.product_description_amazon}
-                                '''
-                                debug_amazon_marketplace_questionnaires = {'data_field' : 'Marketplace Questionnaires - Amazon', 'result': self.amazon_marketplace_questionnaires}
 
                                 '''
                                 debug_info = {
@@ -103,6 +91,7 @@ class Amazon:
                                     'payload': payload_txt,
                                     'result': result,
                                 }
+                                '''
                                 if self.product_title_amazon:
                                     st.session_state['product_title_amazon'] = 'uploaded'
                                     collect_telemetry(debug_info_product_title_amazon)
@@ -115,52 +104,19 @@ class Amazon:
                                 if self.product_description_amazon:
                                     st.session_state['product_description_amazon'] = 'uploaded'
                                     collect_telemetry(debug_product_description_amazon)
-                                '''
-                                if self.amazon_marketplace_questionnaires:
-                                    if self.amazon_marketplace_questionnaires != self.template:
-                                        st.session_state['amazon_marketplace_questionnaires'] = 'uploaded'
-                                        collect_telemetry(debug_amazon_marketplace_questionnaires)
-                                    else:
-                                         pass
                                 
+
                                 st.session_state['analyzing'] = False 
                     except AttributeError:
                         st.info("Please upload CSV or PDF files first.")
                         hide_button() 
 
     def row1(self):
-            #self.product_title_amazon = st.text_input("Product Title - Amazon:", placeholder='Enter Product Title')
-            #self.images_amazon = st.text_input("Images - Amazon:", placeholder='Enter Images')
-            #self.bullet_points_amazon = st.text_input("Bullet Points - Amazon:", placeholder='Enter Bullet Points')
-            #self.product_description_amazon = st.text_input("Product Description - Amazon:", placeholder='Enter Product Description')
-            self.template = ("Product Title:\n"
-                                                            "a. Does the product title include relevant keywords (e.g., Product Brand/Description + Product Line + Material or Key Ingredient + Color + Size + Quantity)?\n"
-                                                            "b. Is the title within Amazon’s recommended character limit (≤200 characters)?\n"
-                                                            "c. Other Remarks:\n\n"
-                                                            "Images:\n"
-                                                            "a. Is the main image on a pure white background?\n"
-                                                            "b. Are there any logos, watermarks, or text on any images?\n"
-                                                            "c. Do the images showcase the product from multiple angles?\n"
-                                                            "d. Are the images high-resolution and zoomable?\n"
-                                                            "e. Other Remarks:\n\n"
-                                                            "Bullet Points:\n"
-                                                            "a. Do the bullets exceed 250 characters?\n"
-                                                            "b. Are the bullet points clear and concise?\n"
-                                                            "c. Do they highlight key features, benefits, and unique selling points?\n"
-                                                            "d. Are keywords naturally included in the bullet points?\n"
-                                                            "e. Other Remarks:\n\n"
-                                                            "Product Description:\n"
-                                                            "a. Is the product description complete and well-formatted?\n"
-                                                            "b. Is it within the 2000-character limit?\n"
-                                                            "c. Does it include important product specifications (size, material, compatibility)?\n"
-                                                            "d. Are there any customer reviews or ratings?\n"
-                                                            "e. If yes, is the average rating above 4 stars?\n"
-                                                            "f. Other Remarks:")
-            self.amazon_marketplace_questionnaires = st.text_area(
-                                                            "Marketplace Questionnaires - Amazon:",
-                                                            value=self.template,
-                                                            height=600
-                                                        )                                                    
+            self.product_title_amazon = st.text_input("Product Title - Amazon:", placeholder='Enter Product Title')
+            self.images_amazon = st.text_input("Images - Amazon:", placeholder='Enter Images')
+            self.bullet_points_amazon = st.text_input("Bullet Points - Amazon:", placeholder='Enter Bullet Points')
+            self.product_description_amazon = st.text_input("Product Description - Amazon:", placeholder='Enter Product Description')
+
             self.process()
             
 if __name__ == "__main__":

classes/client_summary.py

@@ -6,7 +6,7 @@ from helper.button_behaviour import hide_button
 from helper.initialize_analyze_session import initialize_analyze_session
 
 
-class ClientSummary:
+class CientSummary:
     def __init__(self):
         self.initialize()
         self.row1()
@@ -18,13 +18,13 @@ class ClientSummary:
             st.session_state['client_summary'] = ''
         if 'client_name' not in st.session_state:
             st.session_state['client_name'] = ''
-        if 'client_website' not in st.session_state:
-            st.session_state['client_website'] = ''
+        if 'client_webiste' not in st.session_state:
+            st.session_state['client_webiste'] = ''
         if 'target_market' not in st.session_state:
             st.session_state['target_market'] = ''
     
     def process (self):
-            with st.spinner('Uploading Client Details...', show_time=True):
+            with st.spinner('Seo Analyst...', show_time=True):
                         st.write('')
                         client_summary = ""
                         client_name = ""
@@ -44,10 +44,10 @@ class ClientSummary:
                             collect_telemetry(debug_client_summary)
                         if self.name:
                             st.session_state['client_name'] = 'uploaded'
-                            collect_telemetry(debug_client_name)
-                        if self.website:
-                            st.session_state['client_website'] = 'uploaded'
                             collect_telemetry(debug_client_website)
+                        if self.website:
+                            st.session_state['client_webiste'] = 'uploaded'
+                            collect_telemetry(debug_client_name)
              
     def row1(self):
             self.client_summary = st.text_area("Client Summary:", help="Name of business, nature of business, location, products/services")

classes/content.py

@@ -35,7 +35,7 @@ class Content:
                 session = st.session_state.analyze
 
                 if (self.content_in_the_website or self.content_outside_the_website) and session == 'clicked':
-                    with st.spinner('Uploading Contents...', show_time=True):
+                    with st.spinner('SEO On Page Analyst...', show_time=True):
                         st.write('')
                         content_in_the_website = ""
                         content_outside_the_website = ""
@@ -52,18 +52,13 @@ class Content:
                         debug_info_content_outside_the_website = {'data_field' : 'Content outside the Website', 'result': content_outside_the_website}
 
                         if self.content_in_the_website:
-                            if self.content_in_the_website != self.template_content_in_the_website:
-                                st.session_state['content_in_the_website'] = 'uploaded'
-                                collect_telemetry(debug_info_content_in_the_website)
-                            else:
-                                 pass
+                            st.session_state['content_in_the_website'] = 'uploaded'
+                            collect_telemetry(debug_info_content_in_the_website)
                         if self.content_outside_the_website:
-                            if self.content_outside_the_website != self.template_content_outside_the_website:
-                                st.session_state['content_outside_the_website'] = 'uploaded'
-                                collect_telemetry(debug_info_content_outside_the_website)
-                            else:
-                                pass
-                    
+                            st.session_state['content_outside_the_website'] = 'uploaded'
+                            collect_telemetry(debug_info_content_outside_the_website)
+                        
+                            
                         #with st.expander("Debug information", icon="⚙"):
                         #    st.write(debug_info)
 
@@ -75,92 +70,8 @@ class Content:
                             pass
                         
     def row1(self):
-            self.template_content_in_the_website = ("Content and Messaging:\n"
-                                                    "a. Is the text easy to read and understand?\n"
-                                                    "b. Does it clearly explain what the business offers?\n"
-                                                    "c. Are the brand’s Unique Selling Propositions (USPs) clearly emphasized?\n"
-                                                    "d. Other Remarks:\n\n"
-                                                    
-                                                    "Call-to-Action (CTAs):\n"
-                                                    "a. Are CTAs prominently placed and easy to find?\n"
-                                                    "b. Are the CTAs strong and action-focused?\n"
-                                                    "c. Do they appear in the right places?\n"
-                                                    "d. Other Remarks:\n\n"
-                                                    
-                                                    "Images and Videos:\n"
-                                                    "a. Are the images and videos high quality?\n"
-                                                    "b. Do they clearly show the product or service?\n"
-                                                    "c. Are the videos easy to watch (no unnecessary clicks or extra steps)?\n"
-                                                    "d. Are the visuals engaging upon first glance?\n"
-                                                    "e. Other Remarks:\n\n"
-                                                    
-                                                    "Blog and SEO:\n"
-                                                    "a. Does the site have a blog section?\n"
-                                                    "b. Is the blog updated regularly?\n"
-                                                    "c. Are the articles helpful, relevant, and informative?\n"
-                                                    "d. Are internal links used to guide users to related or deeper content?\n"
-                                                    "e. Other Remarks:\n\n"
-                                                    
-                                                    "User Experience (UX) and Navigation:\n"
-                                                    "a. Is the site easy to navigate with clear menus and categories?\n"
-                                                    "b. Can users quickly find important information?\n"
-                                                    "c. Are any interactions creating unnecessary friction (e.g., signups to view content)?\n"
-                                                    "d. Other Remarks:\n\n"
-                                                    
-                                                    "Product or Services (For E-Commerce):\n"
-                                                    "a. Does the site clearly explain the company’s products or services?\n"
-                                                    "b. Are product or service details clear?\n"
-                                                    "c. Are there enough pictures or videos?\n"
-                                                    "d. Is there a sense of urgency or promotions to encourage action?\n"
-                                                    "e. Other Remarks:")
-            self.template_content_outside_the_website = ("Backlinks and Referring Domains:\n"
-                                                            "a. Are there backlinks from relevant and authoritative websites?\n"
-                                                            "b. Do the referring sites belong to the same industry or niche?\n"
-                                                            "c. Are there spammy or low-quality backlinks (e.g., thin directories)?\n"
-                                                            "d. Are the backlinks helpful and align with Google’s Helpful Content guidelines?\n"
-                                                            "e. Are there any guest posts or articles on other websites?\n"
-                                                            "f. Other Remarks:\n\n"
-                                                            
-                                                            "Community Engagement (Forums and Platforms):\n"
-                                                            "a. Is the brand/product/company mentioned in online forums (e.g., Reddit, or Quora)?\n"
-                                                            "b. Are the mentions from forums and platforms generally positive?\n"
-                                                            "c. Are the mentions from forums and platforms generally negative?\n"
-                                                            "d. Is it actively participating or present in these communities?\n"
-                                                            "e. Is there a strategy for using personas or ambassadors to represent the client’s company/brand/product?\n"
-                                                            "f. Other Remarks:\n\n"
-                                                            
-                                                            "Online Reviews and Reputation Management:\n"
-                                                            "a. Are there recent reviews on platforms like Google, Trustpilot, or Yelp?\n"
-                                                            "b. Are the reviews mostly positive?\n"
-                                                            "c. Are the reviews mostly negative?\n"
-                                                            "d. Is the client responding to reviews, especially complaints or fake ones?\n"
-                                                            "e. Do the reviews mention recurring issues (e.g., poor support, unsolicited emails)?\n"
-                                                            "f. Other Remarks:\n\n"
-                                                            
-                                                            "Public Relations and Media Coverage:\n"
-                                                            "a. Has the client’s company been featured in news sites or magazines?\n"
-                                                            "b. Are the articles helpful and recent?\n"
-                                                            "c. Are PR opportunities being used to boost awareness?\n"
-                                                            "d. Other Remarks:\n\n"
-                                                            
-                                                            "Branded Blog Networks:\n"
-                                                            "a. Are there any off-page blog sites created by the client’s company?\n"
-                                                            "b. Is the content unique, helpful, and adding SEO value?\n"
-                                                            "c. Can the content be moved or consolidated into the main site?\n"
-                                                            "d. Other Remarks:\n\n"
-                                                            
-                                                            "Email Marketing & CRM Engagement:\n"
-                                                            "a. Is email being used to follow up with customers or leads (e.g., newsletters, cart recovery)?\n"
-                                                            "b. Are they sending follow-up emails?\n"
-                                                            "c. Are emails building relationships and promoting content or reviews?\n"
-                                                            "d. Other Remarks:")
-            
-            self.content_in_the_website = st.text_area("Content in the Website:", 
-                                                       value=self.template_content_in_the_website,
-                                                        height=600)
-            self.content_outside_the_website = st.text_area("Content outside the Website:", 
-                                                            value=self.template_content_outside_the_website,
-                                                            height=600)
+            self.content_in_the_website = st.text_input("Content in the Website (Website Content)", placeholder='Enter Content in the Website')
+            self.content_outside_the_website = st.text_input("Content outside the Website (Website Content)", placeholder='Enter Content outside the Website')
 
             self.process()
 

classes/ebay.py

@@ -31,7 +31,7 @@ class eBay:
                 st.switch_page("./pages/home.py")
         except Exception:
             pass
-
+        '''
         if 'product_title_ebay' not in st.session_state:
             st.session_state['product_title_ebay'] = ''
         if 'category_ebay' not in st.session_state:
@@ -40,25 +40,20 @@ class eBay:
             st.session_state['images_ebay'] = ''
         if 'product_description_ebay' not in st.session_state:
             st.session_state['product_description_ebay'] = ''
-        '''
-        if 'ebay_marketplace_questionnaires' not in st.session_state:
-            st.session_state['ebay_marketplace_questionnaires'] = ''
 
     def process(self):
         session = st.session_state.analyze
-        if (self.ebay_marketplace_questionnaires) and session == 'clicked':
+        if (self.product_title_ebay or self.category_ebay or self.images_ebay or self.product_description_ebay) and session == 'clicked':
                     try:
-                        #product_title_ebay = ""
-                        #category_ebay = ""
-                        #images_ebay = ""
-                        #product_description_ebay = ""
-                        ebay_marketplace_questionnaires = ""
+                        product_title_ebay = ""
+                        category_ebay = ""
+                        images_ebay = ""
+                        product_description_ebay = ""
 
-                        with st.spinner('Uploading Ebay Files...', show_time=True):
+                        with st.spinner('eBay...', show_time=True):
                                 st.write('')
                                 # INITIALIZING SESSIONS
                                 #combined_text += f"Client Summary: {st.session_state.nature}\n"
-                                '''
                                 try:
                                     product_title_ebay += f"\nProduct Title: {self.product_title_ebay}"
                                 except KeyError:
@@ -75,11 +70,6 @@ class eBay:
                                     product_description_ebay += f"\nProduct Description: {self.product_description_ebay}"
                                 except KeyError:
                                     pass
-                                '''
-                                try:
-                                    ebay_marketplace_questionnaires += f"Marketplace Questionnaires - eBay: {self.ebay_marketplace_questionnaires}"
-                                except KeyError:
-                                    pass
                                 
                                 # OUTPUT FOR SEO ANALYST
                                 #payload_txt = {"question": combined_text}
@@ -88,12 +78,10 @@ class eBay:
                                 #end_time = time.time()
                                 #time_lapsed = end_time - start_time
                                 
-                                #debug_info_product_title_ebay = {'data_field' : 'Product Title - eBay', 'result': self.product_title_ebay}
-                                #debug_category_ebay = {'data_field' : 'Category - eBay', 'result': self.category_ebay}
-                                #debug_images_ebay = {'data_field' : 'Images - eBay', 'result': self.images_ebay}
-                                #debug_product_description_ebay = {'data_field' : 'Product Description - eBay', 'result': self.product_description_ebay}
-
-                                debug_ebay_marketplace_questionnaires = {'data_field' : 'Marketplace Questionnaires - eBay', 'result': self.ebay_marketplace_questionnaires}
+                                debug_info_product_title_ebay = {'data_field' : 'Product Title - eBay', 'result': self.product_title_ebay}
+                                debug_category_ebay = {'data_field' : 'Category - eBay', 'result': self.category_ebay}
+                                debug_images_ebay = {'data_field' : 'Images - eBay', 'result': self.images_ebay}
+                                debug_product_description_ebay = {'data_field' : 'Product Description - eBay', 'result': self.product_description_ebay}
 
                                 '''
                                 debug_info = {
@@ -103,7 +91,7 @@ class eBay:
                                     'payload': payload_txt,
                                     'result': result,
                                 }
-                                
+                                '''
                                 if self.product_title_ebay:
                                     st.session_state['product_title_ebay'] = 'uploaded'
                                     collect_telemetry(debug_info_product_title_ebay)
@@ -116,13 +104,7 @@ class eBay:
                                 if self.product_description_ebay:
                                     st.session_state['product_description_ebay'] = 'uploaded'
                                     collect_telemetry(debug_product_description_ebay)
-                                '''
-                                if self.ebay_marketplace_questionnaires:
-                                    if self.ebay_marketplace_questionnaires != self.template:
-                                        st.session_state['ebay_marketplace_questionnaires'] = 'uploaded'
-                                        collect_telemetry(debug_ebay_marketplace_questionnaires)
-                                    else:
-                                         pass
+                                
 
                                 st.session_state['analyzing'] = False 
                     except AttributeError:
@@ -130,36 +112,11 @@ class eBay:
                         hide_button() 
 
     def row1(self):
-            #self.product_title_ebay = st.text_input("Product Title - eBay:", placeholder='Enter Product Title')
-            #self.category_ebay = st.text_input("Images - eBay:", placeholder='Enter Images')
-            #self.images_ebay = st.text_input("Bullet Points - eBay:", placeholder='Enter Bullet Points')
-            #self.product_description_ebay = st.text_input("Product Description - eBay:", placeholder='Enter Product Description')
+            self.product_title_ebay = st.text_input("Product Title - eBay:", placeholder='Enter Product Title')
+            self.category_ebay = st.text_input("Images - eBay:", placeholder='Enter Images')
+            self.images_ebay = st.text_input("Bullet Points - eBay:", placeholder='Enter Bullet Points')
+            self.product_description_ebay = st.text_input("Product Description - eBay:", placeholder='Enter Product Description')
 
-            self.template = ("Product Title:\n"
-                                                        "a. Is the title within the 80-character limit?\n"
-                                                        "b. Does the title include important details (e.g., brand, color, quantity, compatibility)?\n"
-                                                        "c. Are search keywords used effectively in the title?\n"
-                                                        "d. Other Remarks:\n\n"
-                                                        "Category:\n"
-                                                        "a. Is the product listed under the correct eBay category?\n"
-                                                        "b. Other Remarks:\n\n"
-                                                        "Images:\n"
-                                                        "a. Are the product images on a white background?\n"
-                                                        "b. Are there any text, logos, or watermarks on the images?\n"
-                                                        "c. Are the images high-resolution and zoomable?\n"
-                                                        "d. Other Remarks:\n\n"
-                                                        "Product Description:\n"
-                                                        "a. Is the product description complete and detailed?\n"
-                                                        "b. Are bullet points used to highlight features and benefits?\n"
-                                                        "c. Are there images embedded in the description?\n"
-                                                        "d. Are there any technical issues (e.g., broken images, loading errors)?\n"
-                                                        "e. Is there consistent keyword usage in the description?\n"
-                                                        "f. Other Remarks:")
-            self.ebay_marketplace_questionnaires = st.text_area(
-                                                        "Marketplace Questionnaires - eBay:",
-                                                        value=self.template,
-                                                        height=600
-                                                    )
             self.process()
             
 if __name__ == "__main__":

classes/lld_pm_ln.py

@@ -34,7 +34,7 @@ class LLD_PM_LN:
                 session = st.session_state.analyze
                 if (self.lead_generation_mechanism) and session == 'clicked':
                     lead_generation_mechanism = ""
-                    with st.spinner('Uploading Lead Generation...', show_time=True):
+                    with st.spinner('SEO On Page Analyst...', show_time=True):
                         st.write('')
 
                         try:

classes/pull_through_offers.py

@@ -30,7 +30,7 @@ class PullThroughOffers:
                 session = st.session_state.analyze
                 if (self.pull_through_offers) and session == 'clicked':
                     pull_through_offers = ""
-                    with st.spinner('Uploading Pull Through Offers...', show_time=True):
+                    with st.spinner('SEO On Page Analyst...', show_time=True):
                         st.write('')
                         
                         try:

classes/response_connection_analyst.py

@@ -1,87 +0,0 @@
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-from pymongo import MongoClient
-import json
-
-class ConnectionAnalyst:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        #text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('Connection Analyst...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'Connection Analyst', 'result': payload_txt_model}
-                                upload_response(debug_info)
-
-                                count = 0
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""  
-            count = 0
-            try:
-                session_client_summary = st.session_state['client_summary']
-                if session_client_summary == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Client Summary")
-            except Exception as e:
-                pass
-            
-            if count >= 1:
-                self.process()
-                                       
-
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/response_content.py

@@ -72,7 +72,7 @@ class Content:
     def process(self):
                 with st.spinner('Content Analyst...', show_time=True):
                         st.write('')       
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}                                     
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}                                     
                         try:
                             payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                             payload_txt_model = self.request_model(payload_txt, headers)

classes/response_content_process_and_assets_analyst.py

@@ -1,100 +0,0 @@
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-from pymongo import MongoClient
-import json
-class Content_Process_and_Assets_Analyst:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('Content - Process and Assets Analyst...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'Content - Process and Assets Analyst', 'result': payload_txt_model}
-                                upload_response(debug_info)
-
-                                count = 0
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""  
-            count = 0
-            try:
-                session_client_summary = st.session_state['client_summary']
-                if session_client_summary == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Client Summary")
-            except Exception as e:
-                pass
-            try:
-                session_content_in_the_website = st.session_state['content_in_the_website']
-                if session_content_in_the_website == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Content in the Website")
-            except Exception as e:
-                pass
-            try:
-                session_content_outside_the_website = st.session_state['content_outside_the_website']
-                if session_content_outside_the_website == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Content outside the Website")
-            except Exception as e:
-                pass
-            
-            if count >= 3:
-                self.process()
-                                       
-
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/response_conversion_analyst.py

@@ -1,118 +0,0 @@
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-from pymongo import MongoClient
-import json
-
-class ConversionAnalyst:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('Conversion Analyst...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'Conversion Analyst', 'result': payload_txt_model}
-                                upload_response(debug_info)
-
-                                count = 0
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""  
-            count = 0
-            try:
-                session_lead_generation_mechanism = st.session_state['lead_generation_mechanism']
-                if session_lead_generation_mechanism == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Lead Generation Mechanism")
-            except Exception as e:
-                pass
-            try:
-                session_client_relations_management_system = st.session_state['client_relations_management_system']
-                if session_client_relations_management_system == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Client Relations Management System")
-            except Exception as e:
-                pass
-            try:
-                session_pull_through_offers = st.session_state['pull_through_offers']
-                if session_pull_through_offers == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Pull through offers")
-            except Exception as e:
-                pass
-            try:
-                session_content_in_the_website = st.session_state['content_in_the_website']
-                if session_content_in_the_website == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Content in the Website")
-            except Exception as e:
-                pass
-            try:
-                session_content_outside_the_website = st.session_state['content_outside_the_website']
-                if session_content_outside_the_website == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Content outside the Website")
-            except Exception as e:
-                pass
-            
-            if count >= 1:
-                name = self.fetch_data("Client Name")
-                website = self.fetch_data("Client Website")
-                self.payload = name + website + self.payload
-                self.process()
-                                       
-
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/response_desired_outcome.py

@@ -1,88 +0,0 @@
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-from pymongo import MongoClient
-import json
-
-class DesiredOutcome:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        #text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('Desired Outcome Analyst...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'Desired Outcomes Analyst', 'result': payload_txt_model}
-                                upload_response(debug_info)
-
-                                st.session_state['client_summary'] = ''
-                                count = 0
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""  
-            count = 0
-            try:
-                session_client_summary = st.session_state['client_summary']
-                if session_client_summary == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Client Summary")
-            except Exception as e:
-                pass
-            
-            if count >= 1:
-                self.process()
-                                       
-
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/response_df_overview.py

@@ -1,95 +0,0 @@
-from io import StringIO
-from urllib.parse import urlparse
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-import json
-from pymongo import MongoClient
-
-class dfOverview:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        #text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('DF Overview Analyst...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'DF Overview Analyst', 'result': payload_txt_model}
-                                upload_response(debug_info)
-
-                                st.session_state['client_summary'] = ''
-                                st.session_state['client_name'] = ''
-                                count = 0
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""  
-            count = 0
-            try:
-                session_client_summary = st.session_state['client_summary']
-                if session_client_summary == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Client Summary")
-                    self.payload += self.fetch_data("Client Name")
-                
-            except Exception as e:
-                pass
-            
-            if count >= 1:
-                summary = self.fetch_data("Client Summary")
-                self.payload = summary + self.payload
-                self.process()
-                                       
-
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/response_executive_summary.py

@@ -1,9 +1,11 @@
+from urllib.parse import urlparse
 import streamlit as st
 import requests
 from dotenv import load_dotenv
 import os
 from helper.upload_response import upload_response
 from helper.upload_File import uploadFile
+import json
 from pymongo import MongoClient
 from helper.data_field import get_analyst_response
 
@@ -54,7 +56,7 @@ class ExecutiveSummary:
     def process(self):
                 with st.spinner('Executive Summary...', show_time=True):
                         st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}         
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)

classes/response_lld_pm_ln.py

@@ -73,7 +73,7 @@ class LLD_PM_LN:
     def process(self):
                 with st.spinner('LLD/PM/LN Analyst...', show_time=True):
                         st.write('')       
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}                                     
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}                                     
                         try:
                             payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                             payload_txt_model = self.request_model(payload_txt, headers)

classes/response_marketplace.py

@@ -39,13 +39,10 @@ class Marketplace:
         response.raise_for_status()
         output = response.json()
         #st.write(output)
-        text_amazon = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        #text_ebay = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]["ebay"]
-        text_amazon = json.loads(text_amazon)
-        #text_ebay = json.loads(text_ebay)
-        #text = text_amazon + text_ebay
-        #st.write(text_amazon)
-        return text_amazon
+        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
+        text = json.loads(text)
+        #st.write(text)
+        return text
     
     def fetch_backlinks(self, data_field):
         mongodb_uri = os.getenv("MONGODB_URI")
@@ -74,13 +71,13 @@ class Marketplace:
     def process (self):    
         with st.spinner('Marketplace Analyst...', show_time=True):
                         st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}         
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)
                                 debug_info = {'data_field' : 'Marketplace Analyst', 'result': payload_txt_model}
                                 upload_response(debug_info)
-                                '''
+
                                 st.session_state['product_title_amazon'] = ''
                                 st.session_state['images_amazon'] = ''
                                 st.session_state['bullet_points_amazon'] = ''
@@ -89,9 +86,6 @@ class Marketplace:
                                 st.session_state['category_ebay'] = ''
                                 st.session_state['images_ebay'] = ''
                                 st.session_state['product_description_ebay'] = ''
-                                '''
-                                st.session_state['amazon_marketplace_questionnaires'] = ''
-                                st.session_state['ebay_marketplace_questionnaires'] = ''
                                 count = 0
                         except Exception as e:
                             pass
@@ -103,7 +97,6 @@ class Marketplace:
             #analyze_button = st.button("Analyze", disabled=initialize_analyze_session())
             self.payload = ""  
             count = 0
-            '''
             try:
                 session_product_title_amazon = st.session_state['product_title_amazon']
                 if session_product_title_amazon == 'uploaded':
@@ -162,22 +155,6 @@ class Marketplace:
                     self.payload += self.fetch_data("Product Description - eBay")                 
             except Exception as e:
                 pass
-            '''
-            try:
-                session_amazon_marketplace_questionnaires = st.session_state['amazon_marketplace_questionnaires']
-                if session_amazon_marketplace_questionnaires == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Marketplace Questionnaires - Amazon")                 
-            except Exception as e:
-                pass
-            
-            try:
-                session_ebay_marketplace_questionnaires = st.session_state['ebay_marketplace_questionnaires']
-                if session_ebay_marketplace_questionnaires == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Marketplace Questionnaires - eBay")                 
-            except Exception as e:
-                pass
 
             if count >= 1:
                 summary = self.fetch_data("Client Summary")

classes/response_off.py

@@ -9,6 +9,8 @@ from helper.upload_response import upload_response
 from helper.upload_File import uploadFile
 from helper.button_behaviour import hide_button, unhide_button
 from helper.initialize_analyze_session import initialize_analyze_session
+import pandas as pd
+import asyncio
 import json
 from pymongo import MongoClient
 from helper.data_field import data_field
@@ -35,12 +37,11 @@ class SeoOffPageAnalyst:
         response = requests.post(self.model_url, json=payload_txt, headers=headers)
         response.raise_for_status()
         output = response.json()
-        #st.write(output)
         text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
         text = json.loads(text)
-        #st.write(text)
-        #backlinks = text[0]
-        #referring_domains = text[1]
+        
+        backlinks = text[0]
+        referring_domains = text[1]
 
         return text
     
@@ -62,7 +63,7 @@ class SeoOffPageAnalyst:
     def process(self):
                 with st.spinner('SEO Off Page Analyst...', show_time=True):
                         st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}         
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)
@@ -70,7 +71,7 @@ class SeoOffPageAnalyst:
                                 upload_response(debug_info)
 
                                 st.session_state['off_page_file_uploaded'] = ''
-                                
+                                count = 0
                         except Exception as e:
                             pass
                         st.session_state['analyzing'] = False    
@@ -87,6 +88,7 @@ class SeoOffPageAnalyst:
                 
             except Exception as e:
                 pass
+
             if count >= 1:
                 summary = self.fetch_data("Client Summary")
                 self.payload = summary + self.payload

classes/response_on_page.py

@@ -74,7 +74,7 @@ class SeoOn:
                 with st.spinner('SEO On Page...', show_time=True):
                         st.write('')
                         # OUTPUT FOR SEO ANALYST
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}                                  
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}                                  
                         try:                          
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)

classes/response_pull_through_offers.py

@@ -72,7 +72,7 @@ class PullThroughOffers:
     def process(self):
                 with st.spinner('Pull through offers...', show_time=True):
                         st.write('')       
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}                                     
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}                                     
                         try:
                             payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                             payload_txt_model = self.request_model(payload_txt, headers)

classes/response_sem_ppc.py

@@ -79,7 +79,7 @@ class Sem_PPC:
     def process (self):    
         with st.spinner('SEM/PPC Analyst...', show_time=True):
                         st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}         
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)

classes/response_seo.py

@@ -60,7 +60,7 @@ class Seo:
         mydb = myclient.get_database()
         mycol = mydb["df_data"]
         x = mycol.find_one({"data_field": data_field})
-        x = x["result"]
+        x = x["result"]['question']
         return x
     
     def fetch_data(self, data_field):
@@ -78,10 +78,79 @@ class Seo:
         x = x["result"]
         return x
     
+    def detect_encoding(self, uploaded_file):
+        result = chardet.detect(uploaded_file.read(100000))
+        uploaded_file.seek(0)  # Reset file pointer to the beginning
+        return result['encoding']
+
+    def keyword_ranking(self, df_seo):
+        keyword_ranking = df_seo
+        st.session_state['keyword_ranking'] = keyword_ranking
+
+        keywords_ranking_sorted = keyword_ranking.sort_values("Position", ascending=True)
+
+        keywords_ranking_top_10 = keywords_ranking_sorted[keywords_ranking_sorted["Position"] <= 10].shape[0]
+        keywords_ranking_top_100 = keywords_ranking_sorted[keywords_ranking_sorted["Position"] <= 100].shape[0]
+
+        keyword_ranking = {
+            'Keyword_top_10': keywords_ranking_top_10,
+            'Keyword_top_100': keywords_ranking_top_100
+        }
+        st.session_state['keyword_ranking'] = keyword_ranking
+
+    def traffic_files(self, df_traffic):
+        traffic_channels = df_traffic
+        try:
+            traffic_channels.rename(columns={traffic_channels.columns[0]: 'date'}, inplace=True)
+            traffic_channels['date'] = pd.to_datetime(traffic_channels['date'], format='mixed')
+        except pandas._libs.tslibs.parsing.DateParseError:
+            pass
+        traffic_channels_sort = traffic_channels.sort_values("date", ascending=False)
+
+        organic_traffic = traffic_channels_sort['Organic Search'].values[0]
+        paid_traffic = traffic_channels_sort['Paid Search'].values[0]
+        direct_traffic = traffic_channels_sort['Direct'].values[0]
+        referral_traffic = traffic_channels_sort['Referral'].values[0]
+
+        st.session_state['organic_traffic'] = organic_traffic
+        st.session_state['paid_traffic'] = paid_traffic
+        st.session_state['direct_traffic'] = direct_traffic
+        st.session_state['referral_traffic'] = referral_traffic
+   
+    def ga4_traffic(self, others):
+        st.session_state['others'] = others
+
+        ga4_paid_social = others['Sessions'].values[0]
+        ga4_organic_traffic = others['Sessions'].values[4]
+        ga4_direct_traffic = others['Sessions'].values[2]
+        ga4_referral_traffic = others['Sessions'].values[3]
+        
+        st.session_state['ga4_paid_social'] = ga4_paid_social
+        st.session_state['ga4_organic_traffic'] = ga4_organic_traffic
+        st.session_state['ga4_direct_traffic'] = ga4_direct_traffic
+        st.session_state['ga4_referral_traffic'] = ga4_referral_traffic
+
+    def delete_sessions(self):
+        try:
+            del st.session_state['df_traffic']
+            del st.session_state['others']
+            del st.session_state['df_seo']
+            del st.session_state['keyword_ranking']   
+            del st.session_state['ga4_paid_social']
+            del st.session_state['ga4_organic_traffic']
+            del st.session_state['ga4_direct_traffic']
+            del st.session_state['ga4_referral_traffic']
+            del st.session_state['organic_traffic']
+            del st.session_state['paid_traffic']
+            del st.session_state['direct_traffic']
+            del st.session_state['referral_traffic']
+        except KeyError:
+            pass
+    
     def process (self):    
         with st.spinner('Seo Analyst...', show_time=True):
                         st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}         
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)
@@ -93,7 +162,7 @@ class Seo:
                                 st.session_state['others'] = ''
                                 st.session_state['df_traffic'] = ''
                                 st.session_state['df_seo'] = ''
-                                
+                                count = 0
                         except Exception as e:
                             pass
                         st.session_state['analyzing'] = False    
@@ -103,21 +172,55 @@ class Seo:
             #st.write("") # FOR THE HIDE BUTTON
             #analyze_button = st.button("Analyze", disabled=initialize_analyze_session())
             self.payload = ""  
-            self.payload += self.fetch_data("SEO Keywords")
-        
-            self.payload += self.fetch_data("Traffic Channels")
-    
-            self.payload += self.fetch_data("Traffic Acquisition")
-    
-            self.payload += self.fetch_data("Pages Indexed")            
-    
-            self.payload += self.fetch_data("Bounce Rate")    
+            count = 0
+            try:
+                session_traffic_aqcuisition = st.session_state['df_seo']
+                if session_traffic_aqcuisition == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("SEO Keywords")
+                
+            except Exception as e:
+                pass
+            try:
+                session_traffic_channels = st.session_state['df_traffic']
+                if session_traffic_channels == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Traffic Channels")
+            except Exception as e:
+                pass
+            try:
+                session_others = st.session_state['others']
+                if session_others == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Traffic Acquisition")
+                
+            except Exception as e:
+                pass
+            try:
+                session_page_index = st.session_state['pages_index']
+                if session_page_index == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Pages Indexed")            
+            except Exception as e:
+                pass
+            try:
+                session_bounce_rate = st.session_state['bounce_rate']
+                if session_bounce_rate == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Bounce Rate")                 
+            except Exception as e:
+                pass
+            try:
+                session_backlinks = st.session_state["off_page_file_uploaded"] 
+                if session_backlinks == 'uploaded':
+                    self.payload += self.fetch_backlinks("Backlinks") 
+            except Exception as e:
+                pass
 
-            self.payload += self.fetch_backlinks("Backlinks") 
-            
-            summary = self.fetch_data("Client Summary")
-            self.payload = summary + self.payload
-            self.process()
+            if count >= 1:
+                summary = self.fetch_data("Client Summary")
+                self.payload = summary + self.payload
+                self.process()
             
 
 if __name__ == "__main__":

classes/response_snapshot.py

@@ -1,101 +0,0 @@
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-from pymongo import MongoClient
-from helper.data_field import get_analyst_response
-import json
-
-
-class Snapshot:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('Snapshot...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'Snapshot Analyst', 'result': payload_txt_model}
-                                upload_response(debug_info)
-
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""
-            
-            self.website_and_tools_data = get_analyst_response("Website and Tools Analyst")
-            self.sem_data = get_analyst_response("SEM/PPC Analyst")
-            self.seo_data = get_analyst_response("SEO Analyst")
-            self.social_media_data = get_analyst_response("Social Media Analyst")
-            self.content_data = get_analyst_response("Content Analyst")
-            self.marketpalce_data = get_analyst_response("Marketplace Analyst")
-            
-            analyst_data_dict = {
-                "Website and Tools": self.website_and_tools_data,
-                "SEM/PPC": self.sem_data,
-                "SEO": self.seo_data,
-                "Social Media": self.social_media_data,
-                "Content": self.content_data,
-                "Marketplace": self.marketpalce_data,
-            }
-
-            for analyst_name, data in analyst_data_dict.items():
-                self.payload += f"\n\n--- {analyst_name} Analysis ---\n"
-                if isinstance(data, list):
-                    self.payload += "\n".join(map(str, data))
-                else:
-                    self.payload += str(data)
-            
-            self.process()
-                                       
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/response_social_media.py

@@ -80,7 +80,7 @@ class SocialMedia:
     def process(self):  
         with st.spinner('Social Media Analyst...', show_time=True):
                     st.write('')
-                    headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}              
+                    headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}              
                     try:
                         payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                         payload_txt_model = self.request_model(payload_txt, headers)
@@ -101,28 +101,54 @@ class SocialMedia:
 
     def row1(self):
             st.session_state['analyzing'] = False
-            self.payload = ""                   
-            
-            self.payload += self.fetch_data("Facebook")        
-    
-    
-            self.payload += self.fetch_data("Instagram")
-    
-    
-            self.payload += self.fetch_data("Twitter")
-    
-    
-            self.payload += self.fetch_data("YouTube")
-    
-    
-            self.payload += self.fetch_data("Linkedin")           
-    
-    
-            self.payload += self.fetch_data("Tiktok")
-            
-            summary = self.fetch_data("Client Summary")
-            self.payload = summary + self.payload
-            self.process()
+            self.payload = ""
+            count = 0                           
+            try:
+                session_fb = st.session_state['fb_upload']
+                if session_fb == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Facebook")        
+            except Exception as e:
+                pass
+            try:
+                session_ig = st.session_state['ig_upload']
+                if session_ig == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Instagram")
+            except Exception as e:
+                pass
+            try:
+                session_twitter = st.session_state['twitter_upload']
+                if session_twitter == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Twitter")
+            except Exception as e:
+                pass
+            try:
+                session_yt = st.session_state['youtube_upload']
+                if session_yt == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("YouTube")
+            except Exception as e:
+                pass
+            try:
+                session_linkedin = st.session_state['linkedin_upload']
+                if session_linkedin == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Linkedin")           
+            except Exception as e:
+                pass
+            try:
+                session_tiktok = st.session_state['tiktok_upload']
+                if session_tiktok == 'uploaded':
+                    count += 1
+                    self.payload += self.fetch_data("Tiktok")
+            except Exception as e:
+                pass
+            if count >= 1:
+                summary = self.fetch_data("Client Summary")
+                self.payload = summary + self.payload
+                self.process()
             
 
 if __name__ == "__main__":

classes/response_target_market.py

@@ -55,7 +55,7 @@ class TargetMarket:
     def process(self):
                 with st.spinner('Target Market Analyst...', show_time=True):
                         st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}         
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)

classes/response_website_and_tools.py

@@ -72,7 +72,7 @@ class WebsiteAndTools:
     def process(self):
                 with st.spinner('Website and Tools...', show_time=True):
                         st.write('')       
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}                                     
+                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x-api-key')}"}                                     
                         try:
                                 payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
                                 payload_txt_model = self.request_model(payload_txt, headers)

classes/response_website_audience_acquisition.py

@@ -1,91 +0,0 @@
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-import os
-from helper.upload_response import upload_response
-from helper.upload_File import uploadFile
-from pymongo import MongoClient
-import json
-
-class WebsiteAudienceAcquisition:
-    def __init__(self, model_url):
-        self.uploaded_files = []
-        self.file_dict = {}
-        self.model_url = model_url
-        #self.analyst_name = analyst_name
-        #self.data_src = data_src
-        #self.analyst_description = analyst_description
-        self.initialize()
-        self.row1()
-
-    def initialize(self):
-        # FOR ENV
-        load_dotenv()
-
-        # AGENT NAME
-        #st.header(self.analyst_name)
-    
-    def request_model(self, payload_txt, headers):
-        response = requests.post(self.model_url, json=payload_txt, headers=headers)
-        response.raise_for_status()
-        output = response.json()
-        #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        #text = json.loads(text)
-        #st.write(text)
-        return text
-    
-    def fetch_data(self, data_field):
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_data"]
-        
-        # Sort by timestamp field in descending order
-        x = mycol.find_one(
-            {"data_field": data_field},
-            sort=[("timestamp", -1)]  
-        )
-        
-        x = x["result"]
-        return x
-    
-    def process(self):
-                with st.spinner('Website Audience Acquisition...', show_time=True):
-                        st.write('')
-                        headers = {"Content-Type": "application/json", "x-api-key": f"{os.getenv('x_api_key')}"}         
-                        try:
-                                payload_txt = {"input_value": self.payload, "output_type": "text", "input_type": "chat"}
-                                payload_txt_model = self.request_model(payload_txt, headers)
-                                debug_info = {'data_field' : 'Website Audience Acquisition', 'result': payload_txt_model}
-                                upload_response(debug_info)
-                                st.session_state['website_audience'] = ''
-
-                                count = 0
-                        except Exception as e:
-                            pass
-                        st.session_state['analyzing'] = False    
-                      
-    def row1(self):
-            st.session_state['analyzing'] = False
-            self.payload = ""  
-            count = 0
-            try:
-                session_content_outside_the_website = st.session_state['others']
-                if session_content_outside_the_website == 'uploaded':
-                    count += 1
-                    self.payload += self.fetch_data("Traffic Acquisition")
-            except Exception as e:
-                pass
-            
-            if count >= 1:
-                name = self.fetch_data("Client Name")
-                website = self.fetch_data("Client Website")
-                self.payload = name + website + self.payload
-                self.process()
-                                       
-
-if __name__ == "__main__":
-    st.set_page_config(layout="wide")
-
-upload = uploadFile()

classes/sem_ppc.py

@@ -56,7 +56,7 @@ class Sem_PPC:
                         mobile_ads = ""
                         video_ads = ""
                         shopping_ads = ""
-                        with st.spinner('Uploading SEM/PPC...', show_time=True):
+                        with st.spinner('Ads...', show_time=True):
                                 st.write('')
                                 # INITIALIZING SESSIONS
                                 #combined_text += f"Client Summary: {st.session_state.nature}\n"

classes/website_and_tools.py

@@ -70,7 +70,7 @@ class WebsiteAndTools:
                     client_relations_management_system = ""
                     mobile_loading_speed = ""
         
-                    with st.spinner('Uploading Website and Tools...', show_time=True):
+                    with st.spinner('SEO On Page Analyst...', show_time=True):
                         st.write('')
                         '''
                         try:

helper/data_field.py

@@ -5,9 +5,9 @@ def data_field(data_src):
         myclient = MongoClient(mongodb_uri)
         mydb = myclient.get_database()
         mycol = mydb["df_data"]
-        x = mycol.find_one({"data_field": data_src},
-                sort=[('timestamp', -1)])
-        x = x["result"]
+        x = mycol.find_one({"data_field": data_src})
+        x = x["result"]["question"]
+        #st.write(x)
         return x
 
 def get_analyst_response(data_src):
@@ -27,37 +27,5 @@ def get_analyst_response(data_src):
                 if myclient:
                         myclient.close()
 
-
-def get_marketplace_response(data_src):
-    try:
-        mongodb_uri = os.getenv("MONGODB_URI")
-        myclient = MongoClient(mongodb_uri)
-        mydb = myclient.get_database()
-        mycol = mydb["df_response"]
-        
-        # Find the most recent document matching the data_src
-        document = mycol.find_one(
-            {"data_field": data_src},
-            sort=[('timestamp', -1)]
-        )
-        
-        # Check if document exists and has the result field
-        if document and "result" in document:
-            # Extract amazon and ebay data separately
-            amazon_data = document["result"].get("amazon", [])
-            ebay_data = document["result"].get("ebay", [])
-            
-            # Combine both datasets into a single list
-            combined_data = amazon_data + ebay_data
-            
-            return combined_data
-        else:
-            print(f"No matching document or 'result' field found for data_src: {data_src} in df_response. 404")
-            return None
-    except Exception as e:
-        print(f"Error retrieving data: {str(e)}")
-        return None
-    finally:
-        if myclient:
-            myclient.close()
+#
         

helper/telemetry.py

@@ -39,23 +39,3 @@ def collect_telemetry(data):
         print(f"Error sending data to MongoDB: {e}")
     finally:
         client.close()
-
-def clear_collection(data):
-    """
-    Deletes all documents from a specified MongoDB collection.
-    """
-    mongodb_uri = os.getenv("MONGODB_URI")
-    if not mongodb_uri:
-        print("Deletion skipped: No database configured.")
-        return
-
-    try:
-        client = MongoClient(mongodb_uri)
-        db = client.get_default_database()
-        collection = db[f"{data}"]  # Replace with your collection name
-        result = collection.delete_many({})
-        print(f"Deleted {result.deleted_count} documents from the collection.")
-    except Exception as e:
-        print(f"Error deleting documents: {e}")
-    finally:
-        client.close()

helper/upload_File.py

@@ -28,48 +28,6 @@ class uploadFile:
                     pass
    
             st.session_state['uploaded_files'] = self.file_dict
-    
-    def upload_website_audience(self, uploaded_files):
-        for _ in range(len(self.file_dict)):
-            self.file_dict.popitem() 
-
-        for uploaded_file in uploaded_files:
-            if uploaded_file.type == "application/pdf":
-                try:
-                    with pymupdf.open(stream=uploaded_file.read(), filetype="pdf") as doc:  
-                        text = chr(12).join([page.get_text() for page in doc])
-                        self.file_dict[uploaded_file.name] = {'type': 'pdf', 'content': text}
-                except Exception:
-                    pass
-            elif uploaded_file.type == "text/csv":
-                try:
-                    # Skip comment lines that start with #
-                    df = pd.read_csv(
-                        uploaded_file,
-                        comment='#',  # Treat lines starting with # as comments
-                        engine='python'  # Use more flexible engine
-                    )
-                    self.file_dict[uploaded_file.name] = {'type': 'csv', 'content': df}
-                except Exception as e:
-                    print(f"Error processing CSV: {str(e)}")
-                    # If that fails, you could try a more manual approach
-                    try:
-                        uploaded_file.seek(0)
-                        raw_text = uploaded_file.read().decode('utf-8')
-                        # Get only non-comment lines
-                        data_lines = [line for line in raw_text.split('\n') if not line.strip().startswith('#')]
-                        
-                        # Use StringIO to create a file-like object from the filtered lines
-                        from io import StringIO
-                        csv_data = StringIO('\n'.join(data_lines))
-                        
-                        # Read from the filtered data
-                        df = pd.read_csv(csv_data)
-                        self.file_dict[uploaded_file.name] = {'type': 'csv', 'content': df}
-                    except Exception as e:
-                        print(f"Second attempt failed: {str(e)}")
-            
-            st.session_state['upload_website_audience'] = self.file_dict
 
     def upload_file_seo(self, uploaded_files):
         for _ in range(len(self.file_dict)):

pages/analyzing_page.py

@@ -1,7 +1,6 @@
 import os
 import streamlit as st
 import threading
-import time
 from streamlit.runtime.scriptrunner import add_script_run_ctx
 from classes.response_off import SeoOffPageAnalyst
 from classes.response_on_page import SeoOn
@@ -14,371 +13,210 @@ from classes.response_content import Content
 from classes.response_sem_ppc import Sem_PPC
 from classes.response_marketplace import Marketplace
 from classes.response_target_market import TargetMarket
-from classes.response_df_overview import dfOverview
-from classes.response_desired_outcome import DesiredOutcome
-from classes.response_conversion_analyst import ConversionAnalyst
-from classes.response_website_audience_acquisition import WebsiteAudienceAcquisition
-from classes.response_content_process_and_assets_analyst import Content_Process_and_Assets_Analyst
-from classes.response_connection_analyst import ConnectionAnalyst
 from classes.response_executive_summary import ExecutiveSummary
-from classes.response_snapshot import Snapshot
-
-# Initialize session state to track if analysis has been run
-if 'analysis_completed' not in st.session_state:
-    st.session_state.analysis_completed = False
-
-# Create a thread-safe way to update the UI
-class ThreadSafeAnalysis:
-    def __init__(self, placeholder, name):
-        self.placeholder = placeholder
-        self.name = name
-        self.lock = threading.Lock()
-        
-    def update_info(self, message):
-        with self.lock:
-            try:
-                self.placeholder.info(message)
-            except Exception:
-                # Silently ignore errors here - this prevents "bad set index" errors
-                pass
-            
-    def update_success(self, message):
-        with self.lock:
-            try:
-                self.placeholder.success(message)
-            except Exception:
-                # Silently ignore errors here
-                pass
-            
-    def update_error(self, message):
-        with self.lock:
-            try:
-                self.placeholder.error(message)
-            except Exception:
-                # Silently ignore errors here
-                pass
 
 def run_analysis():
-    # Create placeholders for status updates
-    placeholders = {
-        "off_page": st.empty(),
-        "on_page": st.empty(),
-        "website_tools": st.empty(),
-        "seo": st.empty(),
-        "social_media": st.empty(),
-        "lld_pm_ln": st.empty(),
-        "pull_through": st.empty(),
-        "content": st.empty(),
-        "sem_ppc": st.empty(),
-        "marketplace": st.empty(),
-        "target_market": st.empty(),
-        "df_overview": st.empty(),
-        "desired_outcome": st.empty(),
-        "conversion": st.empty(),
-        "website_audience": st.empty(),
-        "content_process_and_assets": st.empty(),
-        "connection": st.empty(),
-        "snapshot": st.empty(),
-        "executive_summary": st.empty(),
-        
-    }
-    
-    # Create thread-safe handlers for each analysis type
-    handlers = {name: ThreadSafeAnalysis(placeholder, name) 
-                for name, placeholder in placeholders.items()}
-    
-    # Define all analysis functions
+    # Placeholders for status updates
+    off_page_status = st.empty()
+    on_page_status = st.empty()
+    website_and_tools_status = st.empty()
+    seo_status = st.empty()
+    social_media_status = st.empty()
+    lld_pm_ln_status = st.empty()
+    pull_through_offers_status = st.empty()
+    content_status = st.empty()
+    sem_ppc = st.empty()
+    marketplace = st.empty()
+    target_market = st.empty()
+    executive_summary_status = st.empty()
+
     def run_off_page_analysis():
-        handler = handlers["off_page"]
         try:
-            handler.update_info("Running SEO Off Page Analysis...")
+            off_page_status.info("Starting SEO Off Page Analysis...")
             result = SeoOffPageAnalyst(os.getenv('MODEL_Off_Page_Analyst'))
-            handler.update_success("SEO Off Page Analysis completed successfully.")
+            off_page_status.success("SEO Off Page Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"SEO Off Page Analysis failed: {str(e)}")
+            off_page_status.error(f"SEO Off Page Analysis failed: {e}")
             return None
 
     def run_on_page_analysis():
-        handler = handlers["on_page"]
         try:
-            handler.update_info("Running On Page Analysis...")
+            on_page_status.info("Starting On Page Analysis...")
             result = SeoOn(os.getenv('MODEL_On_Page_Analyst'))
-            handler.update_success("On Page Analysis completed successfully.")
+            on_page_status.success("On Page Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"On Page Analysis failed: {str(e)}")
+            on_page_status.error(f"On Page Analysis failed: {e}")
             return None
     
     def run_website_and_tools_analysis():
-        handler = handlers["website_tools"]
         try:
-            handler.update_info("Running Website and Tools Analysis...")
+            website_and_tools_status.info("Starting Website and Tools Analysis...")
             result = WebsiteAndTools(os.getenv('Model_Website_and_Tools_Analyst'))
-            handler.update_success("Website and Tools completed successfully.")
+            website_and_tools_status.success("Website and Tools completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Website and Tools Analysis failed: {str(e)}")
+            on_page_status.error(f"Website and Tools Analysis failed: {e}")
             return None
         
     def run_seo_analysis():
-        handler = handlers["seo"]
         try:
-            handler.update_info("Running SEO Analysis...")
+            seo_status.info("Starting SEO Analysis...")
             result = Seo(os.getenv('MODEL_SEO_Analyst'))
-            handler.update_success("SEO Analysis completed successfully.")
+            seo_status.success("SEO Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"SEO Analysis failed: {str(e)}")
+            seo_status.error(f"SEO Analysis failed: {e}")
             return None
         
     def run_social_media_analysis():
-        handler = handlers["social_media"]
         try:
-            handler.update_info("Running Social Media Analysis...")
+            social_media_status.info("Starting Social Media Analysis...")
             result = SocialMedia(os.getenv('MODEL_Social_Media_Analyst'))
-            handler.update_success("Social Media Analysis completed successfully.")
+            social_media_status.success("Social Media Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Social Media Analysis failed: {str(e)}")
+            social_media_status.error(f"Social Media Analysis failed: {e}")
             return None
         
     def run_lld_pm_ln():
-        handler = handlers["lld_pm_ln"]
         try:
-            handler.update_info("Running LLD/PM/LN Analysis...")
+            lld_pm_ln_status.info("Starting LLD/PM/LN Analysis...")
             result = LLD_PM_LN(os.getenv('Model_LLD_PM_LN_ANALYST'))
-            handler.update_success("LLD/PM/LN completed successfully.")
+            lld_pm_ln_status.success("LLD/PM/LN completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"LLD/PM/LN Analysis failed: {str(e)}")
+            lld_pm_ln_status.error(f"LLD/PM/LN Analysis failed: {e}")
             return None
         
     def run_pull_through_offers():
-        handler = handlers["pull_through"]
         try:
-            handler.update_info("Running Pull through offer Analysis...")
+            pull_through_offers_status.info("Starting Pull through offer Analysis...")
             result = PullThroughOffers(os.getenv('Model_Pull_Through_Offers_Analyst'))
-            handler.update_success("Pull through offer completed successfully.")
+            pull_through_offers_status.success("Pull through offer completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Pull through offer Analysis failed: {str(e)}")
+            pull_through_offers_status.error(f"Pull through offer Analysis failed: {e}")
             return None
         
     def run_content():
-        handler = handlers["content"]
         try:
-            handler.update_info("Running Content Analysis...")
+            content_status.info("Starting Content Analysis...")
             result = Content(os.getenv('Model_Content'))
-            handler.update_success("Content Analysis completed successfully.")
+            content_status.success("Content Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Content Analysis failed: {str(e)}")
+            content_status.error(f"Content Analysis failed: {e}")
             return None
         
     def run_sem_ppc_analysis():
-        handler = handlers["sem_ppc"]
         try:
-            handler.update_info("Running SEM/PPC Analysis...")
+            sem_ppc.info("Starting SEM/PPC Analysis...")
             result = Sem_PPC(os.getenv('Model_SEM_PPC_Analyst'))
-            handler.update_success("SEM/PPC Analysis completed successfully.")
+            sem_ppc.success("SEM/PPC Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"SEM/PPC Analysis failed: {str(e)}")
+            sem_ppc.error(f"SEM/PPC Analysis failed: {e}")
             return None
         
     def run_marketplace_analysis():
-        handler = handlers["marketplace"]
         try:
-            handler.update_info("Running Marketplace Analysis...")
-            result = Marketplace(os.getenv('Model_Marketplace_Analyst'))
-            handler.update_success("Marketplace Analysis completed successfully.")
+            marketplace.info("Starting Marketplace Analysis...")
+            result = Marketplace(os.getenv('Model_SEM_PPC_Analyst'))
+            marketplace.success("Marketplace Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Marketplace Analysis failed: {str(e)}")
+            marketplace.error(f"Marketplace Analysis failed: {e}")
             return None
     
     def run_target_market_analysis():
-        handler = handlers["target_market"]
         try:
-            handler.update_info("Running Target Market Analysis...")
+            target_market.info("Starting Target Market Analysis...")
             result = TargetMarket(os.getenv('Model_Target_Market_Analyst'))
-            handler.update_success("Target Market Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"Target Market Analysis failed: {str(e)}")
-            return None
-        
-    def run_df_overview_analysis():
-        handler = handlers["df_overview"]
-        try:
-            handler.update_info("Running DF Overview Analysis...")
-            result = dfOverview(os.getenv('Model_DF_Overview_Analyst'))
-            handler.update_success("DF Overview Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"DF Overview Analysis failed: {str(e)}")
-            return None
-    
-    def run_desired_outcomes_analysis():
-        handler = handlers["desired_outcome"]
-        try:
-            handler.update_info("Running Desired Outcomes Analysis...")
-            result = DesiredOutcome(os.getenv('Model_Desired_Outcomes_DM_Analyst'))
-            handler.update_success("Desired Outcomes Analysis completed successfully.")
+            target_market.success("Target Market Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Desired Outcomes Analysis failed: {str(e)}")
-            return None
-    
-    def run_conversion_analysis():
-        handler = handlers["conversion"]
-        try:
-            handler.update_info("Running Conversion Analysis...")
-            result = ConversionAnalyst(os.getenv('Model_Conversion_Analyst'))
-            handler.update_success("Conversion Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"Conversion Analysis failed: {str(e)}")
-            return None
-            
-    def run_website_audience():
-        handler = handlers["website_audience"]
-        try:
-            handler.update_info("Running Website Audience Acquisition Analysis...")
-            result = WebsiteAudienceAcquisition(os.getenv('Model_Website_Audience_Acquisition_Analyst'))
-            handler.update_success("Website Audience Acquisition Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"Website Audience Acquisition Analysis failed: {str(e)}")
-            return None
-        
-    def run_content_process_and_assets_analysis():
-        handler = handlers["content_process_and_assets"]
-        try:
-            handler.update_info("Running Content - Process and Assets Analysis...")
-            result = Content_Process_and_Assets_Analyst(os.getenv('Model_Content_Process_and_Assets_Analyst'))
-            handler.update_success("Content - Process and Assets Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"Content - Process and Assets Analysis failed: {str(e)}")
-            return None
-
-    def run_connection_analysis():
-        handler = handlers["connection"]
-        try:
-            handler.update_info("Connection Analysis...")
-            result = ConnectionAnalyst(os.getenv('Model_Connection_Analyst'))
-            handler.update_success("Connection Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"Connection Analysis failed: {str(e)}")
-            return None
-
-    def run_snapshot_analysis():
-        handler = handlers["snapshot"]
-        try:
-            handler.update_info("Running Snapshot by Channel Analysis...")
-            result = Snapshot(os.getenv('Model_Snapshot_by_Channel_Analyst'))
-            handler.update_success("Snapshot by Channel Analysis completed successfully.")
-            return result
-        except Exception as e:
-            handler.update_error(f"Snapshot by Channel Analysis failed: {str(e)}")
+            target_market.error(f"Target Market Analysis failed: {e}")
             return None
     
     def run_executive_summary_analysis():
-        handler = handlers["executive_summary"]
         try:
-            handler.update_info("Running Executive Summary Analysis...")
+            executive_summary = st.empty().info("Starting Executive Summary Analysis...")
             result = ExecutiveSummary(os.getenv('Model_Executive_Summary_Analyst'))
-            handler.update_success("Executive Summary Analysis completed successfully.")
+            executive_summary = st.empty().success("Executive Summary Analysis completed successfully.")
             return result
         except Exception as e:
-            handler.update_error(f"Executive Summary Analysis failed: {str(e)}")
+            executive_summary = st.empty().error(f"Executive Summary Analysis failed: {e}")
             return None
 
-    # Define first batch of analyses
-    threads_first_batch = [
-        (run_off_page_analysis, "off_page"),
-        (run_on_page_analysis, "on_page"),
-        (run_website_and_tools_analysis, "website_tools"),
-        (run_seo_analysis, "seo"),
-        (run_social_media_analysis, "social_media"),
-        (run_lld_pm_ln, "lld_pm_ln"),
-        (run_pull_through_offers, "pull_through"),
-        (run_content, "content"),
-        (run_sem_ppc_analysis, "sem_ppc"),
-        #(run_marketplace_analysis, "marketplace"),
-        (run_target_market_analysis, "target_market"),
-        (run_df_overview_analysis, "df_overview"),
-        (run_desired_outcomes_analysis, "desired_outcome"),
-        (run_content_process_and_assets_analysis, "content_process_and_assets"),
-        (run_conversion_analysis, "conversion"),
-        (run_website_audience, "website_audience"),
-        (run_connection_analysis, "connection")
-    ]
-    
-    # Create and start first batch threads with small delays to prevent UI conflicts
-    thread_objects_first_batch = []
-    for i, (func, name) in enumerate(threads_first_batch):
-        # Add a small stagger to thread start times to reduce conflicts
-        time.sleep(0.1)
-        thread = threading.Thread(target=func, name=name)
-        add_script_run_ctx(thread)  # Attach Streamlit context
-        thread_objects_first_batch.append(thread)
-        thread.start()
-    
-    # Wait for all first batch threads to complete
-    for thread in thread_objects_first_batch:
-        thread.join()
-    
-    # Add a separator
+    # Create threads for concurrent execution
+    off_page_thread = threading.Thread(target=run_off_page_analysis)
+    on_page_thread = threading.Thread(target=run_on_page_analysis)
+    website_and_tools_thread = threading.Thread(target=run_website_and_tools_analysis)
+    seo_thread = threading.Thread(target=run_seo_analysis)
+    social_media_thread = threading.Thread(target=run_social_media_analysis)
+    llm_pm_ln_thread = threading.Thread(target=run_lld_pm_ln)
+    pull_through_offers_thread = threading.Thread(target=run_pull_through_offers)
+    content_thread = threading.Thread(target=run_content)
+    content_sem_ppc_thread = threading.Thread(target=run_sem_ppc_analysis)
+    marketplace_thread = threading.Thread(target=run_marketplace_analysis)
+    target_market_thread = threading.Thread(target=run_target_market_analysis)
+
+    # Attach Streamlit context to threads
+    add_script_run_ctx(off_page_thread)
+    add_script_run_ctx(on_page_thread)
+    add_script_run_ctx(website_and_tools_thread)
+    add_script_run_ctx(seo_thread)
+    add_script_run_ctx(social_media_thread)
+    add_script_run_ctx(llm_pm_ln_thread)
+    add_script_run_ctx(pull_through_offers_thread)
+    add_script_run_ctx(content_thread)
+    add_script_run_ctx(content_sem_ppc_thread)
+    add_script_run_ctx(marketplace_thread)
+    add_script_run_ctx(target_market_thread)
+
+    # Start threads
+    off_page_thread.start()
+    on_page_thread.start()
+    website_and_tools_thread.start()
+    seo_thread.start()
+    social_media_thread.start()
+    llm_pm_ln_thread.start()
+    pull_through_offers_thread.start()
+    content_thread.start()
+    content_sem_ppc_thread.start()
+    marketplace_thread.start()
+    target_market_thread.start()
+
+    # Wait for threads to complete
+    off_page_thread.join()
+    on_page_thread.join()
+    website_and_tools_thread.join()
+    seo_thread.join()
+    social_media_thread.join()
+    llm_pm_ln_thread.join()
+    pull_through_offers_thread.join()
+    content_thread.join()
+    content_sem_ppc_thread.join()
+    marketplace_thread.join()
+    target_market_thread.join()
+
+    st.markdown("---")
+    executive_summary_status.info("Starting Executive Summary Analysis...")
     try:
-        st.markdown("---")
-    except Exception:
-        pass
-    
-    # Wait a bit to let UI stabilize before starting second batch
-    time.sleep(0.5)
+        executive_summary = ExecutiveSummary(os.getenv('Model_Executive_Summary_Analyst'))
+        executive_summary_status.success("Executive Summary Analysis completed successfully.")
+    except Exception as e:
+        executive_summary_status.error(f"Executive Summary Analysis failed: {e}")    
+        st.success("🎉 All analyses completed!") # Final success message
     
-    # Create threads for second batch (snapshot and executive summary)
-    threads_second_batch = [
-        (run_snapshot_analysis, "snapshot"),
-        (run_executive_summary_analysis, "executive_summary")
-    ]
-    
-    # Create and start second batch threads
-    thread_objects_second_batch = []
-    for i, (func, name) in enumerate(threads_second_batch):
-        # Add a small stagger between threads
-        time.sleep(0.2)
-        thread = threading.Thread(target=func, name=name)
-        add_script_run_ctx(thread)  # Attach Streamlit context
-        thread_objects_second_batch.append(thread)
-        thread.start()
-    
-    # Wait for second batch threads to complete
-    for thread in thread_objects_second_batch:
-        thread.join()
-    
-    # Set analysis_completed to True when all analyses are done
-    st.session_state.analysis_completed = True
-    try:
-        st.success("🎉 All analyses completed!")
-    except Exception:
-        pass
+    st.success("🎉 All analyses completed!") # Final success message
+    # --- Display Button After Completion ---
+    if st.button("View Results", icon="📃"):
+        st.switch_page("pages/output.py")
 
-# Navigation button
+# Execute the analysis
 if st.button("Back"):
-    st.switch_page("pages/home.py")
-
-# Main logic
-if not st.session_state.analysis_completed:
-    run_analysis()
-else:
-    st.info("Analysis has already been completed.")
-
-# View Results button (only displayed after analysis is completed)
-if st.session_state.analysis_completed and st.button("View Results", icon="📃"):
-    st.switch_page("pages/output.py")
-    st.session_state.analysis_completed = False
+        st.switch_page("pages/home.py")
+run_analysis()

pages/home.py

@@ -2,6 +2,8 @@ import os
 import streamlit as st
 from classes.Off_Page import SeoOffPageAnalyst
 from classes.On_Page import SeoOn
+from classes.On_Page_Crawl import SeoOnCrawl
+from classes.Seo_Backlinks import SeoBacklinks
 from classes.Seo import Seo
 from classes.Social_Media_FB import Facebook
 from classes.Social_Media_IG import Instagram
@@ -10,7 +12,7 @@ from classes.Youtube import YouTube
 from classes.Linkedin import Linkedin
 from classes.Tiktok import Tiktok
 from classes.website_and_tools import WebsiteAndTools
-from classes.client_summary import ClientSummary
+from classes.client_summary import CientSummary
 from classes.pull_through_offers import PullThroughOffers
 from classes.lld_pm_ln import LLD_PM_LN
 from classes.content import Content
@@ -19,7 +21,6 @@ from classes.amazon import Amazon
 from classes.ebay import eBay
 import asyncio
 from helper.upload_button import hide_button, unhide_button
-from helper.telemetry import clear_collection
 import time
 
 class DigitalFootprintDashboard:
@@ -39,40 +40,29 @@ class DigitalFootprintDashboard:
             st.session_state['nature'] = ''
         if 'analyze' not in st.session_state:
             st.session_state['analyze'] = ''
-        if 'analysis_completed' not in st.session_state:
-            st.session_state.analysis_completed = False
-        if 'uploading' not in st.session_state:
-            st.session_state['uploading'] = False
 
     async def create_row1(self):
         """Create the first row with four columns"""
         col1, col2, col3, col4, col5 = st.columns(5, border=True, gap="medium", vertical_alignment="top")
         
         with col1:
-            button_label = "Uploading..." if st.session_state['uploading'] else "Sync Data"
-            if st.button(button_label, key="sync_button", icon="🔄", use_container_width=True):
-                st.session_state['uploading'] = True
-                st.session_state['analyze'] = 'clicked'
-                
-                st.session_state['uploading'] = False
+            
+            self.upload_file_button = st.button("Sync Data", st.session_state['analyze'], icon="🔄", use_container_width=True)
+            if self.upload_file_button == True:
+                st.session_state["analyze"] = 'clicked'
+                unhide_button()
             else:
                 st.session_state["analyze"] = ''
 
-            #self.upload_file_button = st.button("Sync Data", st.session_state['analyze'], icon="🔄", use_container_width=True)
-            
-            #if self.upload_file_button == True:
-            #    st.session_state["analyze"] = 'clicked'
-                #unhide_button()
-            #else:
-            #    st.session_state["analyze"] = ''
-            
-            analyze_disabled = st.session_state.get('analyze') != 'clicked'
-            if st.button("Analyze", key="analyze_button", icon="✨", use_container_width=True, disabled=analyze_disabled):
-                st.session_state.analysis_completed = False
+            self.analyze_button = st.button("Analyze", icon="✨", use_container_width=True)
+            if self.analyze_button == True:
                 st.switch_page("pages/analyzing_page.py")
+            else:
+                hide_button()
+            
+            self.client_summary = CientSummary()
             
             
-            self.client_summary = ClientSummary()
             
         with col2:
             st.write("## Website Traffic")
@@ -109,40 +99,43 @@ class DigitalFootprintDashboard:
             self.website_and_tools = WebsiteAndTools(os.getenv('MODEL_On_Page_Analyst'))
             self.lld_pm_ln = LLD_PM_LN(os.getenv('Model_LLD_PM_LN_ANALYST'))
             self.pull_through_offers = PullThroughOffers(os.getenv('Model_Pull_Through_Offers_Analyst'))
+            self.content = Content(os.getenv('Model_Content'))
 
         return col1, col2, col3, col4, col5
 
     async def create_row2(self):
         """Create the first row with four columns"""
-        col1, col4 = st.columns(2, border=True, gap="medium", vertical_alignment="top")
-        # col1, col2, col3, col4 = st.columns(4, border=True, gap="medium", vertical_alignment="top")
+        col1, col2, col3, col4 = st.columns(4, border=True, gap="medium", vertical_alignment="top")
         
         with col1:
             st.write("## Ads")
             self.sem_ppc = Sem_PPC(os.getenv('Model_SEM_PPC_Analyst'))
-        # with col2:
-        #     st.write("## Amazon")
-        #     self.amazon = Amazon(os.getenv('Model_SEM_PPC_Analyst'))
-        # with col3:
-        #     st.write("## eBay")
-        #     self.ebay = eBay(os.getenv('Model_SEM_PPC_Analyst'))
-        with col4:
-            st.write("## Website Content")
-            self.content = Content(os.getenv('Model_Content'))
-        return col1, col4
+        with col2:
+            st.write("## Amazon")
+            self.amazon = Amazon(os.getenv('Model_SEM_PPC_Analyst'))
+        with col3:
+            st.write("## eBay")
+            self.ebay = eBay(os.getenv('Model_SEM_PPC_Analyst'))
+        return col1, col2, col3
     
-    async def delete_button(self):
-        reset_button = st.button("RESET ALL",icon="🗑️", use_container_width=True)
-
-        if reset_button:
-            clear_collection("df_data")
-            clear_collection("df_response")
+    async def run_analysis(self):
+        result = await asyncio.gather(
+            self.gtmetrix.process(), 
+            self.backlinks.process(), 
+            self.keywords.process(), 
+            self.facebook.process(), 
+            self.instagram.process(), 
+            self.twitter.process(), 
+            self.youtube.process(), 
+            self.linkedin.process(), 
+            self.tiktok.process(), 
+        )
+        st.session_state.analyze = False
 
     async def main(self):
         """Main method to run the dashboard"""
         await self.create_row1()
         await self.create_row2()
-        await self.delete_button()
         #self.run_analysis()
 
 # Main execution

pages/output.py

@@ -1,116 +1,45 @@
 import json
 import os
 import streamlit as st
-from helper.data_field import get_analyst_response, data_field, get_marketplace_response
-import time
+from helper.data_field import get_analyst_response
+from helper.telemetry import collect_telemetry
 
 st.set_page_config(layout="centered") 
 
 def write_client_footprint():
 
-    try:
-        web = get_analyst_response("Website and Tools Analyst")
-        result_web = {item["category"]: item["current_footprint"] for item in web}
-    except TypeError:
-        result_web = None
-
-    try:
-        seo = get_analyst_response("SEO Analyst")
-        seo = {item["category"]: item["current_footprint"] for item in seo}
-    except TypeError:
-        seo = None
-
-    try:
-        socmed = get_analyst_response("Social Media Analyst")
-        socmed = {item["category"]: item["current_footprint"] for item in socmed}
-    except TypeError:
-        socmed = None
-
-    def safe_get(data, key):
-        value = data.get(key)
-        return value if value else "N/A"
+    web = get_analyst_response("Website and Tools Analyst")
+    result_web = {item["category"]: item["current_footprint"] for item in web}
+    
+    seo = get_analyst_response("SEO Analyst")
+    seo = {item["category"]: item["current_footprint"] for item in seo}
+    
+    socmed = get_analyst_response("Social Media Analyst")
+    socmed = {item["category"]: item["current_footprint"] for item in socmed}
+    
     
     markdown_table = "| Source/Channel | Current KPI |\n"
     markdown_table += "|---|---|\n"
-    markdown_table += f"| Website Health Score | {safe_get(result_web, 'website_overall_health_score')} |\n"
-    markdown_table += f"| Organic Traffic to the Website | {safe_get(seo, 'organic_traffic')} |\n"
-    markdown_table += f"| Paid Traffic to the Website | {safe_get(seo, 'paid_traffic')} |\n"
-    markdown_table += f"| Referral Traffic to the Website | {safe_get(seo, 'referral_traffic')} |\n"
+    markdown_table += f"| Website Health Score | {result_web['website_overall_health_score']} |\n"
+    markdown_table += f"| Organic Traffic to the Website | {seo['organic_traffic']} |\n"
+    markdown_table += f"| Paid Traffic to the Website | {seo['paid_traffic']} |\n"
+    markdown_table += f"| Referral Traffic to the Website | {seo['referral_traffic']} |\n"
     markdown_table += f"| Email Traffic to the Website | N/A |\n"
-    markdown_table += f"| Direct Traffic to the Website | {safe_get(seo, 'direct_traffic')} |\n"
+    markdown_table += f"| Direct Traffic to the Website | {seo['direct_traffic']} |\n"
     markdown_table += f"| Social Traffic to the Website | N/A |\n"
     markdown_table += f"| Display Traffic to the Website | N/A |\n"
     markdown_table += f"| Email Database | N/A |\n"
-    markdown_table += f"| Facebook Followers | {safe_get(socmed, 'facebook_followers')} |\n"
-    markdown_table += f"| Twitter Followers | {safe_get(socmed, 'twitter_followers')} |\n"
-    markdown_table += f"| Instagram Followers | {safe_get(socmed, 'instagram_followers')} |\n"
-    markdown_table += f"| Linkedin Followers | {safe_get(socmed, 'linkedin_followers')} |\n"
+    markdown_table += f"| Facebook Followers | {socmed['facebook_followers']} |\n"
+    markdown_table += f"| Twitter Followers | {socmed['twitter_followers']} |\n"
+    markdown_table += f"| Instagram Followers | {socmed['instagram_followers']} |\n"
+    markdown_table += f"| Linkedin Followers | {socmed['linkedin_followers']} |\n"
     markdown_table += f"| Google My Business | N/A |\n"
-    markdown_table += f"| # of Keywords Ranking in Top 10 | {safe_get(seo, 'keyword_ranking_in_top_10')} |\n"
-    markdown_table += f"| # of Keywords Ranking in Top 100 | {safe_get(seo, 'keyword_ranking_in_top_100')} |\n"
+    markdown_table += f"| # of Keywords Ranking in Top 10 | {seo['keyword_ranking_in_top_10']} |\n"
+    markdown_table += f"| # of Keywords Ranking in Top 100 | {seo['keyword_ranking_in_top_100']} |\n"
     
     return markdown_table
     
-def write_snapshot(data):
-     
-    if data:
-        try:
-            
-            parsed_data = data
-            
-            if isinstance(parsed_data, list):
-                # Create Markdown table header
-                markdown_table = "| Channel | Status | Requirements | What's Needed to Deliver |\n"
-                markdown_table += "|---|---|---|---|\n"
-
-                # Loop through the list of dictionaries
-                for item in parsed_data:
-                    # Use .get() for safety in case keys are missing
-                    channel = item.get('channel', 'N/A')
-                    status = item.get('status', 'N/A')
-                    requirements = item.get('requirements', 'N/A')
-                    deliver = item.get('deliver', 'N/A')
-
-                    # Add a row to the Markdown table string
-                    # Replace underscores with spaces and apply title case to category
-                                       # Replace underscores with spaces first
-                    channel_temp = channel.replace('_', ' ')
-
-                    # Apply title case if there are multiple words, otherwise uppercase
-                    if ' ' in channel_temp: # Check for spaces directly
-                        channel_formatted = channel_temp.title()
-                    else:
-                        channel_formatted = channel_temp.upper() # Use upper() instead of upper_case()
-                   
-
-                    markdown_table += f"| {channel_formatted} | {status} | {requirements} | {deliver} |\n"
-                    
-
-                # Display the complete Markdown table
-                st.markdown(markdown_table)
-
-            # Handle case if data is not a list (e.g., a single dictionary)
-            elif isinstance(parsed_data, dict):
-                 st.write("Analysis Result (Summary):")
-                 # You might want to display dictionary data differently
-                 st.json(parsed_data) # Example: Display as JSON
-            else:
-                 st.warning("data is not in the expected list format.")
-                 st.write(parsed_data) # Show the raw data
-
-        except json.JSONDecodeError:
-            st.error("Error: Could not parse the data as JSON.")
-            st.text(data) # Show the raw string data
-        except AttributeError:
-             st.error("Error: Could not find expected keys ('channel', 'status', 'requirements', 'deliver') in the data.")
-             st.write(parsed_data) # Show the data that caused the error
-        except Exception as e:
-            st.error(f"An unexpected error occurred while processing data: {e}")
-            st.write(data) # Show the raw data
-    else:
-        st.warning("No data retrieved for analysis.")
-    # --- End: Loop and display data ---
-        
+    
 def write_table(website_and_tools_data):
      
     if website_and_tools_data:
@@ -133,7 +62,6 @@ def write_table(website_and_tools_data):
                     # Add a row to the Markdown table string
                     # Replace underscores with spaces and apply title case to category
                     category_formatted = category.replace('_', ' ').title()
-                    
                     current_footprint_formatted = current_footprint.replace('_', ' ')
                     best_of_breed_formatted = best_of_breed.replace('_', ' ')
 
@@ -219,22 +147,25 @@ def seo_on_page_table(df_data):
     # --- End: Loop and display data ---
     
 def display_outputs():
-    client_name = data_field("Client Name")
-    client_website = data_field("Client Website")
-    
-    
+    st.markdown("<div id='top'></div>", unsafe_allow_html=True);
+    client_name = "RMX Creatives"
+    client_website = "https://rmxcreatives.com/"
+    overview = f"""**{client_name}** is a financial services company based in Auckland, New Zealand, specializing in providing quick and flexible loan solutions for businesses and individuals. Represented by Paul Stone, LoansOne has enlisted ShoreMarketing to perform a deep dive into their digital footprint to have a view of the holistic status of their digital properties and determine how each property can play part in implementing a stronger digital marketing plan.\n
+The Digital Marketing Footprint consists of deep-dive research by ShoreMarketing specialists to help the business leaders of LoansOne understand the effectiveness of their existing digital initiatives with the view of giving them an insight to developing a strategy and effectively allocating business resources to digital properties that will give them the best results.\n
+This document represents the results of our audit of LoansOne’s digital marketing and management practices. Our audit covered reviews of key digital areas: Website and Tools, PPC/SEM, SEO, Social Media, and Market Places."""
     
-    overview = get_analyst_response("DF Overview Analyst")    
     
     st.markdown("# Digital Marketing Audit")
     st.markdown(f"for: **{client_name} ({client_website})**")
     st.write("")
-    
+    st.write("")
+    st.write("")
     st.markdown("### DIGITAL FOOTPRINT OVERVIEW")
     st.markdown(f"{overview}")
     st.markdown("---")
     st.markdown("### Executive Summary")
-    st.markdown(get_analyst_response("Executive Summary"))
+
+    st.markdown(f"Simtech LED's digital footprint reveals significant strengths and areas for improvement that can enhance its competitive positioning in the casino, gaming, and entertainment LED market. The analysis highlights the following key findings and recommendations")
     st.markdown("---")
     
     st.markdown("### CLIENT FOOTPRINT")
@@ -252,7 +183,7 @@ def display_outputs():
     st.markdown("---")    
     
     st.markdown("### SNAPSHOT BY CHANNEL")    
-    write_snapshot(get_analyst_response("Snapshot Analyst")) #write_snapshot
+    st.write("TBD")
     st.markdown("---")
     
     st.markdown("## AUDITS PER CHANNEL")
@@ -264,7 +195,7 @@ In line with this, we have looked into the technology used by **{client_name}**
     website_and_tools_data = get_analyst_response("Website and Tools Analyst")
     write_table(website_and_tools_data)
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
    
     st.markdown("### SEARCH ENGINE MARKETING/PPC")
@@ -276,7 +207,7 @@ Currently, {client_name} has already explored numerous online advertising. Its c
     sem_data = get_analyst_response("SEM/PPC Analyst")
     write_table(sem_data)
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
     
     st.markdown("### SEARCH ENGINE OPTIMIZATION")
@@ -287,7 +218,7 @@ There are two types of SEO based on where the optimization is implemented: On-pa
     seo_data = get_analyst_response("SEO Analyst")
     write_table(seo_data)
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
     
     # Write On Page Table
@@ -295,15 +226,15 @@ There are two types of SEO based on where the optimization is implemented: On-pa
     on_page_data = get_analyst_response("On Page Analyst")
     seo_on_page_table(on_page_data)
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
     
     # Write Off Page Table
     st.markdown("### OFF PAGE OPTIMIZATION")
-    on_page_data = get_analyst_response("SEO Off Page Analyst")
+    on_page_data = get_analyst_response("Off Page Analyst")
     seo_on_page_table(on_page_data)
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
     
     # Write SocMed Table
@@ -314,7 +245,7 @@ Regardless, it is still a great channel worth investing to improve a business’
     social_media_data = get_analyst_response("Social Media Analyst")
     write_table(social_media_data)
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
     
     # Write SocMed Table
@@ -322,14 +253,15 @@ Regardless, it is still a great channel worth investing to improve a business’
     st.markdown(f"""Content is king in digital marketing. People log into the internet to look for and consume information in different formats: text-based, video, audio, or image. Content is what help businesses establish their expertise in the industry, convert leads into customers, guide their customers through their sales funnel, and build relationships with their customers. """)
     content_data = get_analyst_response("Content Analyst")
     write_table(content_data)
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
 
-    # if (get_analyst_response("Marketplace Analyst")):
-    #     st.markdown("### MARKET PLACE")
-    #     st.table(get_analyst_response("Marketplace Analyst"))
-    #     st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
-    #     st.markdown("---")
+    if (get_analyst_response("Marketplace Analyst")):
+        st.markdown("### MARKET PLACE")
+        marketpalce_data = get_analyst_response("Marketplace Analyst")
+        write_table(marketpalce_data)
+        st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+        st.markdown("---")
     
     
     st.markdown("## OTHER INFORMATION")
@@ -349,7 +281,7 @@ Regardless, it is still a great channel worth investing to improve a business’
     st.write(target_market_data['summary'])
     
     st.markdown("##### WHAT IS THE DESIRED OUTCOMES OF DIGITAL MARKETING?")
-    st.markdown(get_analyst_response("Desired Outcomes Analyst"))
+    st.write("TBD")
     
     st.markdown("##### WHAT IS THE PULL-THROUGH OFFER?")
     pull_through_data = get_analyst_response("Pull through offers Analyst")
@@ -357,7 +289,7 @@ Regardless, it is still a great channel worth investing to improve a business’
     
     
     st.markdown("##### WEBSITE AUDIENCE ACQUISITION")
-    website_audience_data = get_analyst_response("Website Audience Acquisition")
+    website_audience_data = get_analyst_response("Website Audience Acquisition Analyst")
     st.write(website_audience_data)
     
     #LLD/PM/LN
@@ -371,7 +303,7 @@ Regardless, it is still a great channel worth investing to improve a business’
     st.markdown("##### LEAD NURTURING")
     st.write(lld_data.get('lead_nurturing', None))
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")
     
     
@@ -379,21 +311,15 @@ Regardless, it is still a great channel worth investing to improve a business’
     st.write(f"""Content is king in digital marketing. People log into the internet to look for and consume information in different formats: text-based, video, audio, or image. Content is what help businesses establish their expertise in the industry, convert leads into customers, guide their customers through their sales funnel, and build relationships with their customers. \n
 We have evaluated the process of content development strategy and existing content assets of {client_name} based on how they serve clients throughout the customer journey. """)
     
-    def safe_value(data: dict, key: str) -> str:
-        try:
-            value = data.get(key)
-            return value if value else "N/A"
-        except Exception:
-            return "N/A"
-
+    
     pna_data = get_analyst_response("Content - Process and Assets Analyst")
     if pna_data:
         st.markdown("##### AWARENESS STAGE")
-        st.write(safe_value(pna_data, 'awareness_stage'))
+        st.write(pna_data.get('awareness_stage', 'N/A'))
         st.markdown("##### CONSIDERATION STAGE")
-        st.write(safe_value(pna_data, 'consideration_stage'))
+        st.write(pna_data.get('consideration_stage', 'N/A'))
         st.markdown("##### DECISION STAGE")
-        st.write(safe_value(pna_data, 'decision_stage'))
+        st.write(pna_data.get('decision_stage', 'N/A'))
         
     else:
         st.markdown("##### AWARENESS STAGE")
@@ -403,46 +329,24 @@ We have evaluated the process of content development strategy and existing conte
         st.markdown("##### DECISION STAGE")
         st.write(None)
         
-    
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     st.markdown("---")       
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
     
-    
-    conversion = get_analyst_response("Conversion Analyst")
     st.markdown("#### CONVERSION –  ACTIVATION OF VISITORS")
+    st.markdown("##### AWARENESS TO TRAFFIC")
+    st.write("TBD")
+    st.markdown("##### TRAFFIC TO LEAD CONVERSION")
+    st.write("TBD")
+    st.markdown("##### LEAD TO SALES CONVERSION")
+    st.write("TBD")
+    st.markdown("##### CONVERSION TO BRAND LOYALTY")
+    st.write("TBD")
     
-    if conversion:
-        st.markdown("##### AWARENESS TO TRAFFIC")
-        st.write(safe_value(conversion, 'awareness_to_traffic'))
-        
-        st.markdown("##### TRAFFIC TO LEAD CONVERSION")
-        st.write(safe_value(conversion, 'traffic_to_lead'))
-        
-        st.markdown("##### LEAD TO SALES CONVERSION")
-        st.write(safe_value(conversion, 'lead_to_sales'))
-        
-        st.markdown("##### CONVERSION TO BRAND LOYALTY")
-        st.write(safe_value(conversion, 'conversion_to_brand'))
-    else:
-        st.markdown("##### AWARENESS TO TRAFFIC")
-        st.write(None)
-        st.markdown("##### TRAFFIC TO LEAD CONVERSION")
-        st.write(None)
-        st.markdown("##### LEAD TO SALES CONVERSION")
-        st.write(None)
-        st.markdown("##### CONVERSION TO BRAND LOYALTY")
-        st.write(None)
-    
-    
-    conversion = get_analyst_response("Connection Analyst")
     st.markdown("##### CONNECTION OF ALL ONLINE AND OFFLINE TOUCH POINTS")
-    st.write(conversion)
+    st.write("TBD")
     
-    #st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
-    
-
+    st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
 
-st.markdown("<div id='top'></div>", unsafe_allow_html=True);    
 if st.button("Back to Dashboard", icon="🏠"):
         st.switch_page("pages/home.py")
 display_outputs()