Add Executive Summary analysis functionality and integrate into analyzing page

classes/response_executive_summary.py

@@ -0,0 +1,117 @@
+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
+
+
+class ExecutiveSummary:
+    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('Executive Summary...', 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' : 'Executive Summary', '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.on_page_data = get_analyst_response("On Page Analyst")
+            self.off_page_data = get_analyst_response("Off Page 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")
+            self.target_market_data = get_analyst_response("Target Market Analyst")
+            self.website_audience_data = get_analyst_response("Pull through offers Analyst")
+            self.pull_through_data = get_analyst_response("Website Audience Acquisition Analyst")
+            self.lld_data = get_analyst_response("LLD/PM/LN Analyst")
+            self.pna_data = get_analyst_response("Content - Process and Assets Analyst")
+            
+            analyst_data_dict = {
+                "Website and Tools": self.website_and_tools_data,
+                "SEM/PPC": self.sem_data,
+                "SEO": self.seo_data,
+                "On Page": self.on_page_data,
+                "Off Page": self.off_page_data,
+                "Social Media": self.social_media_data,
+                "Content": self.content_data,
+                "Marketplace": self.marketpalce_data,
+                "Target Market": self.target_market_data,
+                "Pull through offers": self.website_audience_data,
+                "Website Audience Acquisition": self.pull_through_data,
+                "LLD/PM/LN": self.lld_data,
+                "Content - Process and Assets": self.pna_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()

pages/analyzing_page.py

@@ -13,6 +13,7 @@ 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_executive_summary import ExecutiveSummary
 
 def run_analysis():
     # Placeholders for status updates
@@ -27,6 +28,7 @@ def run_analysis():
     sem_ppc = st.empty()
     marketplace = st.empty()
     target_market = st.empty()
+    executive_summary_status = st.empty()
 
     def run_off_page_analysis():
         try:
@@ -137,7 +139,17 @@ def run_analysis():
         except Exception as e:
             target_market.error(f"Target Market Analysis failed: {e}")
             return None
-        
+    
+    def run_executive_summary_analysis():
+        try:
+            executive_summary = st.empty().info("Starting Executive Summary Analysis...")
+            result = ExecutiveSummary(os.getenv('Model_Executive_Summary_Analyst'))
+            executive_summary = st.empty().success("Executive Summary Analysis completed successfully.")
+            return result
+        except Exception as e:
+            executive_summary = st.empty().error(f"Executive Summary Analysis failed: {e}")
+            return None
+
     # 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)
@@ -191,7 +203,13 @@ def run_analysis():
     target_market_thread.join()
 
     st.markdown("---")
-    st.success("🎉 All analyses completed!") # Final success message
+    executive_summary_status.info("Starting Executive Summary Analysis...")
+    try:
+        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
     # --- Display Button After Completion ---
     if st.button("View Results", icon="📃"):
         st.switch_page("pages/output.py")

pages/home.py

@@ -54,7 +54,6 @@ class DigitalFootprintDashboard:
             else:
                 st.session_state["analyze"] = ''
 
-                    
             self.analyze_button = st.button("Analyze", icon="✨", use_container_width=True)
             if self.analyze_button == True:
                 st.switch_page("pages/analyzing_page.py")

pages/output.py

@@ -2,7 +2,7 @@ import json
 import os
 import streamlit as st
 from helper.data_field import get_analyst_response
-import time
+from helper.telemetry import collect_telemetry
 
 st.set_page_config(layout="centered") 
 
@@ -111,8 +111,6 @@ def seo_on_page_table(df_data):
     else:
         st.warning("No data retrieved for analysis.")
     # --- End: Loop and display data ---
-
-     
     
 def display_outputs():
     st.markdown("<div id='top'></div>", unsafe_allow_html=True);
@@ -132,6 +130,7 @@ This document represents the results of our audit of LoansOne’s digital market
     st.markdown(f"{overview}")
     st.markdown("---")
     st.markdown("### 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("---")
     
@@ -241,11 +240,13 @@ Regardless, it is still a great channel worth investing to improve a business’
     st.write("TBD")
     
     st.markdown("##### WHAT IS THE PULL-THROUGH OFFER?")
-    st.write(get_analyst_response("Pull through offers Analyst"))
+    pull_through_data = get_analyst_response("Pull through offers Analyst")
+    st.write(pull_through_data)
     
     
     st.markdown("##### WEBSITE AUDIENCE ACQUISITION")
-    st.write(get_analyst_response("Website Audience Acquisition Analyst"))
+    website_audience_data = get_analyst_response("Website Audience Acquisition Analyst")
+    st.write(website_audience_data)
     
     #LLD/PM/LN
     lld_data = get_analyst_response("LLD/PM/LN Analyst")
@@ -301,8 +302,7 @@ We have evaluated the process of content development strategy and existing conte
     st.write("TBD")
     
     st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
-    
-    
+
 if st.button("Back to Dashboard", icon="🏠"):
         st.switch_page("pages/home.py")
 display_outputs()