Refactor marketplace data retrieval to separate Amazon and eBay responses; update analysis handler to use the correct model.

classes/response_marketplace.py

@@ -39,8 +39,11 @@ class Marketplace:
         response.raise_for_status()
         output = response.json()
         #st.write(output)
-        text = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]
-        text = json.loads(text)
+        text_amazon = output["outputs"][0]["outputs"][0]["results"]["text"]["data"]["text"]["amazon"]
+        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)
         return text
     

helper/data_field.py

@@ -27,5 +27,37 @@ 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()
         

pages/analyzing_page.py

@@ -180,7 +180,7 @@ def run_analysis():
         handler = handlers["marketplace"]
         try:
             handler.update_info("Running Marketplace Analysis...")
-            result = Marketplace(os.getenv('Model_SEM_PPC_Analyst'))
+            result = Marketplace(os.getenv('Model_Target_Market_Analyst'))
             handler.update_success("Marketplace Analysis completed successfully.")
             return result
         except Exception as e:

pages/output.py

@@ -1,7 +1,7 @@
 import json
 import os
 import streamlit as st
-from helper.data_field import get_analyst_response, data_field
+from helper.data_field import get_analyst_response, data_field, get_marketplace_response
 import time
 
 st.set_page_config(layout="centered") 
@@ -256,7 +256,7 @@ Regardless, it is still a great channel worth investing to improve a business’
 
     if (get_analyst_response("Marketplace Analyst")):
         st.markdown("### MARKET PLACE")
-        marketpalce_data = get_analyst_response("Marketplace Analyst")
+        marketpalce_data = get_marketplace_response("Marketplace Analyst")
         write_table(marketpalce_data)
         st.markdown("<a href='#top'>Go to top</a>", unsafe_allow_html=True)
         st.markdown("---")