Update src/streamlit_app.py

src/streamlit_app.py

@@ -259,41 +259,52 @@ def get_similar_content(content, n_recommendations=5):
             "accept": "application/json"
         }
         
-        # Query the similarities table
-        similarity_table_url = "https://mtoft20-potm.hf.space/api/v1/db/data/noco/p9pozkcw81t9aee/content_similarities"
-        params = {
-            "where": f"(title,eq,\"{content['title']}\")"
-        }
+        # URLs for both similarity tables
+        similarity_table_urls = [
+            "https://mtoft20-potm.hf.space/api/v1/db/data/noco/p9pozkcw81t9aee/mtsx4yp45gi12tm",
+            "https://mtoft20-potm.hf.space/api/v1/db/data/noco/p9pozkcw81t9aee/mca47f9wyoubouk"
+        ]
         
-        response = requests.get(similarity_table_url, headers=headers, params=params)
+        similar_items = []
         
-        if response.status_code == 200:
-            data = response.json()
-            if data and len(data.get('list', [])) > 0:
-                # Get similar items from stored data
-                similar_items = json.loads(data['list'][0]['similar_items'])
-                
-                # Limit to requested number
-                similar_items = similar_items[:n_recommendations]
-                
-                # Get full content details for each similar item
-                similar_content = []
-                for item in similar_items:
-                    # Query main content table for full details
-                    content_params = {
-                        "where": f"(title,eq,\"{item['title']}\")"
-                    }
-                    content_response = requests.get(NOCODB_URL, headers=headers, params=content_params)
-                    
-                    if content_response.status_code == 200:
-                        content_data = content_response.json()
-                        if content_data and len(content_data.get('list', [])) > 0:
-                            content_dict = content_data['list'][0]
-                            content_dict['similarity'] = f"{item['similarity']:.2%}"
-                            similar_content.append(content_dict)
+        # Check both tables for similarities
+        for table_url in similarity_table_urls:
+            params = {
+                "where": f"(title,eq,\"{content['title']}\")"
+            }
+            
+            response = requests.get(table_url, headers=headers, params=params)
+            
+            if response.status_code == 200:
+                data = response.json()
+                if data and len(data.get('list', [])) > 0:
+                    # Get similar items from stored data
+                    table_items = json.loads(data['list'][0]['similar_items'])
+                    similar_items.extend(table_items)
+        
+        if similar_items:
+            # Sort by similarity score and limit to requested number
+            similar_items.sort(key=lambda x: x['similarity'], reverse=True)
+            similar_items = similar_items[:n_recommendations]
+            
+            # Get full content details for each similar item
+            similar_content = []
+            for item in similar_items:
+                # Query main content table for full details
+                content_params = {
+                    "where": f"(title,eq,\"{item['title']}\")"
+                }
+                content_response = requests.get(NOCODB_URL, headers=headers, params=content_params)
                 
-                return similar_content
+                if content_response.status_code == 200:
+                    content_data = content_response.json()
+                    if content_data and len(content_data.get('list', [])) > 0:
+                        content_dict = content_data['list'][0]
+                        content_dict['similarity'] = f"{item['similarity']:.2%}"
+                        similar_content.append(content_dict)
             
+            return similar_content
+        
         return []
     except Exception as e:
         st.error(f"Error fetching similar content: {str(e)}")