Update gradio_app.py

gradio_app.py

@@ -77,18 +77,22 @@ def news_analysis(text):
         # Prepare results for JSON output
         json_results = response.json()
 
-        # Preprocess to convert the claim_objects from a dict to a list
+        # Preprocess to convert 'claim_objects' from any type to a list
         for result in json_results:
-            if isinstance(result.get('claim_objects'), dict):
-                result['claim_objects'] = list(result['claim_objects'].values())
+            # Ensure 'claim_objects' is a list, or if it's a dict, convert it to a list of its values, else leave it as an empty list
+            claim_objects = result.get('claim_objects')
+            if isinstance(claim_objects, dict):
+                result['claim_objects'] = list(claim_objects.values())
+            elif not isinstance(claim_objects, list):
+                result['claim_objects'] = []  # Default to empty list if it's not a list or dict
         
-        # Flatten the JSON
+        # Flatten the JSON for 'claim_objects'
         dataframe_results = pd.json_normalize(
             json_results,
-            record_path=['claim_objects'],                # Nested array to flatten
-            meta=['doc_id', 'details', 'domain'],         # Top-level fields to retain
-            sep='_',                                      # Separator for nested fields
-            errors='ignore'                               # To handle cases with missing keys
+            record_path=['claim_objects'],                  # Nested array to flatten
+            meta=['doc_id', 'details', 'domain'],           # Top-level fields to retain
+            sep='_',                                        # Separator for nested fields
+            errors='ignore'                                 # To handle cases with missing keys
         )
         return json_results, dataframe_results
     except Exception as e:
@@ -111,19 +115,28 @@ def claim_verification(text):
         # Prepare results for JSON output
         json_results = response.json()
 
-        # Preprocess to convert nested fields from dict to list
+        # Preprocess to convert nested fields from any type to lists
         for result in json_results:
-            # Convert 'support' to a list if it's a dictionary
-            if isinstance(result.get('support'), dict):
-                result['support'] = list(result['support'].values())
+            # Ensure 'support' is a list, or if it's a dict, convert it to a list of its values, else leave it as an empty list
+            support = result.get('support')
+            if isinstance(support, dict):
+                result['support'] = list(support.values())
+            elif not isinstance(support, list):
+                result['support'] = []  # Default to empty list if it's not a list or dict
             
-            # Convert 'refute' to a list if it's a dictionary
-            if isinstance(result.get('refute'), dict):
-                result['refute'] = list(result['refute'].values())
+            # Ensure 'refute' is a list, or if it's a dict, convert it to a list of its values, else leave it as an empty list
+            refute = result.get('refute')
+            if isinstance(refute, dict):
+                result['refute'] = list(refute.values())
+            elif not isinstance(refute, list):
+                result['refute'] = []  # Default to empty list if it's not a list or dict
             
-            # Convert 'no_info' to a list if it's a dictionary
-            if isinstance(result.get('no_info'), dict):
-                result['no_info'] = list(result['no_info'].values())
+            # Ensure 'no_info' is a list, or if it's a dict, convert it to a list of its values, else leave it as an empty list
+            no_info = result.get('no_info')
+            if isinstance(no_info, dict):
+                result['no_info'] = list(no_info.values())
+            elif not isinstance(no_info, list):
+                result['no_info'] = []  # Default to empty list if it's not a list or dict
         
         # Flatten the JSON
         dataframe_results = pd.json_normalize(