Wire normalize_facts into sync and async fact extraction paths

After parsing LLM JSON response, normalize facts before passing them
to the embedding model. Fixes 'list'/'dict' object has no attribute
'replace' when smaller LLMs return malformed fact objects.

mem0/memory/main.py

@@ -28,6 +28,7 @@ from mem0.memory.telemetry import capture_event
 from mem0.memory.utils import (
     extract_json,
     get_fact_retrieval_messages,
+    normalize_facts,
     parse_messages,
     parse_vision_messages,
     process_telemetry_filters,
@@ -37,8 +38,8 @@ from mem0.utils.factory import (
     EmbedderFactory,
     GraphStoreFactory,
     LlmFactory,
-    VectorStoreFactory,
     RerankerFactory,
+    VectorStoreFactory,
 )
 
 # Suppress SWIG deprecation warnings globally
@@ -451,6 +452,7 @@ class Memory(MemoryBase):
                     # Try extracting JSON from response using built-in function
                     extracted_json = extract_json(response)
                     new_retrieved_facts = json.loads(extracted_json)["facts"]
+                new_retrieved_facts = normalize_facts(new_retrieved_facts)
         except Exception as e:
             logger.error(f"Error in new_retrieved_facts: {e}")
             new_retrieved_facts = []
@@ -1477,6 +1479,7 @@ class AsyncMemory(MemoryBase):
                     # Try extracting JSON from response using built-in function
                     extracted_json = extract_json(response)
                     new_retrieved_facts = json.loads(extracted_json)["facts"]
+                new_retrieved_facts = normalize_facts(new_retrieved_facts)
         except Exception as e:
             logger.error(f"Error in new_retrieved_facts: {e}")
             new_retrieved_facts = []