refactor: v2 search and update examples (#3508)

examples/mem0-demo/app/api/chat/route.ts

@@ -70,7 +70,7 @@ const retrieveMemories = (memories: any) => {
 export async function POST(req: Request) {
   const { messages, system, tools, userId } = await req.json();
 
-  const memories = await getMemories(messages, { user_id: userId, rerank: true, threshold: 0.1, output_format: "v1.0" });
+  const memories = await getMemories(messages, { user_id: userId, rerank: true, threshold: 0.1 });
   const mem0Instructions = retrieveMemories(memories);
 
   const result = streamText({

examples/misc/fitness_checker.py

@@ -27,7 +27,7 @@ agent = Agent(
 # Store user preferences as memory
 def store_user_preferences(conversation: list, user_id: str = USER_ID):
     """Store user preferences from conversation history"""
-    memory_client.add(conversation, user_id=user_id, output_format="v1.1")
+    memory_client.add(conversation, user_id=user_id)
 
 
 # Memory-aware assistant function

examples/misc/multillm_memory.py

@@ -99,7 +99,6 @@ Provide actionable insights in your area of expertise."""
         user_id=project_id,  # Project-level memory
         agent_id=specialist,  # Agent-specific memory
         metadata={"contributor": specialist, "task_type": "research", "model_used": spec_info["model"]},
-        output_format="v1.1",
     )
 
     return result

examples/misc/personal_assistant_agno.py

@@ -44,7 +44,7 @@ def chat_user(user_input: str = None, user_id: str = "user_123", image_path: str
         }
 
         # Send both as separate message objects
-        client.add([text_msg, image_msg], user_id=user_id, output_format="v1.1")
+        client.add([text_msg, image_msg], user_id=user_id)
         print("✅ Image uploaded and stored in memory.")
 
     if user_input:

examples/misc/personalized_search.py

@@ -66,7 +66,7 @@ def setup_user_history(user_id):
 
     logger.info(f"Setting up user history for {user_id}")
     for conversation in conversations:
-        mem0_client.add(conversation, user_id=user_id, output_format="v1.1")
+        mem0_client.add(conversation, user_id=user_id)
 
 
 def get_user_context(user_id, query):
@@ -209,7 +209,7 @@ def store_search_interaction(user_id, original_query, agent_response):
             {"role": "assistant", "content": f"Provided personalized results based on user preferences: {agent_response}"}
         ]
 
-        mem0_client.add(messages=interaction, user_id=user_id, output_format="v1.1")
+        mem0_client.add(messages=interaction, user_id=user_id)
 
         logger.info(f"Stored search interaction for user {user_id}")