[Update] Default LLM (#3587)

docs/integrations/agentops.mdx

@@ -49,7 +49,7 @@ local_config = {
     "llm": {
         "provider": "openai",
         "config": {
-            "model": "gpt-4o-mini",
+            "model": "gpt-4.1-nano-2025-04-14",
             "temperature": 0.1,
             "max_tokens": 2000,
         },

docs/integrations/agno.mdx

@@ -36,7 +36,7 @@ from agno.tools.mem0 import Mem0Tools
 
 agent = Agent(
     name="Memory Agent",
-    model=OpenAIChat(id="gpt-4o-mini"),
+    model=OpenAIChat(id="gpt-4.1-nano-2025-04-14"),
     tools=[Mem0Tools()],
     description="An assistant that remembers and personalizes using Mem0 memory."
 )

docs/integrations/keywords.mdx

@@ -55,7 +55,7 @@ config = {
     "llm": {
         "provider": "openai",
         "config": {
-            "model": "gpt-4o-mini",
+            "model": "gpt-4.1-nano-2025-04-14",
             "temperature": 0.0,
             "api_key": keywordsai_api_key,
             "openai_base_url": base_url,
@@ -101,7 +101,7 @@ messages = [
 
 # Add memory and generate a response
 response = client.chat.completions.create(
-    model="openai/gpt-4o",
+    model="openai/gpt-4.1-nano",
     messages=messages,
     extra_body={
         "mem0_params": {

docs/integrations/langchain.mdx

@@ -39,7 +39,7 @@ load_dotenv()
 # os.environ["MEM0_API_KEY"] = "your-mem0-api-key"
 
 # Initialize LangChain and Mem0
-llm = ChatOpenAI(model="gpt-4o-mini")
+llm = ChatOpenAI(model="gpt-4.1-nano-2025-04-14")
 mem0 = MemoryClient()
 ```
 

docs/integrations/livekit.mdx

@@ -147,7 +147,7 @@ async def entrypoint(ctx: JobContext):
 
     session = AgentSession(
         stt=deepgram.STT(),
-        llm=openai.LLM(model="gpt-4o-mini"),
+        llm=openai.LLM(model="gpt-4.1-nano-2025-04-14"),
         tts=openai.TTS(voice="ash",),
         turn_detection=EnglishModel(),
         vad=silero.VAD.load(),

docs/integrations/llama-index.mdx

@@ -83,7 +83,7 @@ config = {
     "llm": {
         "provider": "openai",
         "config": {
-            "model": "gpt-4o",
+            "model": "gpt-4.1-nano-2025-04-14",
             "temperature": 0.2,
             "max_tokens": 2000,
         },
@@ -116,7 +116,7 @@ from dotenv import load_dotenv
 load_dotenv()
 
 # os.environ["OPENAI_API_KEY"] = "<your-openai-api-key>"
-llm = OpenAI(model="gpt-4o-mini")
+llm = OpenAI(model="gpt-4.1-nano-2025-04-14")
 ```
 
 ### SimpleChatEngine

docs/integrations/mastra.mdx

@@ -106,7 +106,7 @@ const mem0Agent = new Agent({
     Use the Mem0-memorize tool to save important information that might be useful later.
     Use the Mem0-remember tool to recall previously saved information when answering questions.
   `,
-  model: openai('gpt-4o'),
+  model: openai('gpt-4.1-nano'),
   tools: { mem0RememberTool, mem0MemorizeTool },
 });
 ```

docs/integrations/openai-agents-sdk.mdx

@@ -63,7 +63,7 @@ agent = Agent(
     Use the save_memory tool to store important information about the user.
     Always personalize your responses based on available memory.""",
     tools=[search_memory, save_memory],
-    model="gpt-4o"
+    model="gpt-4.1-nano-2025-04-14"
 )
 
 def chat_with_agent(user_input: str, user_id: str) -> str:
@@ -114,7 +114,7 @@ travel_agent = Agent(
     understand the user's travel preferences and history before making recommendations.
     After providing your response, use store_conversation to save important details.""",
     tools=[search_memory, save_memory],
-    model="gpt-4o"
+    model="gpt-4.1-nano-2025-04-14"
 )
 
 health_agent = Agent(
@@ -123,7 +123,7 @@ health_agent = Agent(
     understand the user's health goals and dietary preferences.
     After providing advice, use store_conversation to save relevant information.""",
     tools=[search_memory, save_memory],
-    model="gpt-4o"
+    model="gpt-4.1-nano-2025-04-14"
 )
 
 # Triage agent with handoffs
@@ -134,7 +134,7 @@ triage_agent = Agent(
     For health-related questions (fitness, diet, wellness, exercise), hand off to the Health Advisor.
     For general questions, handle them directly using available tools.""",
     handoffs=[travel_agent, health_agent],
-    model="gpt-4o"
+    model="gpt-4.1-nano-2025-04-14"
 )
 
 def chat_with_handoffs(user_input: str, user_id: str) -> str: