[Update] Default LLM (#3587)

docs/examples/ai_companion_js.mdx

@@ -45,7 +45,7 @@ ${memoriesStr}`;
   ];
   
   const response = await openaiClient.chat.completions.create({
-    model: "gpt-4o-mini",
+    model: "gpt-4.1-nano-2025-04-14",
     messages: messages
   });
   

docs/examples/collaborative-task-agent.mdx

@@ -51,7 +51,7 @@ class CollaborativeAgent:
             {"role": "user", "content": f"Prompt: {prompt}\nContext:\n{context}"}
         ]
         reply = client.chat.completions.create(
-            model="gpt-4o-mini",
+            model="gpt-4.1-nano-2025-04-14",
             messages=messages
         ).choices[0].message.content.strip()
         self.add_message("assistant", "assistant", reply)

docs/examples/eliza_os.mdx

@@ -44,7 +44,7 @@ MEM0_API_KEY= # Mem0 API Key (get from https://app.mem0.ai/dashboard/api-keys)
 MEM0_USER_ID= # Default: eliza-os-user
 MEM0_PROVIDER= # Default: openai
 MEM0_PROVIDER_API_KEY= # API Key for the provider (OpenAI, Anthropic, etc.)
-SMALL_MEM0_MODEL= # Default: gpt-4o-mini
+SMALL_MEM0_MODEL= # Default: gpt-4.1-nano
 MEDIUM_MEM0_MODEL= # Default: gpt-4o
 LARGE_MEM0_MODEL= # Default: gpt-4o
 ```

docs/examples/llama-index-mem0.mdx

@@ -20,7 +20,7 @@ import os
 from llama_index.llms.openai import OpenAI
 
 os.environ["OPENAI_API_KEY"] = "<your-openai-api-key>"
-llm = OpenAI(model="gpt-4o")
+llm = OpenAI(model="gpt-4.1-nano-2025-04-14")
 ```
 
 Initialize the Mem0 client. You can find your API key [here](https://app.mem0.ai/dashboard/api-keys). Read about Mem0 [Open Source](https://docs.mem0.ai/open-source/overview).

docs/examples/llamaindex-multiagent-learning-system.mdx

@@ -81,7 +81,7 @@ class MultiAgentLearningSystem:
 
     def __init__(self, student_id: str):
         self.student_id = student_id
-        self.llm = OpenAI(model="gpt-4o", temperature=0.2)
+        self.llm = OpenAI(model="gpt-4.1-nano-2025-04-14", temperature=0.2)
 
         # Memory context for this student
         self.memory_context = {"user_id": student_id, "app": "learning_assistant"}

docs/examples/mem0-mastra.mdx

@@ -97,7 +97,7 @@ export const mem0Agent = new Agent({
   instructions: `
     You are a helpful assistant that has the ability to memorize and remember facts using Mem0.
   `,
-  model: openai('gpt-4o'),
+  model: openai('gpt-4.1-nano'),
   tools: { mem0RememberTool, mem0MemorizeTool },
 });
 ```

docs/examples/mem0-openai-voice-demo.mdx

@@ -162,7 +162,7 @@ def create_memory_voice_agent():
             Use the search_memories tool when you need context from past conversations or user asks you to recall something.
             """,
         ),
-        model="gpt-4o",
+        model="gpt-4.1-nano-2025-04-14",
         tools=[save_memories, search_memories],
     )
     
@@ -171,7 +171,7 @@ def create_memory_voice_agent():
 
 This function:
 - Creates an OpenAI Agent with specific instructions
-- Configures it to use gpt-4o (you can use other models)
+- Configures it to use gpt-4.1-nano (you can use other models)
 - Registers the memory-related tools with the agent
 - Uses `prompt_with_handoff_instructions` to include standard voice agent behaviors
 
@@ -369,7 +369,7 @@ def create_memory_voice_agent():
             Use the search_memories tool when you need context from past conversations or user asks you to recall something.
             """,
         ),
-        model="gpt-4o",
+        model="gpt-4.1-nano-2025-04-14",
         tools=[save_memories, search_memories],
     )
     

docs/examples/memory-guided-content-writing.mdx

@@ -103,7 +103,7 @@ Preferences:
     ]
 
     response = openai.chat.completions.create(
-        model="gpt-4o-mini",
+        model="gpt-4.1-nano-2025-04-14",
         messages=messages
     )
     clean_response = response.choices[0].message.content.strip()

docs/examples/openai-inbuilt-tools.mdx

@@ -119,7 +119,7 @@ const carRecommendationTool = zodResponsesFunction({
 
 // Use the tool in your OpenAI request
 const response = await openAIClient.responses.create({
-    model: "gpt-4o",
+    model: "gpt-4.1-nano-2025-04-14",
     tools: [{ type: "web_search_preview" }, carRecommendationTool],
     input: `${getMemoryString(relevantMemories)}\n${userInput}`,
 });
@@ -131,7 +131,7 @@ Combine memory with web search for up-to-date recommendations:
 
 ```javascript
 const response = await openAIClient.responses.create({
-    model: "gpt-4o",
+    model: "gpt-4.1-nano-2025-04-14",
     tools: [{ type: "web_search_preview" }, carRecommendationTool],
     input: `${getMemoryString(relevantMemories)}\n${userInput}`,
 });
@@ -202,7 +202,7 @@ async function main(memory = false) {
   }
 
   const response = await openAIClient.responses.create({
-    model: "gpt-4o",
+    model: "gpt-4.1-nano-2025-04-14",
     tools: [{ type: "web_search_preview" }, tool],
     input: `${getMemoryString(relevantMemories)}\n${input}`,
   });

docs/examples/personal-ai-tutor.mdx

@@ -58,7 +58,7 @@ class PersonalAITutor:
         """
         # Start a streaming response request to the AI
         response = self.client.responses.create(
-            model="gpt-4o",
+            model="gpt-4.1-nano-2025-04-14",
             instructions="You are a personal AI Tutor.",
             input=question,
             stream=True

docs/examples/personal-travel-assistant.mdx

@@ -35,7 +35,7 @@ config = {
     "llm": {
         "provider": "openai",
         "config": {
-            "model": "gpt-4o",
+            "model": "gpt-4.1-nano-2025-04-14",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -76,7 +76,7 @@ class PersonalTravelAssistant:
 
         # Generate response using Responses API
         response = self.client.responses.create(
-            model="gpt-4o",
+            model="gpt-4.1-nano-2025-04-14",
             input=prompt
         )
 
@@ -140,9 +140,9 @@ class PersonalTravelAssistant:
             prompt = f"User input: {question}\n Previous memories: {previous_memories}"
         self.messages.append({"role": "user", "content": prompt})
 
-        # Generate response using GPT-4o
+        # Generate response using gpt-4.1-nano
         response = self.client.chat.completions.create(
-            model="gpt-4o",
+            model="gpt-4.1-nano-2025-04-14"2025-04-14",
             messages=self.messages
         )
         answer = response.choices[0].message.content