diff --git a/examples/misc/diet_assistant_voice_cartesia.py b/examples/misc/diet_assistant_voice_cartesia.py
new file mode 100644
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+++ b/examples/misc/diet_assistant_voice_cartesia.py
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+"""Simple Voice Agent with Memory: Personal Food Assistant.
+A food assistant that remembers your dietary preferences and speaks recommendations
+Powered by Agno + Cartesia + Mem0
+
+export MEM0_API_KEY=your_mem0_api_key
+export OPENAI_API_KEY=your_openai_api_key
+export CARTESIA_API_KEY=your_cartesia_api_key
+"""
+
+from textwrap import dedent
+from agno.agent import Agent
+from agno.models.openai import OpenAIChat
+from agno.tools.cartesia import CartesiaTools
+from agno.utils.audio import write_audio_to_file
+from mem0 import MemoryClient
+
+memory_client = MemoryClient()
+USER_ID = "food_user_01"
+
+# Agent instructions
+agent_instructions = dedent(
+    """Follow these steps SEQUENTIALLY to provide personalized food recommendations with voice:
+    1. Analyze the user's food request and identify what type of recommendation they need.
+    2. Consider their dietary preferences, restrictions, and cooking habits from memory context.
+    3. Generate a personalized food recommendation based on their stored preferences.
+    4. Analyze the appropriate tone for the response (helpful, enthusiastic, cautious for allergies).
+    5. Call `list_voices` to retrieve available voices.
+    6. Select a voice that matches the helpful, friendly tone.
+    7. Call `text_to_speech` to generate the final audio recommendation.
+    """
+)
+
+# Simple agent that remembers food preferences
+food_agent = Agent(
+    name="Personal Food Assistant",
+    description="Provides personalized food recommendations with memory and generates voice responses using Cartesia TTS tools.",
+    instructions=agent_instructions,
+    model=OpenAIChat(id="gpt-4o"),
+    tools=[CartesiaTools(voice_localize_enabled=True)],
+    show_tool_calls=True,
+)
+
+
+def get_food_recommendation(user_query: str, user_id):
+    """Get food recommendation with memory context"""
+
+    # Search memory for relevant food preferences
+    memories_result = memory_client.search(
+        query=user_query,
+        user_id=user_id,
+        limit=5
+    )
+
+    # Add memory context to the message
+    memories = [f"- {result['memory']}" for result in memories_result]
+    memory_context = "Memories about user that might be relevant:\n" + "\n".join(memories)
+
+    # Combine memory context with user request
+    full_request = f"""
+    {memory_context}
+
+    User: {user_query}
+
+    Answer the user query based on provided context and create a voice note.
+    """
+
+    # Generate response with voice (same pattern as translator)
+    food_agent.print_response(full_request)
+    response = food_agent.run_response
+
+    # Save audio file
+    if response.audio:
+        import time
+        timestamp = int(time.time())
+        filename = f"food_recommendation_{timestamp}.mp3"
+        write_audio_to_file(
+            response.audio[0].base64_audio,
+            filename=filename,
+        )
+        print(f"Audio saved as {filename}")
+
+    return response.content
+
+
+def initialize_food_memory(user_id):
+    """Initialize memory with food preferences"""
+    messages = [
+        {
+            "role": "user",
+            "content": "Hi, I'm Sarah. I'm vegetarian and lactose intolerant. I love spicy food, especially Thai and Indian cuisine.",
+        },
+        {
+            "role": "assistant",
+            "content": "Hello Sarah! I've noted that you're vegetarian, lactose intolerant, and love spicy Thai and Indian food.",
+        },
+        {
+            "role": "user",
+            "content": "I prefer quick breakfasts since I'm always rushing, but I like cooking elaborate dinners. I also meal prep on Sundays.",
+        },
+        {
+            "role": "assistant",
+            "content": "Got it! Quick breakfasts, elaborate dinners, and Sunday meal prep. I'll remember this for future recommendations.",
+        },
+        {
+            "role": "user",
+            "content": "I'm trying to eat more protein. I like quinoa, lentils, chickpeas, and tofu. I hate mushrooms though.",
+        },
+        {
+            "role": "assistant",
+            "content": "Perfect! I'll focus on protein-rich options like quinoa, lentils, chickpeas, and tofu, and avoid mushrooms.",
+        },
+    ]
+
+    memory_client.add(messages, user_id=user_id)
+    print("Food preferences stored in memory")
+
+
+# Initialize the memory for the user once in order for the agent to learn the user preference
+initialize_food_memory(user_id=USER_ID)
+
+print(get_food_recommendation("Which type of restaurants should I go tonight for dinner and cuisines preferred?", user_id=USER_ID))
+# OUTPUT: 🎵 Audio saved as food_recommendation_1750162610.mp3
+# For dinner tonight, considering your love for healthy spic optionsy, you could try a nice Thai, Indian, or Mexican restaurant.
+# You might find dishes with quinoa, chickpeas, tofu, and fresh herbs delightful. Enjoy your dinner!