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#1	"""
#2	Create your personal AI Assistant powered by memory that supports both text and images and remembers your preferences
#3
#4	In order to run this file, you need to set up your Mem0 API at Mem0 platform and also need a OpenAI API key.
#5	export OPENAI_API_KEY="your_openai_api_key"
#6	export MEM0_API_KEY="your_mem0_api_key"
#7	"""
#8
#9	import base64
#10	from pathlib import Path
#11
#12	from agno.agent import Agent
#13	from agno.media import Image
#14	from agno.models.openai import OpenAIChat
#15
#16	from mem0 import MemoryClient
#17
#18	# Initialize the Mem0 client
#19	client = MemoryClient()
#20
#21	# Define the agent
#22	agent = Agent(
#23	name="Personal Agent",
#24	model=OpenAIChat(id="gpt-4.1-nano-2025-04-14"),
#25	description="You are a helpful personal agent that helps me with day to day activities."
#26	"You can process both text and images.",
#27	markdown=True,
#28	)
#29
#30
#31	# Function to handle user input with memory integration with support for images
#32	def chat_user(user_input: str = None, user_id: str = "user_123", image_path: str = None):
#33	if image_path:
#34	with open(image_path, "rb") as image_file:
#35	base64_image = base64.b64encode(image_file.read()).decode("utf-8")
#36
#37	# First: the text message
#38	text_msg = {"role": "user", "content": user_input}
#39
#40	# Second: the image message
#41	image_msg = {
#42	"role": "user",
#43	"content": {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}},
#44	}
#45
#46	# Send both as separate message objects
#47	client.add([text_msg, image_msg], user_id=user_id)
#48	print("✅ Image uploaded and stored in memory.")
#49
#50	if user_input:
#51	memories = client.search(user_input, user_id=user_id)
#52	memory_context = "\n".join(f"- {m['memory']}" for m in memories)
#53
#54	prompt = f"""
#55	You are a helpful personal assistant who helps user with his day-to-day activities and keep track of everything.
#56
#57	Your task is to:
#58	1. Analyze the given image (if present) and extract meaningful details to answer the user's question.
#59	2. Use your past memory of the user to personalize your answer.
#60	3. Combine the image content and memory to generate a helpful, context-aware response.
#61
#62	Here is what remember about the user:
#63	{memory_context}
#64
#65	User question:
#66	{user_input}
#67	"""
#68	if image_path:
#69	response = agent.run(prompt, images=[Image(filepath=Path(image_path))])
#70	else:
#71	response = agent.run(prompt)
#72	client.add(f"User: {user_input}\nAssistant: {response.content}", user_id=user_id)
#73	return response.content
#74
#75	return "No user input or image provided."
#76
#77
#78	# Example Usage
#79	user_id = "user_123"
#80	print(chat_user("What did I ask you to remind me about?", user_id))
#81	# # OUTPUT: You asked me to remind you to call your mom tomorrow. 📞
#82	#
#83	print(chat_user("When is my test?", user_id=user_id))
#84	# OUTPUT: Your pilot's test is on your birthday, which is in five days. You're turning 25!
#85	# Good luck with your preparations, and remember to take some time to relax amidst the studying.
#86
#87	print(
#88	chat_user(
#89	"This is the picture of what I brought with me in the trip to Bahamas",
#90	image_path="travel_items.jpeg", # this will be added to Mem0 memory
#91	user_id=user_id,
#92	)
#93	)
#94	print(chat_user("hey can you quickly tell me if brought my sunglasses to my trip, not able to find", user_id=user_id))
#95	# OUTPUT: Yes, you did bring your sunglasses on your trip to the Bahamas along with your laptop, face masks and other items..
#96	# Since you can't find them now, perhaps check the pockets of jackets you wore or in your luggage compartments.
#97

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