123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990 |
- ---
- title: MultiOn
- ---
- Build personal browser agent remembers user preferences and automates web tasks. It integrates Mem0 for memory management with MultiOn for executing browser actions, enabling personalized and efficient web interactions.
- ## Overview
- In this example, we will create a Browser based AI Agent that searches [arxiv.org](https://arxiv.org) for research papers relevant to user's research interests.
- ## Setup and Configuration
- Install necessary libraries:
- ```bash
- pip install mem0ai multion
- ```
- First, we'll import the necessary libraries and set up our configurations.
- ```python
- import os
- from mem0 import Memory
- from multion.client import MultiOn
- # Configuration
- OPENAI_API_KEY = 'sk-xxx' # Replace with your actual OpenAI API key
- MULTION_API_KEY = 'your-multion-key' # Replace with your actual MultiOn API key
- USER_ID = "deshraj"
- # Set up OpenAI API key
- os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY
- # Initialize Mem0 and MultiOn
- memory = Memory()
- multion = MultiOn(api_key=MULTION_API_KEY)
- ```
- ## Add memories to Mem0
- Next, we'll define our user data and add it to Mem0.
- ```python
- # Define user data
- USER_DATA = """
- About me
- - I'm Deshraj Yadav, Co-founder and CTO at Mem0, interested in AI and ML Infrastructure.
- - Previously, I was a Senior Autopilot Engineer at Tesla, leading the AI Platform for Autopilot.
- - I built EvalAI at Georgia Tech, an open-source platform for evaluating ML algorithms.
- - Outside of work, I enjoy playing cricket in two leagues in the San Francisco.
- """
- # Add user data to memory
- memory.add(USER_DATA, user_id=USER_ID)
- print("User data added to memory.")
- ```
- ## Retrieving Relevant Memories
- Now, we'll define our search command and retrieve relevant memories from Mem0.
- ```python
- # Define search command and retrieve relevant memories
- command = "Find papers on arxiv that I should read based on my interests."
- relevant_memories = memory.search(command, user_id=USER_ID, limit=3)
- relevant_memories_text = '\n'.join(mem['text'] for mem in relevant_memories)
- print(f"Relevant memories:")
- print(relevant_memories_text)
- ```
- ## Browsing arXiv
- Finally, we'll use MultiOn to browse arXiv based on our command and relevant memories.
- ```python
- # Create prompt and browse arXiv
- prompt = f"{command}\n My past memories: {relevant_memories_text}"
- browse_result = multion.browse(cmd=prompt, url="https://arxiv.org/")
- print(browse_result)
- ```
- ## Conclusion
- By integrating Mem0 with MultiOn, you've created a personalized browser agent that remembers user preferences and automates web tasks. For more details and advanced usage, refer to the full [cookbook here](https://github.com/mem0ai/mem0/blob/main/cookbooks/mem0-multion.ipynb).
- ## Help
- - Feel free to visit our [Github](https://github.com/mem0ai/mem0) or [Mem0 Platform](https://app.mem0.ai/).
- - For any questions or assistance, please reach out to `taranjeetio` on [Discord](https://mem0.ai/discord).
|