Give Long Term Memory for AI Agents, Here is how

🚀 Welcome to an exciting journey into AI memory integration with mem0! 🚀 In this video, we'll explore how to enhance your AI agents by integrating long-term memory using mem0, previously known as EmbedChain. mem0: Give Long Term Memory for AI Agents, Here is how By the end of this tutorial, you'll be able to: 🔹 Implement multi-level memory in AI agents 🔹 Achieve adaptive personalisation 🔹 Utilise a developer-friendly API for seamless integration 🔹 Ensure cross-platform consistency 🔹 Run mem0 locally on your computer 🔧 Steps Covered in This Video: Installation and Setup pip install mem0ai Export your OpenAI API key Initialise mem0 Memory Import and initialise the memory function Storing and Retrieving Memory Store memory from unstructured text Retrieve all stored memories Searching and Updating Memory Perform semantic searches within memory Update existing memories Deleting Memory and Viewing History Delete specific memories View change history of memories Integration with AI Agents Create tools and agents for memory handling Example using Praison AI tools creator for enhanced functionality 🔗 Links: Patreon: https://patreon.com/MervinPraison Ko-fi: https://ko-fi.com/mervinpraison Discord: https://discord.gg/nNZu5gGT59 Twitter / X : https://twitter.com/mervinpraison GPU for 50% of it's cost: https://bit.ly/mervin-praison Coupon: MervinPraison (50% Discount) Code: https://mer.vin/2024/07/mem0-and-praison-ai-integration/ https://mer.vin/2024/07/mem0-example-code/ 🛠️ Tools Used: mem0 (EmbedChain) OpenAI API Praison AI Various Python libraries 📚 Resources: mem0 Documentation OpenAI API Key Generation Praison AI Tools 👍 Don't forget to like, share, and subscribe for more AI tutorials! 🔔 Hit the bell icon to stay updated with the latest content! Timestamps: 0:00 - Introduction and Overview 0:26 - Features and Benefits of mem0 1:00 - Installation and Setup 1:26 - Initialising mem0 Memory 1:57 - Storing and Retrieving Memory 2:42 - Searching for Memories