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Adding Long-Term Memory to a chatbot with Mem0 | by Rajesh Nayak | Oct, 2024 | Medium

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In my previous post titled Next-Gen Memory for AI Agentic Systems: Mem0, I explored Mem0, an open source library providing a self-improving memory layer for LLM applications. We looked at the typical use cases and the features of Mem0 that enable that. In this post, we will implement long term memory for a simple chatbot using Mem0 in python. Let’s dive directly into the code. We will start with a simple chatbot using the OpenAI API. We’ll create a python file basic_chatbot.py and add the below code for a basic chatbot Please note that we have provided the chatbot with the ability to remember the current conversation i.e. session memory by creating a conversation variable and appending both the user’s input and the assistant’s response to this variable. We then run the python file and provide a food preference “I am a vegetarian” to the Assistant. Next, we ask the Assistant to recommend 2 snack options. Since the Assistant has the context of the previous messages, it responds with two

Adding Long-Term Memory to a chatbot with Mem0 Rajesh Nayak 8 min read · Oct 1, 2024 -- 1 Listen Share Press enter or click to view image in full size Author generated Image using Microsoft Designer In my previous post titled Next-Gen Memory for AI Agentic Systems: Mem0 , I explored Mem0, an open source library providing a self-improving memory layer for LLM applications. We looked at the typical use cases and the features of Mem0 that enable that. In this post, we will implement long term memory for a simple chatbot using Mem0 in python. Let’s dive directly into the code. A Simple Chatbot wit

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