How to Add Memory to Your AI Agent Using LangChain (Step-by-Step Tutorial)
7/4/20251 min read
Building an AI agent is exciting, but what’s even more powerful? Giving your AI the ability to remember.
In this tutorial, you’ll learn how to add memory to your LangChain-powered AI agent, enabling it to remember what users say across turns, sessions, or even tasks.
We’ll cover two popular memory types:
ConversationBufferMemory — remembers the full conversation history
ConversationSummaryMemory — compresses old chats into summaries
Let’s start improving your chatbot’s brain.
Prerequisites
Already built your basic agent using LangChain and OpenAI (from our previous article)? Great! If not, follow that first.
Also, make sure you’ve installed LangChain and OpenAI:
Step 1: Set Up Your Chat Model
Step 2: Add Buffer Memory (Remembers Everything)
Test It:
➡️ Output: "Your name is Alice."
Step 3: Add Summary Memory (Saves Token Space)
When chats get long, you’ll want to summarize older turns:
It keeps the recent turns while summarizing earlier messages like:
➡️ "The user is discussing personal identity. Her name is Alice."
Step 4: Choose Which One to Use
Use BufferMemory for short, detailed conversations
Use SummaryMemory for long chats or low token usage
Optional: View the Memory Contents
Final Thoughts
Your AI agent is now much smarter and more human-like, capable of holding a flowing conversation.
In the next post, we’ll combine multiple memory types, buffer + summary + vector search, to create a multi-session memory agent that remembers even after restarts.