LangGraph Intro – Storing and Using Long-Term Memory in AI Agents with LangGraph
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LangGraph Intro – Storing and Using Long-Term Memory in AI Agents with LangGraph
4 698 просмотров · 1 г. назад
GrabDuck!
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4 698 просмотров · 1 г. назад
In this video, LangGraph Intro – Storing and Using Long-Term Memory in AI Agents with LangGraph, we dive into how to build smarter, more contextual AI agents by giving them long-term memory. Instead of forgetting everything between sessions, your agent can now remember details about users—even across different threads—thanks to the LangGraph store feature. You’ll see how to structure and store user-specific information and use it to enhance chatbot interactions both in Python and LangGraph Studio.
This is part of the Building AI Agents with LangGraph: A Beginner’s Guide series and will be especially useful if you’re working with autonomous agents, LangChain, or exploring how to build agentic workflows that scale.
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00:00 – Intro: What is Long-Term Memory in AI Agents
03:25 – Store Structure: Namespace, Key, Value
06:15 – Building the Chatbot with Long-Term Memory
11:24 – Demo: Testing the Chatbot with Long-Term Memory
13:52 – LangGraph Studio Demo: Memory Visualization
15:42 – Final Thoughts and What’s Next
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💡 Explore More:
Check out the GitHub repo with all the code we used in this session: https://github.com/esurovtsev/langgra...
#aidevelopment #aiintegration #aiprogramming
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