Github's Daily Top Pick: Add Super Memory to AI Agents, Never Offline for 24 Hours

A few days ago, a friend complained that the AI robot he made was like an amnesiac. Every time it restarts, it forgets everything we talked about before, and you have to repeat your preferences all over again.

The worst thing is that if you want the robot to be online 24 hours a day, the cost of calling LLM is so high that it hurts him.

So, today I'm going to introduce you to memU, an open-source memory framework that won Github's daily top pick. In short, it's like giving AI a human-like super brain, so that your robot doesn't have amnesia 24 hours a day and can think actively.

Open source address: https://github.com/NevaMind-AI/memU

In fact, memU is an agent memory framework. Don't think of it as too complicated. Just think of it as AI's exclusive hippocampus. Our human hippocampus is responsible for storing and organizing memories, and MemU is the same.

It's not like ordinary storage tools that only pile up data rigidly, but it sorts information into categories like we do when we take notes, understands the meaning inside, and can store it for a long time, allowing AI to truly have the ability to remember everything.

How amazing is this thing? Let me tell you in detail. First of all, the most intuitive feeling is that the robot will take the initiative to remember things. You casually mentioned that you are a vegetarian, and it silently remembered it.

The next time you ask for restaurant recommendations, it will directly give you a list of vegetarian restaurants, without you having to repeat it again. And this is not simple rote memorization, it will understand the context like a person.

For example, if you said you wanted to learn Python before, and then you mentioned that you wanted to make a crawler, it can connect these two things and recommend relevant learning resources to you.

In terms of cost, it really saves a lot of money. memU will cache those insights that have been remembered to avoid repeated calls to LLM. It's like you memorizing the multiplication table, so you don't have to do vertical calculations every time you do addition, subtraction, multiplication, and division.

In this way, the cost of long-term operation of the robot is directly reduced, and being online 24 hours a day is no longer a bottomless pit of burning money.

What I find most distinctive is the custom memory rules, which are very practical. Everyone's usage scenarios are different, and their needs are also different. MemU is very flexible. You can define your own memory types. For example, if you are in sales, you can add a customer preference type.

If you are in R&D, you can add a technology stack type. You can also classify and adjust the accuracy of retrieval to fully fit your business scenarios.

For example, for the R&D team, each person's technology stack is different, so you can customize exclusive memory categories for the AI assistant to specifically record each person's technology stack.

Customize memory types and categories, add the technology stack type, and divide it into Python skills and Go language skills, and re-initialize the service.

In this way, AI can accurately distinguish each person's skills, which is especially convenient when doing team skill inventory, without having to ask one by one.

Overall, memU is really suitable for developers who want to create a truly intelligent and non-amnesiac AI robot. Whether you are playing around as an individual or a formal company project, this framework can save you a lot of trouble.

Currently, this open source project with over 8000 stars is very popular, and you can try it if you are interested.