Your AI agent is forgetting everything after each interaction? Yeah, that's a problem. You need some kind of memory system if you want to build anything more complex than a chatty chatbot.
What is Agent Memory?
Agent memory is just a fancy term for "the thing that makes AI agents not forget stuff." It's a system that stores and retrieves information across interactions. Think of it like your browser's cookies, but way smarter.
There are two types of memory in AI agents:
- Short-term memory (working memory): used for the current session
- Long-term memory: persistent across sessions
You need both to build something useful.
MrMemory: A Managed Memory API
MrMemory is a managed memory API that provides scalable long-term memory for AI agents. It's like a super-smart, super-reliable cookie jar. Here's an example of using it:
from mrmemory import MrMemory
client = MrMemory(api_key="your-key")
client.remember("user prefers dark mode", tags=["preferences"])
And here's how you can recall the user's preference:
results = client.recall("what theme does the user like?")
print(results) # Output: "dark mode"
Other Options
If MrMemory isn't your thing, there are other alternatives:
- Mem0: A bit more complicated to set up, but scalable and reliable.
- Zep: Another managed memory API with a steeper learning curve.
- MemGPT: Specialized for GPT-like models, might not be suitable for others.
Conclusion
Implementing robust agent memory is hard. You need to get both short-term and long-term memory working together in harmony. With MrMemory, you can at least get the long-term memory part right.
Try it out and see if it makes a difference.
Related reading:
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