pacjam

7 ms·

1. 31.▲
   The software stack for LLM agents (in 2024)(letta.com)

   2 points by pacjam 2y ago|0 comments
2. 32.▲
   by pacjam 3y ago

   Super cool, as LLM agents continue to grow in popularity the field needs more open datasets for function calling + open models finetuned specifically for function calling. Excited to try and integrate the new function calling model into Mem
3. 33.▲
   by pacjam 3y ago

   Thanks for checking out the paper! Just to clarify in case there was any misunderstanding, recursive summarization is just one part of the memory management in MemGPT: as you mentioned, in MemGPT the conversation queue is managed via recurs
4. 34.▲
   by pacjam 3y ago

   These are all great points - who or what you ask to manage memory is a design decision and IMO there's two main ways to do it (in the context of chatbots): * implicit memory management, where the "main LLM" (or for chat, the
5. 35.▲
   by pacjam 3y ago

   Grammar-based sampling is a great idea and a perfect fit for something like MemGPT! In our experiments using MemGPT with non-gpt-4 models, the biggest issue impacting performance ended up being incorrect use of function parameters and funct
6. 36.▲
   by pacjam 3y ago

   Interesting analogy! There's no clear infinite tape equivalent in MemGPT, but you can view the virtual context loosely as a tape. Moving the head could correspond to MemGPT indexing into virtual context - if the data is in-context (ins
7. 37.▲
   by pacjam 3y ago

   Awesome, feel free to open issues or PRs to our repo if you want to contribute! It's all open source and under Apache 2.0, and we're actively looking at integrating common workflows to the CLI. You're correct that MemGPT does
8. 38.▲
   by pacjam 3y ago

   If you have a chance try it out via the Discord bot or with the GitHub repo! Or even just check out the short demo GIFs we released (at https://github.com/cpacker/memgpt ) to get an idea of the MemGPT inputs/output
9. 39.▲
   by pacjam 3y ago

   Thanks for your interest! Question - does the title of the chat ever change after it's first assigned? If so, using a recursive summary to refresh the title sounds like a reasonable idea (especially if you're already computing a s
10. 40.▲
    by pacjam 3y ago

    Happy to chat more about other ideas in this direction! There are plenty of things we tried with varying degrees of success (especially when trying to get MemGPT to work on less powerful LLMs), and we'd be interested in hearing what yo
11. 41.▲
    by pacjam 3y ago

    Recursive summarization is a simple and popular way to provide the illusion of infinite context (when you need to free up space, just summarize the oldest N messages into 1 summary message). It's lossy and you'll inevitably lose i
12. 42.▲
    by pacjam 3y ago

    Hey all, MemGPT authors here! Happy to answer any questions about the implementation. If you want to try it out yourself, we have a Discord bot up-and-running on the MemGPT Discord server ( https://discord.gg/9GEQrxmVyE ) whe
13. 43.▲
    by pacjam 3y ago

    Thanks @upghost
14. 44.▲
    by pacjam 3y ago

    This is similar to how our external context is implemented under the hood - you might be interested in our perpetual chat bot example in the GitHub repo ( https://github.com/cpacker/MemGPT ), the message traces in the de
15. 45.▲
    by pacjam 3y ago

    If you want to try the MemGPT Discord chatbot, join the Discord server (linked above), then check out the #memgpt channel to start messaging the bot. If you want to run the chatbot or API docs examples locally, you can follow the instructio
16. 46.▲
    by pacjam 3y ago

    Update - we just released a Discord perpetual chatbot implemented on top of MemGPT, you can try it here: https://discord.gg/9GEQrxmVyE You can also run the chatbot demo + a doc QA bot demo (where you can ask MemGPT about AP
17. 47.▲
    by pacjam 3y ago

    Thanks for your feedback @skrebbel. We called it MemGPT - in reference to teaching LLMs how to manage their own memory hierarchy. The idea and title evolved when we realized we were teaching the LLM to read/write, and this enabled perp
18. 48.▲
    by pacjam 3y ago

    Thanks for your interest! Left a comment on the other thread
19. 49.▲
    by pacjam 3y ago

    Explicit memory management (MemGPT-style) vs implicit/external memory management is an interesting tradeoff. Like you said, adding all the instructions on how to manage memory consumes ~1k tokens (using the default prompts on our MemGP
20. 50.▲
    by pacjam 3y ago

    Hey OP, thank you for the post. In this work, we are looking at one particular functionality of an OS - memory management. The project started off motivated by trying to extend context length for a project we were working on. The analogy to
21. 51.▲
    by pacjam 3y ago

    Thanks for checking out our work! Yeah, great point, this is even more critical in those scenarios when you have very limited memory. You can play around with different context sizes using the code on GitHub: https://github.com&#
22. 52.▲
    by pacjam 3y ago

    Hey all, I’m the lead author on this work. Thanks to the OP for posting, and for all the interest and feedback. To clarify a few points: the goal of this work is to investigate the extent to which an LLM can manage memory and different memo