Open Interpreter Hackathon

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Hackathon Starts

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Community Evaluation Starts

We have extended the Hackathon by 12 more hours due to the high volume of requests from you! We hope this extra time will be helpful for you in completing your project.

NEW Submission Deadline

Check out main Hackathon communication channels for the winners announcement!

Winners Announcement 

InfiniteMemory or AutoPaperwrk

BrianP8701

Previous Flow: 
Message (User) -> Response (Model) -> ....

RAG Flow:
Message (User) -> Retrieve Additional Context (Vector Database) -> Response (Model)

A model hallucinates. A model isn't capable of reading a ton of documentation in one context run. For any specific, project, person, institution or group, they might have a series of documentation, books, reports and data of interest to them specifically, that they want their LLMs to be aware of. Models will never be able to have infinite context. A person might want a reference to a primary source in an engineering or professional environment, an LLM might need more context to better answer a question.

There are a few forms of memory available to a model. One is the information retained during pre-training. There's then information from the immediate context in a message. Furthermore, we can have external memory, akin to a person writing things down or taking notes. This can be a vector database, most commonly used today, to find the most similar piece of text to the message. We implemented this with LLAMA-Index's library on the cloud with a very simple api.

Secondly, is using a knowledge tree. A tree with clone nodes can represent anything a graph can. A knowledge tree allows for log traversals, and is truly the most intuitive and natural way to express information, a tree of knowledge. It utilizes an agents COT during traversal and construction and accounts for the models short term memory loss while still enabling it to work with a lot of data (Infinite if implemented correctly). We ran into the issue of maintaining the tree as it grows, but implemented some stuff. This is a popular idea, seen done most similarly by Arcus.

Agents need memory - context to better answer questions.

"InfiniteMemory or AutoPaperwrk team on Open Interpreter Hackathon Hackathon"

Team Idea

Submission