After OpenAI’s DevDay, we launched a project inspired by GPTs and the Assistants API. It’s called OpenGPTs, and the project implements similar functionalities but in an open source manner — giving you ultimate flexibility of what language model, vector store, tools, and retrieval algorithm are used.

Helpful resources :

• Check out the GitHub repo

• Try out the cloud hosted version

• Read about how we use Redis in OpenGPTs

Taking another look at LangChain Open GPTs

We launched OpenGPTs a couple months back in response to OpenAI’s GPTs. Open GPTs is an open source application builder that lets you choose your own models to run and gives you more flexibility when it comes to cognitive architecture. We’ve been working closely with a few enterprise partners to improve OpenGPTs for their needs, and we want to share a bit more about how the platform works under the hood. Check out our blog post where we dive into:

• MessageGraph: A particular type of graph that OpenGPTs runs on.

• Cognitive architectures: What the 3 different types of cognitive architectures OpenGPTs supports, and how they differ.

• Persistence: How persistence is baked in OpenGPTs via LangGraph checkpoints.

• Configuration: How we use LangChain primitives to configure all these different bots.

• and more...

And check out the demo in which Harrison does a deep-dive on the platform.