gogwilt

Thanks! Super impressed by your team's application of AI!

Thanks!

Yes, I think Rivet, langflow, and flowise all came to the idea of visual programming for LLMs in parallel. I like to think it's a good sign that visual programming is a powerful paradigm here :)

I do think Rivet hits a pretty different use-case. Beyond being in the TypeScript ecosystem, Rivet's remote debugging and embedability are pretty unique, and super critical!

Thanks @ryscheng!

Unfortunately nothing beyond the example apps. We wanted to get an example with a full agentic loop together, but settled for the simpler chatbot.

We'd love suggestions here, actually. Can you think of a use-case that might be a good example to open-source? Preferably something that interacts with multiple APIs towards a specific purpose?

Yes! Thanks a ton for your contributions!

Likely early to growth-stage start-ups!

That's at least what a lot of our early design partners and collaborators have been. Rivet slots in neatly to most modern TypeScript applications, and is pretty easy to adopt progressively.

(Also depends on your definition... I'd consider Ironclad a "growth-stage start-up," but I imagine others would say otherwise!)

Thanks!

I don't think it's a good idea to give an agent tools "just in case."

We've opted for giving our agents access to a few distinct, but powerful tools, and then trusting them to combine these tools in a strategic way. It's going well so far, but we are pretty careful to clearly explain the tools.

However, I've spoken to other teams that have opted for giving their agents tons of tools, and it sounds like that can work pretty well. But everything seems to take work and experimentation.

Thank you! 100% with you on the nightmare using code.

We'd love your feedback when you get a chance to dig in! Building AI features is SUPER fun with Rivet!

Thanks!

Actually, when running locally, you can open it in a web app. There's one catch, though: saving project files is pretty janky (it downloads the project file). I think basically everything else works pretty well, though!

Thanks Mike! Your advice and support has been super critical and motivating!

I think it's people building tool-using agent applications.

We've been collaborating with several amazing teams over the past few months, who have been pushing Rivet in various ways. We used it for a chat interface at Ironclad, but we've seen companies like Bento and Willow integrate it with different UX paradigms.

The commonality seems to be that we are all integrating LLMs into an application, and want the LLM to somehow interact with that application (set up search filters, build a guide based on documentation).

Nice! Love this!

Thanks!

And yes, we'd love to support OSS LLMs. And we welcome contributions ;)

Rivet also has a plug-in system, and our friends at AssemblyAI were actually able to develop a plug-in for using their audio transcription and understanding AI models in Rivet!

Thanks! 100%. I think the TS support has also helped us innovate on the UX side of things much more quickly.