Excited to give this a try! A visual environment seems like a natural fit for chained LLM calls.
Have you considered supporting OSS LLMs? Inference servers like LocalAI or vLLM expose APIs for various OSS models with OpenAI-compatible endpoints, so might not be much more work to integrate.
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!
Comments
Excited to give this a try! A visual environment seems like a natural fit for chained LLM calls.
Have you considered supporting OSS LLMs? Inference servers like LocalAI or vLLM expose APIs for various OSS models with OpenAI-compatible endpoints, so might not be much more work to integrate.
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!
We recently opensourced a similar platform for building workflows by chaining LLMs visually along with LocalAI support.
Check it out at https://github.com/trypromptly/LLMStack. Like you said, it was fairly easy to integrate LocalAI and is a great project.
Nice! Love this!