In case you're using JS/TS, I've been working on an abstraction layer for integrating AI models applications, unifying the API for common operations such as text streaming, object generation, and tool usage: https://github.com/lgrammel/modelfusion
So, you essentially took my project ( https://github.com/rubberduck-ai/rubberduck-vscode ), and instead of contributing to it or forking it, you recommitted all the code under your own name, with a few small tweaks.
To be fair, I saw that you give credit, but it's kind of disappointing still given that prob 98% of the project is the work of the Rubberduck contributors. I know Rubberduck is not that active any more, but it's still disappointing.
I think it is more nuanced. This article for example contains examples that suggest otherwise if you want to increase quality (which is a major concern when putting things in production):
Yes, good point, JS/TS is definitely behind Python. That might explain some of it.
I expect most models to become multi modal in the future and am building towards. A lot of the core logic of agents will nevertheless be text based imo, so that’s a central piece, but I already added text to image and speech to text, and plan to add text to speech next.
ModelFusion is a library for building AI apps, chatbots, and agents. It provides abstractions for AI models, vector indices, and tools.
- Type inference and validation: ModelFusion uses TypeScript and Zod to infer types wherever possible and to validate model responses.
- Flexibility and control: AI application development can be complex and unique to each project. With ModelFusion, you have complete control over the prompts and model settings, and you can access the raw responses from the models quickly to build what you need.
- No chains and predefined prompts: Use the concepts provided by JavaScript (variables, functions, etc.) and explicit prompts to build applications you can easily understand and control. Not black magic.
- More than LLMs: ModelFusion supports other models, e.g., text-to-image and voice-to-text, to help you build rich AI applications that go beyond just text.
- Integrated support features: Essential features like logging, retries, throttling, tracing, and error handling are built-in, helping you focus more on building your application.
Author here - thanks for the mention! Re publicizing: I can never get any attention for my projects, no matter where I post them. Sites like this one (where I tried posting the project multiple times) feel very gamed to me at this point.
I'm developing Rubberduck, an opensource AI chatbot and tool for Visual Studio Code. It can edit code, explain it, generate tests, diagnose errors, or talk about software development.
I plan to release a v1.0 in the coming days and I'm looking for feedback on what to improve.