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Show HN: Use functional tokens for AI agents to simplify app workflows

nexa4ai.com

80 pointsalanzhuly10 comments

Hi HN! I want to share our latest project at NEXA AI. We developed AI agent foundation models designed to transform how developers create AI agent powered apps.

One major challenge we've observed with current human-computer interactions is that many simple, one-step tasks become unnecessarily complex, multi-step workflows due to limitations of current GUIs. AI agents can solve this, but existing AI agent models are slow and costly.

To tackle these issues, we built lightweight AI agent models based on our Octopus V2, small language models for function calling (You can learn more about our functional token approach in our paper: https://huggingface.co/papers/2404.01744). These models support developers in building AI agents both on-device and in the cloud. Our function calling models are 4 times faster, 10 times cheaper, and more accurate than GPT-4o.

We’d love for you to try out our model APIs and see the difference for yourself. Your feedback and thoughts are incredibly valuable to us, and we’re here to answer any questions you might have.

Links:

Website: https://www.nexa4ai.com/octoverse

Playground: https://hub.nexa4ai.com

Documentation: https://docs.nexa4ai.com/

Join Discord to discuss: https://discord.com/invite/thRu2HaK4D

Paper: https://huggingface.co/papers/2404.01744

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I see that I can change the implementation of those functions in a particular model you have. Is it possible to change the defined functions(APIs) to fit my use cases?

Currently, to modify the defined functions in the model, you can provide us with a description of your desired functions, and we can customize (fine-tune) a model for you.

However, if your use case is similar to the current functions of our model, you might consider using nested functions to leverage our existing capabilities.

Feel free to reach out for further assistance or more specific customization needs.

The playground demo looks good, but how does the model perform under real-world conditions with high demand and diverse user inputs?

Our models can handle diverse user inputs well and have high accuracy in our benchmark results. Feel free to check it out here: https://huggingface.co/NexaAIDev/Octopus-v2/blob/main/androi...

It can also handle high demand thanks to its lightweight architecture. During our test, our API has 100x more rate limiting than GPT-4o API

What kind of dev-specific use case would this help with?

Our models offer developers faster, cheaper alternative to GPT-4o for implementing function-calling AI agent workflows. Developers can use our model APIs and implement each model's functions to integrate AI agent functionalities into their apps.

Nice services excellent

What is your differentiation with Multion Agent API?

Do the models work on mobile apps? Or just web apps?

Our models work on both mobile apps and web apps. You can use our model's API, which is flexible and can be integrated with any code.

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