Thanks!

https://github.com/pixeltable/pixelagent/tree/main/examples/... for multiple tools/agents. A tool is just a UDF. You can have as many as you want.

The goal of this reference agent SDK is to showcase the flexibility of Pixeltable (the underlying unified storage and orchestration system) that is Open Source and Apache 2.0.

This is where storage is defined: https://github.com/pixeltable/pixelagent/blob/main/pixelagen.... These are very simple examples.

Here's how an Agentic Reddit bot would work for instance: https://github.com/pixeltable/pixeltable/tree/main/docs/samp...

It really depends on the use case. For Pixelagent, I don't really look at competition as mentioned by the fact that this is a reference implementation.

People should build their own; it's easy. What's difficult is the underlying data infrastructure (storage and orchestration).

It all started with https://github.com/pixeltable/pixeltable which is the core project we are actively working on and the problem space of working with video and frames for Computer Vision teams who struggle with the explosion of data and maintaining lineage and versioning for frames of video.

The same problems arise with LLMs for Documents and Chunks, Audio and Samples, etc.

If you are into that:

- Object Detection on Video Frames: https://github.com/pixeltable/pixeltable/blob/main/docs/note...

- Text and images similarity search: https://github.com/pixeltable/pixeltable/tree/main/docs/samp...

LLM is just a function call. We are agnostic to whatever framework, library, and data format are used; we are focused on solving the data plumbing issues (mulitmodal storage and orchestration) with a simple python sdk: https://github.com/pixeltable/pixeltable.

I like PocketFlow. You beat me on the # of lines of code! But does it provide parallelization, caching, orchestration, versioning, observability, lineage, multi-modal support?

As you just showed, building an agent SDK is easy, so what's interesting to me is tackling:

- Infrastructure Sprawl: Juggling separate systems for vector search, state tracking, multimodal data handling, and monitoring leads to fragmented workflows and high operational costs. - State Management Nightmares: Reliably tracking agent memory, tool calls, and intermediate states across potentially long-running, asynchronous tasks is incredibly difficult. - Multimodal Integration Pain: Integrating and processing images, audio, video, and documents alongside text requires specialized, often disparate, tooling. - Observability Gaps: Understanding why an agent made a decision or failed requires visibility into its state and data lineage, which is often lacking.

And doing all of that while finding the right abstraction layer to leave all the application and business logic to the dev/users so they don't feel limited. It's difficult!

Besides, I don't know where you see a commercial offering? Everything is Apache 2.0/Open Source from A to Z.

Congrats! Take whatever you want :)

Yes: Memory, observability, versioning, and lineage being built-in is a derivative of unifying orchestration and storage: https://docs.pixeltable.com/docs/datastore/computed-columns.