Jido - A SDK for Building Autonomous Agent Systems

This is great. Have been thinking I need something similar. Will try for sure.

The above link to the Getting Started Guide returns a 404…

Thanks, fixed

This is super cool! I’ve been seeing various frameworks like this but so far they’ve all been in python.

Can you explain generally when autonomous agents are preferred to running single threaded assistants with function calling?

Great question - This whole space is evolving quickly and has been a fantastic mental challenge to shed my old habits of how these apps get built - so this is my current perspective.

The “use an LLM assistant to execute a tool” trend of late benefits one party - LLM API providers. I’ve read over a LOT of repo’s, and have played with a lot of toys.

That’s why this foundational repo has ZERO LLM or AI code in it. At this foundational layer, LLM tool calling as a first class citizen didn’t feel right.

Don’t get me wrong, I wrote this to integrate with LLM’s - but the Elixir way is to build with pure data structures and minimal dependencies on OTP. That’s the purpose of this package.

As a sneak peek - here’s a Jido Action which implements a call to Anthropic Claude using instructor_ex to fetch a “Chat Completion” - aka agent chatting: https://github.com/agentjido/jido_ai/blob/main/lib/jido_ai/anthropic.ex#L6

Agents as GenServers is implemented and tested. I’m not entirely happy with the API yet so I didn’t include it in this official release. They each spin up a DynamicSupervisor and can manage delegating tasks to other agents, starting and stopping Signals and doing all sorts of other cool things.

I see a future where we each have thousands of Agents working for us constantly - like a swarm of ants. No other framework or platform comes close to making this happen - so I started from first principles with Elixir.

Enjoy!

EDIT: There will be many examples coming soon to demonstrate the scope of what Agents with Jido are capable of.

Oh, name of the library is extremely close (sounds exactly the same if pronounced in English way) to antisemitic slur.

But Chinese pronunciation “Siodong” is much less similar, perhaps it would make sense to note this way of pronunciation as the official one

Here is a blog post from Hugging Face that has a “when to use agents/when to avoid them” section: Introducing smolagents: simple agents that write actions in code.

If that deterministic workflow fits all queries, by all means just code everything! This will give you a 100% reliable system with no risk of error introduced by letting unpredictable LLMs meddle in your workflow. For the sake of simplicity and robustness, it’s advised to regularize towards not using any agentic behaviour.
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Until recently, computer programs were restricted to pre-determined workflows, trying to handle complexity by piling up if/else switches. They focused on extremely narrow tasks, like “compute the sum of these numbers” or “find the shortest path in this graph”. But actually, most real-life tasks, like our trip example above, do not fit in pre-determined workflows. Agentic systems open up the vast world of real-world tasks to programs!

Great post - added some perspective to the Jido README:

https://github.com/agentjido/jido?tab=readme-ov-file#are-you-sure-you-need-an-agent

Here is another related post from Anthropic: Building Effective AI Agents \ Anthropic

This thread is confusing to me. Reading the OP it seems this is a library that’s kind of sort like Oban – you can build pipelines of tasks, sort of like ETL systems as well.

But now the discussion got steered toward LLM agents and I apparently I misunderstood the whole thing. Anybody wants to put things in context?