I've been experimenting with setting up local multi-agent systems and honestly, it feels like a complete mess right now. I'm struggling with managing agent communications, memory, task routing, and fallback logic — it all seems really jumbled together. I've tried different approaches like using queues, Redis, and even creating my own message handlers, but nothing scales well. Langchain works for simpler tasks, but once you try to increase complexity, it doesn't hold up. On the other hand, tools like Crewa and Autogen feel too rigid or overly dependent on cloud services. I'm wondering if anyone has a local setup they genuinely like, or are we all just muddling through this chaos and pretending it's a structured pipeline? I'm especially curious about how you're managing agent-to-agent communication and memory sharing without everything turning into a tangled mess.
2 Answers
When you mention 'local,' could you clarify what you mean? What specific challenges are you facing with local multi-agent systems?
You're definitely not alone in this! Right now, it feels like we're stuck at the beginning of this tech's evolution cycle. The hype is way ahead of the technology, and yeah, it's messy. But if you keep at it, you'll be better prepared for when it all matures. Focus on integrating these systems with real-world software; that's where the real potential lies.
By 'local,' I mean everything's running on my own machine or server — basically no managed cloud services. I want full control and to create tools that can work in secure or offline settings. But the big hurdle is the lack of built-in orchestration; it’s all about manually connecting agent communications, handling retries, and coordinating tasks. Does that make sense?