How do you build a complex, multi-agent tree system to handle customer interactions? We've got a new open-source repo showing one way! Our multi-agent concierge system has a bunch of regular sub-agents, plus 3 "meta" agents: ➡️ A "concierge" agent which asks the user what they want to do, which can be a complex, multi-step process requiring multiple agents to perform tasks ➡️ An "orchestration" agent which figures out which sub-agent to handle the immediate next task ➡️ A "continuation" agent which looks at the broader context to decide if the user completed their original task or still needs more sub-agents to execute The overall system allows each sub-agent to focus on a specific skillset without having to come up with a giant, over-arching prompt for the entire system. We think it's a flexible, powerful pattern that you can use, so we've open-sourced it! Check out the full blog post: https://lnkd.in/dB34RCu6 Or head straight to the repo: https://lnkd.in/d88YN-Ne
Technofragrance
1mo
Open-sourcing your multi-agent tree system is a generous move!
What about incorporating context caching in the increasingly complex multi-agent systems? This could lead to rising costs.
Software Engineer - AI
1moI went through the whole blog and a very rudimentary question, creeps up in my mind. I want to clarify that I myself create agents and work with GenAI and this question is in no way derogatory to the amazing work accomplished here. Can this whole flow, not be achieved by cleverly executing "If", "Else" statements ? A deeper, more broad question would be, why do we use AI Agents in the first place ? I myself, am struggling to justify this to myself, maybe someone else's thought would help with this.