Browsing: MultiAgent

Managing the economics of multi-agent AI now dictates the financial viability of modern business automation workflows.Organisations progressing past standard chat interfaces into multi-agent applications face two…

In this tutorial, we build an advanced multi-agent communication system using a structured message bus architecture powered by LangGraph and Pydantic. We define a strict ACP-style…

def executor_agent(step: Dict[str, Any], context: Dict[str, Any]) -> StepResult: step_id = int(step.get(“id”, 0)) title = step.get(“title”, f”Step {step_id}”) tool = step.get(“tool”, “llm”) ctx_compact = { “goal”:…

For the past year, AI devs have relied on the ReAct (Reasoning + Acting) pattern—a simple loop where an LLM thinks, picks a tool, and executes.…

landed on arXiv just before Christmas 2025, very much an early present from the team at Google DeepMind, with the title “Towards a Science of Scaling Agent…

@tool def sql_investigate(query: str) -> dict: try: df = con.execute(query).df() head = df.head(30) return { “rows”: int(len(df)), “columns”: list(df.columns), “preview”: head.to_dict(orient=”records”) } except Exception as e:…

In this tutorial, we build an advanced multi-agent incident response system using AgentScope. We orchestrate multiple ReAct agents, each with a clearly defined role such as…

In this tutorial, we build an advanced yet practical multi-agent system using OpenAI Swarm that runs in Colab. We demonstrate how we can orchestrate specialized agents,…

In this tutorial, we build an advanced, end-to-end multi-agent research workflow using the CAMEL framework. We design a coordinated society of agents, Planner, Researcher, Writer, Critic,…

In this tutorial, we build an advanced, fully autonomous logistics simulation in which multiple smart delivery trucks operate within a dynamic city-wide road network. We design…