Llama Agents + Workflows (429 Stars) 2026: Event-Driven, Async-First Multi-Agent Orchestration

Llama Agents + Workflows (429 stars) is LlamaIndex's event-driven, async-first framework for building step-based multi-agent systems. Here is a working example.

💡 What You Will Learn

Llama Agents + Workflows (429 stars) is LlamaIndex's event-driven, async-first framework for building step-based multi-agent systems. Here is a working example.

## The short answer **run-llama/llama-agents** (429 stars, Python) provides Llama Agents + Workflows - an event-driven, async-first, step-based way to build multi-agent systems. Instead of hard-coding agent call chains, you define steps that react to events, which makes complex orchestrations easier to build and debug. ## Why event-driven agents - **Decoupled**: agents communicate via events, not direct calls - **Async-first**: steps run concurrently where possible, cutting total latency - **Step-based**: each step is a discrete unit you can test and reuse - **Observable**: event streams make the system flow visible ## Minimal workflow example ```python from llama_agents import AgentWorkflow, HumanAgent, ToolAgent # Define two agents researcher = ToolAgent(name="researcher", tools=[search_tool]) writer = AgentWorkflow(name="writer") # Orchestrate with a workflow workflow = AgentWorkflow( agents=[researcher, writer], root_agent="writer", ) result = await workflow.run(user_msg="Research topic X and write a summary") print(result) ``` Install: `pip install llama-agents llama-index` ## When to use it - You already use LlamaIndex and want agents with minimal new concepts. - Your orchestration has parallelizable branches (research, summarize, review). - You want explicit control over each step instead of magic chains. ## FAQ **Is it stable?** It is early-stage (429 stars) and evolving quickly; APIs may change between releases. **Does it need a server?** No - workflows run in-process; there are optional server components for distributed agents. **How does it compare to LangGraph?** Both are graph-style orchestrators; Llama Agents stays closer to the LlamaIndex ecosystem, while LangGraph (38,984 stars) is framework-agnostic.