Nodes
Agent Swarm Node
Orchestrate multiple AI agents to collaborate and solve complex tasks
Overview
The Agent Swarm Node enables multiple AI agents to work together collaboratively to solve complex tasks. This node allows you to:- Configure multiple specialized agents with different capabilities
- Define an initial agent to start the conversation
- Allow agents to hand off tasks to other agents based on their expertise
- Create complex workflows where agents collaborate to achieve a goal
Configuration Parameters
The Agent Swarm Node requires configuration of multiple agents that will work together in the swarm. Each agent can be configured independently with its own settings and capabilities.Node Configuration
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Query:
Specify the task or question for the swarm to handle. For example,
Given this email: , identify if it is asking for availability. Look at my calendar to check for my availability and provide timeslots to respond to the email.
Given a contact, conduct web search on the person, and then draft a personalized outreach email to …
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Agents
Configure multiple agents that will participate in the swarm. For each agent, you can:
- Set a custom display name
- Designate it as the initial agent
- Configure agent-specific settings and tools
- Define the agent’s role and capabilities
Choose the initial agent carefully as it will be responsible for starting the conversation and delegating tasks to other agents.
Advanced Settings
Advanced Settings
- Max Steps: Set the maximum number of steps the swarm can take (1-200). This prevents infinite loops and ensures the swarm reaches a conclusion.
Expected Inputs and Outputs
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Inputs:
- The node accepts input data that can be referenced in the query using format strings.
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Outputs:
- output: The final result produced by the swarm
- conversation: A detailed log of the conversation between agents, showing how they collaborated to reach the solution
Use Case Examples
- Complex Problem Solving: Configure multiple agents with different expertise to break down and solve complex problems. Each agent can handle specific aspects of the problem based on their specialized knowledge.
- Multi-perspective Analysis: Use different agents to analyze the same problem from various angles, providing a comprehensive understanding of the situation.
- Collaborative Content Creation: Set up agents with different writing styles and expertise to collaboratively create content, with each agent contributing their specialized knowledge.
Error Handling and Troubleshooting
- Agent Configuration: Make sure each agent in the swarm is properly configured with appropriate settings and tools for their intended role.
- Max Steps Exceeded: If the swarm is not reaching a conclusion, you may need to increase the max_steps parameter or optimize the agent configurations.