This tutorial demonstrates how to create a multi-agent system using the Atomic Agents library. It includes a search agent and a calculator agent that can handle different user queries. Before starting, it is recommended to understand Pydantic and Instructor libraries. To begin, necessary packages like atomic-agents, openai, and instructor need to be installed. Then, libraries for creating the multi-agent system are imported. Components like the client, tools, and agents are initialized, followed by configuring and creating the search and calculator agents. A union response schema is defined to handle responses from both agents. An orchestration agent is created to manage interactions with users, and a main chat loop is set up to determine which agent to use based on user input. The tutorial concludes by highlighting the customization and extension possibilities of the agents and tools within the system. It emphasizes the simplicity of the system prompt and the importance of passing Pydantic schemas to the LLM for better performance. For a more detailed explanation, the GitHub repository or an in-depth guide is recommended.
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Setting up a basic multi-agent system using atomic agents #MAS
