Building a Deep Research AI Multi-Agent with LlamaIndex

Duplicate Laurie's notebook in Google Colab to code along with us! https://bit.ly/4kaugoy To code along live with this session you will need the following: Tavily API Key - https://app.tavily.com/home OpenAI API Key - https://platform.openai.com/api-keys Register for this session to get the recording and resources sent to you! https://www.datacamp.com/webinars/building-a-deep-research-ai-multi-agent-with-llamaindex Resources (including link to code along notebook): https://bit.ly/3EWe6A3 How to Connect to OpenAI's API - https://www.datacamp.com/tutorial/openai-o1-api AI agents are becoming essential tools for automating complex tasks like deep research, especially when paired with frameworks like LlamaIndex. By structuring and evaluating these agents effectively, data scientists and AI engineers can build powerful tools that gather, organize, and summarize information from diverse sources with speed and accuracy. In this hands-on code-along session, Laurie Voss, VP of Developer Relations at LlamaIndex, will guide you through building a deep research AI multi-agent using LlamaIndex. You’ll learn how to structure AI agents, build one designed specifically for researching news articles, and evaluate its performance to ensure high-quality results. Whether you’re new to agent frameworks or looking to deepen your expertise, this session will give you practical skills for building intelligent, research-focused AI systems.