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Building a Deep Research AI Multi-Agent with LlamaIndex

Laurie Voss, VP of Developer Relations at LlamaIndex, guides you through building a deep research AI multi-agent using LlamaIndex.
Laurie Voss
Laurie Voss

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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.

Key Takeaways:

  • Learn how to build an AI agent using LlamaIndex.
  • Discover how to structure and evaluate AI agents for deep research.
  • Build your first AI multi-agent for researching news articles.

Session Resources (Including Set-Up Instructions and Notebook)

Subiecte

Artificial IntelligenceMachine Learning and AIPython

Conexe

Tutorial

Groq LPU Inference Engine Tutorial

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