Llama Index Workflows | Building Async AI Agents

Llama Index Workflows is an event-driven framework for building AI agents. It aims to provide AI Engineers with a structured conceptual frame around which we can build AI software, similar in some respects to LangChain's LangGraph. In this video, we'll compare the two frameworks (Llama Index Workflows and Langchain's LangGraph), learn how to use Workflows, and build an async research agent with the library. 📌 Code: https://github.com/pinecone-io/examples/blob/master/learn/generation/llama-index/llama-index-research-agent.ipynb 🌟 Build Better Agents + RAG: https://platform.aurelio.ai (use "JBMARCH2025" coupon code for $20 free credits) 👾 Discord: https://discord.gg/c5QtDB9RAP Twitter: https://twitter.com/jamescalam LinkedIn: https://www.linkedin.com/in/jamescalam/ #artificialintelligence #llamaindex #coding #programming 00:00 Llama Index Workflows 00:53 Llama Index vs. LangGraph 05:27 Python Prerequisites 06:40 Building Knowledge Base 08:20 Defining Agent Tools 11:02 Defining the LLM 12:31 Llama Index Workflow Events 14:00 Llama Index Agent Workflow 24:25 Debugging our Workflow 26:47 Using and Tweaking our Agent 30:05 Testing Llama Index Async