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