What is LlamaIndex?

LlamaIndex is a complete toolkit for working with LLMs. For this course we’ll focus on three main parts that help build agents in LlamaIndex: Components, Agents and Tools and Workflows.

Let’s look at these key parts of LlamaIndex and how they help with agents:

Components are the basic building blocks you use in LlamaIndex. These include things like prompts, models and databases. Components often help connect LlamaIndex with other tools and libraries.

Agents and Tools are LLM-powered knowledge workers that can intelligently perform various tasks over your data, including both reading and writing operations. They do so with tools and reasoning loops.

Workflows are step-by-step processes that processing logic together. Workflows or agentic workflows are a way to structure agentic behaviour without the explicit use of agents.

Now, let’s see how how Alfred would operate in with these parts of LlamaIndex.

TODO: Add image of Alfred

What Makes LlamaIndex Special?

While LlamaIndex does some things similar to other frameworks like smolagents, it has some key benefits:

  1. Built-in Document Reading with LlamaParse LlamaParse was made specifically for LlamaIndex, so the integration is seamless, although it is a paid feature.

  2. Many Ready-to-Use Components LlamaIndex has been around for a while, so it works with lots of other frameworks. This means it has many tested and reliable components.

  3. Clear Workflow System. Workflows help break down how agents should make decisions step by step. This is like having a map for a conversation or task.

We’ll look more closely at each of these parts and how they work together in the next sections. Let’s start with Components.

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