30 lines
2.6 KiB
Plaintext
30 lines
2.6 KiB
Plaintext
# Introduction to LlamaIndex
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Welcome to this module, where you’ll learn how to build LLM-powered agents using the [LlamaIndex](https://www.llamaindex.ai/) toolkit.
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LlamaIndex is **a complete toolkit for creating LLM-powered agents over your data using indexes and workflows**. For this course we'll focus on three main parts that help build agents in LlamaIndex: **Components**, **Agents and Tools** and **Workflows**.
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Let's look at these key parts of LlamaIndex and how they help with agents:
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- **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.
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- **Tools**: Tools are components that provide specific capabilities like searching, calculating, or accessing external services. They are the building blocks that enable agents to perform tasks.
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- **Agents**: Agents are autonomous components that can use tools and make decisions. They coordinate tool usage to accomplish complex goals.
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- **Workflows** are step-by-step processes that process logic together. Workflows or agentic workflows are a way to structure agentic behaviour without the explicit use of agents.
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## What Makes LlamaIndex Special?
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While LlamaIndex does some things similar to other frameworks like smolagents, it has some key benefits:
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- **Clear Workflow System**. Workflows help break down how agents should make decisions step by step using an event-driven and async-first syntax. This helps you clearly compose and organize your logic.
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- **Advanced Document Parsing with LlamaParse** LlamaParse was made specifically for LlamaIndex, so the integration is seamless, although it is a paid feature.
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- **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, like LLMs, retrievers, indexes, and more.
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- **LlamaHub** is a registry of hundreds of these components, agents and tools that you can use within LlamaIndex.
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All of these concepts are required in different scenarios to create useful agents.
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In the following sections, we will go over each of these concepts in detail.
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After mastering the concepts, we will use our learnings to **create applied use cases with Alfred the agent**!
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Getting our hands on LlamaIndex is exciting, right? So, what are we waiting for? Let's get started with **finding and installing the integrations we need using LlamaHub! 🚀** |