Ts Agents

Building JavaScript agents in LlamaIndex.TS

In this repo we'll walk you through the process of building an Agent in JavaScript using the LlamaIndex.TS library, starting from nothing and add complexity in stages.

What is an Agent?

In LlamaIndex, an agent is a semi-autonomous piece of software powered by an LLM that is given a task and executes a series of steps towards solving that task. It is given a set of tools, which can be anything from arbitrary functions up to full LlamaIndex query engines, and it selects the best available tool to complete each step. When each step is completed, the agent judges whether the task is now complete, in which case it returns a result to the user, or whether it needs to take another step, in which case it loops back to the start.


Install LlamaIndex.TS

You'll need to have a recent version of [Node.js](https://nodejs.org/en) installed. Then you can install LlamaIndex.TS by running

npm install llamaindex

Choose your model

By default we'll be using OpenAI with GPT-4, as it's a powerful model and easy to get started with. If you'd prefer to run a local model, [see below](#using-a-local-model-via-ollama).

A basic agent

Get an OpenAI API key

If you don't already have one, you can sign up for an [OpenAI API key](https://platform.openai.com/api-keys). You should then put the key in a `.env` file in the root of the project; the file should look like

OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXXXXXX

We'll use `dotenv` to pull the API key out of that .env file, so also `npm install dotenv`.

Create `agent.ts`

We want to use `await` so we're going to wrap all of our code in a `main` function, like this:

// Your imports go here

async function main() {
  // the rest of your code goes here
}

main().catch(console.error);

For the rest of this guide we'll assume your code is wrapped like this s