> ## Documentation Index
> Fetch the complete documentation index at: https://docs.inferable.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quick Start

> Get started with Inferable in minutes

This guide will help you quickly set up and run your first Inferable agent workflow.

We will build a simple workflow that greets the user, as an illustration of the basic concepts.

<Steps>
  <Step title="Get you API key">
    You can get a free API key by signing up at [app.inferable.ai](https://app.inferable.ai). Copy your API key to your clipboard. You'll need to paste it into the next step.

    ![API key](https://mintlify.s3.us-west-1.amazonaws.com/inferable/images/api-key.gif)
  </Step>

  <Step title="Clone the starter project">
    Clone the starter project and install dependencies.

    ```bash
    git clone https://github.com/inferablehq/inferable-node-starter
    cd inferable-node-starter
    npm install
    ```
  </Step>

  <Step title="Paste your API key">
    Paste your API key into the `src/workflows/simple.ts` file's client initialization.

    ```typescript
    const inferable = new Inferable({
      apiSecret: "sk_inf...",
    });
    ```
  </Step>

  <Step title="Create a workflow">
    Let's extend the simple.ts workflow with an example that gets some structured data from a website.

    Workflows are a way to define a sequence of actions to be executed. Workflows are durable, can be triggered from anywhere via the API.

    They run on the machine that they are registered on - i.e., your own compute.

    ```typescript
    // src/workflows/simple.ts

    // ... starter code ...

    workflow.version(1).define(async (ctx, input) => {
      // Add this code to the workflow

      // 1. Fetch the URL
      const text = await fetch(input.url)
        .then(res => res.text());

      // 2. Parse the text with a structured output
      const { menuItems, hours } = await ctx.llm.structured({
        input: text,
        schema: z.object({
          menuItems: z.array(z.object({
            name: z.string(),
            price: z.number(),
          })),
          hours: z.object({
            saturday: z.string(),
            sunday: z.string(),
          })
        }),
      });

      // 3. Return the structured data
      return { menuItems, hours };
    });

    // This will register the workflow with the Inferable control-plane at api.inferable.ai
    workflow.listen().then(() => {
      console.log("Workflow listening");
    });
    ```
  </Step>

  <Step title="Start the workflow">
    Start the workflow by running the following command.

    ```bash
    npx tsx src/workflows/simple.ts
    ```

    This will register the workflow with the Inferable control-plane at api.inferable.ai.
  </Step>

  <Step title="Trigger the workflow">
    Workflows can be triggered from anywhere.

    For this example, we'll trigger the workflow with a curl command.

    ```bash
    # Get your cluster details
    CLUSTER_ID="PASTE_YOUR_CLUSTER_ID_HERE"
    API_SECRET="PASTE_YOUR_API_SECRET_HERE"
    RANDOM_ID=$(openssl rand -hex 4)

    # Run the workflow
    curl -XPOST https://api.inferable.ai/clusters/$CLUSTER_ID/workflows/simple/executions \
      -d '{"executionId": "'$RANDOM_ID'", "url": "https://a.inferable.ai/menu.txt"}' \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $API_SECRET"

    # See the output at https://app.inferable.ai/clusters/$CLUSTER_ID/workflows/simple/executions/$RANDOM_ID
    echo "\n\nSee the output at https://app.inferable.ai/clusters/$CLUSTER_ID/workflows/simple/executions/$RANDOM_ID"
    ```
  </Step>

  <Step title="View the execution 🎉">
    You can view the workflow in the Inferable app at the [cluster details page](https://app.inferable.ai/clusters).

    ![Demo Workflow](https://mintlify.s3.us-west-1.amazonaws.com/inferable/images/demo-workflow.png)
  </Step>
</Steps>

That's it! You've created your first Inferable workflow.