---
title: 'Development'
description: 'Learn how to preview changes locally'
---

<Info>
  **Prerequisite** You should have installed Node.js (version 18.10.0 or
  higher).
</Info>

Step 1. Install Mintlify on your OS:

<CodeGroup>

```bash npm
npm i -g mintlify
```

```bash yarn
yarn global add mintlify
```

</CodeGroup>

Step 2. Go to the docs are located (where you can find `mint.json`) and run the following command:

```bash
mintlify dev
```

The documentation website is now available at `http://localhost:3000`.

### Custom Ports

Mintlify uses port 3000 by default. You can use the `--port` flag to customize the port Mintlify runs on. For example, use this command to run in port 3333:

```bash
mintlify dev --port 3333
```

You will see an error like this if you try to run Mintlify in a port that's already taken:

```md
Error: listen EADDRINUSE: address already in use :::3000
```

## Mintlify Versions

Each CLI is linked to a specific version of Mintlify. Please update the CLI if your local website looks different than production.

<CodeGroup>

```bash npm
npm i -g mintlify@latest
```

```bash yarn
yarn global upgrade mintlify
```

</CodeGroup>

## Deployment

<Tip>
  Unlimited editors available under the [Startup
  Plan](https://mintlify.com/pricing)
</Tip>

You should see the following if the deploy successfully went through:

<Frame>
  <img src="/images/checks-passed.png" style={{ borderRadius: '0.5rem' }} />
</Frame>

## Troubleshooting

Here's how to solve some common problems when working with the CLI.

<AccordionGroup>
  <Accordion title="Mintlify is not loading">
    Update to Node v18. Run `mintlify install` and try again.
  </Accordion>
  <Accordion title="No such file or directory on Windows">
Go to the `C:/Users/Username/.mintlify/` directory and remove the `mint`
folder. Then Open the Git Bash in this location and run `git clone
https://github.com/mintlify/mint.git`.

Repeat step 3.

  </Accordion>
  <Accordion title="Getting an unknown error">
    Try navigating to the root of your device and delete the ~/.mintlify folder.
    Then run `mintlify dev` again.
  </Accordion>
</AccordionGroup>

Curious about what changed in a CLI version? [Check out the CLI changelog.](/changelog/command-line)

## Environment Variable Configuration

The simplest way to get started with Skyvern is to set environment variables in a `.env` file at the root of the project. This file is loaded by the application at runtime, and the values are used to configure the system.

### LLM Configuration

Skyvern works with multiple LLM providers. You need to set the following environment variables to configure your LLM provider:

```bash
# One of the below must be set to true
ENABLE_OPENAI=true
# ENABLE_ANTHROPIC=true
# ENABLE_AZURE=true
# ENABLE_BEDROCK=true
# ENABLE_GEMINI=true
# ENABLE_NOVITA=true
# ENABLE_OPENAI_COMPATIBLE=true

# Set your LLM provider API key
OPENAI_API_KEY=sk-xxxxxxxxxxxxx

# Set which model to use
LLM_KEY=OPENAI_GPT4O
```

If you're using OpenAI, you'll need to set `ENABLE_OPENAI=true` and provide your `OPENAI_API_KEY`. The `LLM_KEY` specifies which model to use, and should match one of the registered models in the `LLMConfigRegistry`.

#### Using Custom OpenAI-compatible Models

Skyvern can also use any OpenAI-compatible LLM API endpoint. This is useful for connecting to alternative providers that follow the OpenAI API format or to self-hosted models. This feature is implemented using [liteLLM's OpenAI-compatible provider support](https://docs.litellm.ai/docs/providers/openai_compatible).

To enable this:

```bash
# Enable OpenAI-compatible mode
ENABLE_OPENAI_COMPATIBLE=true

# Required configuration
OPENAI_COMPATIBLE_MODEL_NAME=gpt-3.5-turbo  # The model name supported by your endpoint (REQUIRED)
OPENAI_COMPATIBLE_API_KEY=your-api-key      # API key for your endpoint (REQUIRED)
OPENAI_COMPATIBLE_API_BASE=https://your-api-endpoint.com/v1  # Base URL for your endpoint (REQUIRED)

# Optional configuration
OPENAI_COMPATIBLE_API_VERSION=2023-05-15  # Optional API version
OPENAI_COMPATIBLE_MAX_TOKENS=4096         # Optional, defaults to LLM_CONFIG_MAX_TOKENS
OPENAI_COMPATIBLE_TEMPERATURE=0.0         # Optional, defaults to LLM_CONFIG_TEMPERATURE 
OPENAI_COMPATIBLE_SUPPORTS_VISION=false   # Optional, defaults to false
OPENAI_COMPATIBLE_ADD_ASSISTANT_PREFIX=false  # Optional, defaults to false
OPENAI_COMPATIBLE_MODEL_KEY=OPENAI_COMPATIBLE  # Optional custom key to register the model with
```

**Important Note**: When using this feature, the model name you provide will be prefixed with "openai/" in the liteLLM configuration. This is how liteLLM determines the routing for OpenAI-compatible providers.

This feature allows you to use models from providers like:
- Together.ai
- Anyscale
- Mistral
- Self-hosted models (e.g., using LM Studio or a local vLLM server)
- Any API endpoint that follows the OpenAI API format

Once configured, you can set `LLM_KEY=OPENAI_COMPATIBLE` to use this model as your primary LLM.

For more detailed information about OpenAI-compatible providers supported by liteLLM, see their [documentation](https://docs.litellm.ai/docs/providers/openai_compatible).

### Running the Server