Integrate Runpod with n8n

Learn how to deploy a vLLM worker on Runpod and connect it to n8n for AI-powered workflow automation.

Learn how to integrate Runpod Serverless with n8n, a workflow automation tool. By the end of this tutorial, you’ll have a vLLM endpoint running on Runpod that you can use within your n8n workflows.

What you’ll learn

In this tutorial, you’ll learn how to:

• Deploy a vLLM worker on Runpod Serverless.
• Configure your vLLM endpoint for OpenAI compatibility.
• Connect n8n to your Runpod endpoint.
• Test your integration with a simple workflow.

Requirements

• You’ve created a Runpod account.
• You’ve created a Runpod API key.
• You have n8n installed and running.
• (Optional) For gated models, you’ve created a Hugging Face access token.

Step 1: Deploy a vLLM worker on Runpod

First, you’ll deploy a vLLM worker to serve your language model.

1. Create a new vLLM endpoint

   Open the Runpod console and navigate to the Serverless page.

   Click New Endpoint and select vLLM under Ready-to-Deploy Repos.

2. Configure your endpoint

   For more details on vLLM deployment options, see Deploy a vLLM worker.

   In the deployment modal:

   • Enter the model name or Hugging Face model URL (e.g., openchat/openchat-3.5-0106).
   • Expand the Advanced section:
     • Set Max Model Length to 8192 (or an appropriate context length for your model).
     • You may need to enable tool calling and set an appropriate reasoning parser depending on your model.
   • Click Next.
   • Click Create Endpoint.

   Your endpoint will now begin initializing. This may take several minutes while Runpod provisions resources and downloads your model. Wait until the status shows as Running.

3. Copy your endpoint ID

   Once deployed, navigate to your endpoint in the Runpod console and copy the Endpoint ID. You’ll need this to connect your endpoint to n8n.

Step 2: Connect n8n to your Runpod endpoint

Now you’ll configure n8n to use your Runpod endpoint as an OpenAI-compatible API.

1. Add an OpenAI Chat Model node

   In your n8n workflow, add a new OpenAI Chat Model node to your canvas. Double-click the node to configure it.

2. Create a new credential

   Click the dropdown under Credential to connect with and select Create new credential.

3. Add your Runpod API key

   Under API Key, add your Runpod API Key. You can create an API key in the Runpod console.

4. Configure the base URL

   Under Base URL, replace the default OpenAI URL with your Runpod endpoint URL:

   https://api.runpod.ai/v2/ENDPOINT_ID/openai/v1
   

   Replace ENDPOINT_ID with your endpoint ID from Step 1.

5. Save the credential

   Click Save. n8n will automatically test your endpoint connection. If successful, you can start using the node in your workflow.

Step 3: Test your integration

Create a simple workflow to test your integration.

1. Create a test workflow

   Add a Manual Trigger node and connect it to your OpenAI Chat Model node.

2. Configure the chat model

   In the OpenAI Chat Model node, add a test message like “Hello, what can you help me with?”

3. Execute the workflow

   Click Execute Workflow in n8n. You should see a response from your model running on Runpod.

4. Monitor requests

   Monitor requests from your n8n workflow in the endpoint details page of the Runpod console.

The n8n chat feature may have trouble parsing output from vLLM depending on your model. If you experience issues, try adjusting your model’s output format or testing with a different model.

Next steps

Now that you’ve integrated Runpod with n8n, you can:

• Build complex AI-powered workflows using your Runpod endpoints.
• Explore other integration options with Runpod.
• Learn about OpenAI compatibility features in vLLM.