Deployment of Flows

Overview

Deploy your flows to make them accessible via API endpoints. Once deployed, you can integrate your flows into your own applications, services, or trigger them from external systems.

Deployment Steps

1. Navigate to Your Flow

Navigate to Flows and select the flow you want to deploy. Open the flow editor and switch to the rocket (deployment) section.

If you are unsure about the icon, hover over it to see the description.

2. Create Deployment

Here you will see an overview of all deployments that you currently have. For us this page is empty.

Click Create Deployment to open the deployment dialog and confirm. If you want to change the default settings then expand the different sections of your deployment.

3. Save Your API Key

The first time an API key will be generated automatically. If you need a neew one then expand Deployment Configuration and select generate API Key. We recommend to use different API Keys for each deployment. Make sure to save the APi Key immediately - you won't be able to see it again.

The API key starts with sk (secret key). Do not share it with anyone.

To see an overview of your api keys navigate to the settings section.

Here you can deactivate, delete or create API Keys for your profile.

4. Get Example Code

After deployment, click on the created deployment to view example code.

You can use this code to integrate the flow API into your own application or service.

Testing with Postman

Before integrating into your application, it's recommended to test the API using Postman.

1. Create a Collection

Create a new collection or use an existing one. For example, name it "Test Flow API", then add a new HTTP request by clicking on New.

2. Paste the cURL Command

Simply paste the complete cURL command in the URL section of Postman (highlighted in blue below).

Postman will automatically fill in all the request details from the cURL command.

3. Add Your API Key

Click on the Headers tab, where you'll find x-API-Key. Paste your full API key that you saved earlier, replacing the masked version (the one with stars).

4. Configure Request Body

If your flow accepts input data, you can modify the data under the Body tab. The default structure is:

{
  "input_data": {
    "param1": "value1"
  }
}

Replace the parameters with your actual data. If your flow doesn't require input data, you can delete this or leave it as default. The code snippet is automatically filled with input data that you store in the test data section of teh APi Input Node.

5. Send the Request

Click Send to test your deployed flow. You should receive a response with your flow's output. Depending on your Deplyoment tpye the repsonses work differently: Async or Sync. Also the Deplyoment types may vary in terms of response time.

We have test deployments that you usually use for development or PoCs and that needs some time to get active when you call the API teh first time. In thsi case send teh first APi call and wait 1 minute to send the second if teh first one fails.

If you have a production deplyoment then teh response time is immeadiate depending on your flow type. Some deplyoment types only tell you that your flow was triggered successfully but do nto give you a result. If you expected a result then try different settings for teh deplyoment.

Integration Examples

cURL

curl -X POST https://backend.aicuflow.com/node/deployment-trigger/af86a8a6-40f2-4b92-9f83-c9b3bafb2ccb/ \
  -H "X-API-Key: sk-EuT64********oyU_O" \
  -H "Content-Type: application/json" \
  -d '{
    "input_data": {
      "param1": "value1"
}
  }'

Python

import requests

API_KEY = "sk-EuT64********oyU_O"
API_URL = "https://backend.aicuflow.com/node/deployment-trigger/af86a8a6-40f2-4b92-9f83-c9b3bafb2ccb/"

def trigger_deployment(input_data=None):
    """Trigger Chat Workflow Deployment - waits for completion and returns results"""
    response = requests.post(
        API_URL,
        headers={
            "X-API-Key": API_KEY,
            "Content-Type": "application/json"
        },
        json={
            "input_data": input_data or {},
        }
    )

    if response.ok:
        result = response.json()
        return result["data"]
    else:
        raise Exception(f"API Error: {response.text}")

# Usage example with test data
result = trigger_deployment({'param1': 'value1'})
print(f"Status: {result['status']}")
print(f"Output: {result['output_data']}")
print(f"Duration: {result.get('duration_seconds')} seconds")

JavaScript

const API_KEY = "sk-EuT64********oyU_O";
const API_URL =
  "https://backend.aicuflow.com/node/deployment-trigger/af86a8a6-40f2-4b92-9f83-c9b3bafb2ccb/";

async function triggerDeployment(inputData = {}) {
  // Waits for completion and returns results
  const response = await fetch(API_URL, {
    method: "POST",
    headers: {
      "X-API-Key": API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ input_data: inputData }),
  });

  const result = await response.json();

  if (result.status === "success") {
    return result.data;
  } else {
    throw new Error(`API Error: ${result.message}`);
  }
}

// Usage example with test data
const result = await triggerDeployment({
  param1: "value1",
});
console.log("Status:", result.status);
console.log("Output:", result.output_data);
console.log("Duration:", result.duration_seconds, "seconds");

Best Practices

Security

Never commit API keys to version control
Store API keys in environment variables
Rotate API keys periodically
Use different API keys for development and production

Error Handling

Always handle API errors gracefully
Check response status codes
Implement retry logic for transient failures
Log errors for debugging

Performance

Cache responses when appropriate
Use batch requests if available
Monitor API usage and latency
Set appropriate timeout values

Managing Deployments

View Deployments: See all active deployments in the deployment section
Update Deployment: Redeploy to push changes to your flow
Delete Deployment: Remove deployments you no longer need
Monitor Usage: Track API calls and performance metrics