Trigger Node

Each workflow contains a single trigger node.

There are two main types of triggers: Schedule and API endpoint. The Schedule trigger also supports adding custom conditions (e.g., run the workflow only if new emails are available).

Schedule:

Schedule based trigger node

CRON expressions are used to schedule workflow triggers. You can also add custom conditions.

API:

API endpoint trigger node

Triggering a workflow:

POST /workflows/{id}/jobs

To trigger a workflow via API, send a POST request to https://api.trudo.ai/workflows/{workflow_id_here}/jobs with the required data. This will start the workflow and return a job ID, which can be used to monitor the workflow's status. To receive the API call results, set the system variable wait_for_result to true. Keep in mind that wait_for_result is not forwarded to the workflow itself. To return an API response from the node, use the api_response key like this:

return { 'api_response': your_data_here }

The maximum size of the input and output data is limited to 200 KB.

Headers

Name	Value
Content-Type	application/json
Authorization	Bearer <api_key>

Body

Name	Type	Description
wait_for_result	boolean	optional (default: False)
... your own variables		Include on same level

Response

200

{
    "job_id": "new_job_id", // use this job_id to check status
    "status": "COMPLETED", // PENDING | RUNNING | FAILED | COMPLETED
    "data": {
      // your data from the api_response will be included here.
    }
}

400

{
    "statusCode": 400,
    "body": "Unsupported method or path"
}

403

{
    "statusCode": 403,
    "body": "Authorization failure. Please check the API key."
}

404

{
    "statusCode": 404,
    "body": "error_message_here"
}

example errors: 
 - Endpoint with this workflowId is not deployed.
 - Please provide a valid workflow_id: /workflows/{workflow_id}/jobs

500

{
    "statusCode": 500,
    "body": "Something went wrong, please try again later."
}

Python sample

import requests

# Sample data based on listOfParameters
data = {
    #wait_for_result is a system variable, not passed to the workflow
    "wait_for_result": True,
    #... include the rest of your parameters below. Samples
    "user_id": "3298fh3298dsa", 
    "message": "Please renew my membership"
}

# API endpoint
api_endpoint = "https://api.trudo.ai/workflows/{workflow_id}/jobs"

# Headers
headers = {
    "content-type": "application/json",
    "authorization": "Bearer YOUR_API_KEY"
}

# Make the POST request
response = requests.post(api_endpoint, json=data, headers=headers)

# Check if the request was successful
if response.status_code == 200:
    print("Success:", response.json())
else:
    print("Error:", response.text)

Get job's results and status:

GET /workflows/{id}/jobs/{id}

To get the status and output of a workflow job , send a GET request to https://api.trudo.ai/workflows/{workflow_id_here}/jobs/{job_id}

Headers

Name	Value
Content-Type	application/json
Authorization	Bearer <api_key>

Response

200

{
    "job_id": "job_id", // use this job_id to check status
    "status": "COMPLETED", // PENDING | RUNNING | FAILED | COMPLETED
    "data": {
      // your data from the api_response will be included here.
    }
}

400

{
    "statusCode": 400,
    "body": "Unsupported method or path"
}

403

{
    "statusCode": 403,
    "body": "Authorization failure. Please check the API key."
}

404

{
    "statusCode": 404,
    "body": "error_message_here"
}

example errors: 
 - Endpoint with this workflowId is not deployed.
 - Please provide a valid workflow_id: /workflows/{workflow_id}/jobs

500

{
    "statusCode": 500,
    "body": "Something went wrong, please try again later."
}

import requests

# API endpoint
api_endpoint = f"https://api.trudo.ai/workflows/{workflow_id}/jobs/{job_id}"

# Headers
headers = {
    "content-type": "application/json",
    "authorization": "Bearer YOUR_API_KEY"
}

# Make the GET request
response = requests.get(api_endpoint, headers=headers)

# Check if the request was successful
if response.status_code == 200:
    print("Job Status:", response.json())
else:
    print("Error:", response.text)