Two trigger node seems like it only execute one at a time

ampol_jon · September 18, 2025, 8:21am

Describe the problem/error/question

Hi, I need to execute the workflow which using 2 trigger node as

When Executed by Another Workflow
Webhook listener
The condition is first trigger is exceuted and around next 3 minutes the webhook trigger will run (1st workflow is the one who command external work and moddify my data, will trigger 2nd node after it finished)

i try asking AI assistant and i said i have to use merge node which setup as i want results after all input is arrived, but it seems like the execution i check it run 1 trigger at a time

how to actually done this properly

Please share your workflow

Information on your n8n setup

n8n version: 1.109.1 n8n cloud

krisn0x · September 18, 2025, 12:35pm

This is expected - you can’t have 2 triggers activating in the same execution. When one starts it creates its own execution.

I think it will be best, if in Workflow 1, you merge all data that you need, and pass it to workflow 2 via the Body of the webhook request. This will be the cleanest solution. In workflow 2, you would only use the webhook trigger.

jabbson · September 18, 2025, 1:51pm

If your situation allows, what I would do -

Start your child execution from the main workflow and immediately prepend the subworkflow trigger with an http request node which will send out the resumeUrl to a third party system which will later resume the execution. Then add a wait node, which awaits said webhook call (add a timeout timer of 3 minutes). When the third party system is ready, it calls the callback url and the child execution resumes.

Read more here on Wait node with “On webhook” execution mode.

gabrielhmsantos · September 18, 2025, 5:18pm

Hello @ampol_jon, how are you?

I think it would be helpful if you could provide the main flow so we can better understand your need and suggest the correct flow.

ampol_jon · September 19, 2025, 8:24am

My workflow 1 look like this

{
“nodes”: \[
{
“parameters”: {
“httpMethod”: “POST”,
“path”: “n8n-lark-to-webhook-listener”,
“authentication”: “basicAuth”,
“responseMode”: “responseNode”,
“options”: {}
},
“type”: “n8n-nodes-base.webhook”,
“typeVersion”: 2.1,
“position”: \[
-608,
448
\],
“id”: “bcd84fca-92db-4cc0-b7aa-192f16a8c129”,
“name”: “Lark listener”,
“webhookId”: “d364e6bd-bb35-4a53-8e83-df5c4388572e”,
“credentials”: {
“httpBasicAuth”: {
“id”: “r9mgjrXU1qnt55Sq”,
“name”: “lark-to-n8n”
}
}
},
{
“parameters”: {
“conditions”: {
“options”: {
“caseSensitive”: true,
“leftValue”: “”,
“typeValidation”: “strict”,
“version”: 2
},
“conditions”: \[
{
“id”: “74babfca-2109-4f97-9e55-42b726deef1e”,
“leftValue”: “={{ $json.query }}”,
“rightValue”: “\[^\\x00-\\x7F\]”,
“operator”: {
“type”: “string”,
“operation”: “notRegex”
}
}
\],
“combinator”: “or”
},
“options”: {}
},
“type”: “n8n-nodes-base.if”,
“typeVersion”: 2.2,
“position”: \[
-208,
448
\],
“id”: “3fb86ec0-60ec-4f59-94c6-ead44628a96d”,
“name”: “If”
},
{
“parameters”: {
“promptType”: “define”,
“text”: “=Translate this >> {{ $json.query }}\\n”,
“options”: {
“systemMessage”: “You are translator who aware of thai language to english which always looking for some specific keyword to make an exception such as student’s class or student’s school results retuen must not include double quote, only return the translated rusult without the command you gave”
}
},
“type”: “@n8n/n8n-nodes-langchain.agent”,
“typeVersion”: 2.2,
“position”: \[
16,
512
\],
“id”: “257c9364-d7ea-484b-bedb-8bc2d114e1c0”,
“name”: “AI Agent”
},
{
“parameters”: {
“model”: {
“\__rl”: true,
“value”: “gpt-4o”,
“mode”: “list”,
“cachedResultName”: “gpt-4o”
},
“options”: {}
},
“type”: “@n8n/n8n-nodes-langchain.lmChatOpenAi”,
“typeVersion”: 1.2,
“position”: \[
16,
688
\],
“id”: “7c73a618-e4d4-45c9-ac95-f0dc4299a202”,
“name”: “OpenAI Chat Model”,
“credentials”: {
“openAiApi”: {
“id”: “LTALH8M8UkR0YTWn”,
“name”: “OpenAi account”
}
}
},
{
“parameters”: {
“assignments”: {
“assignments”: \[
{
“id”: “f9aef9eb-e64e-4246-9d3b-c22b3248b722”,
“name”: “query”,
“value”: “={{ $json.body.queryContent }}”,
“type”: “string”
}
\]
},
“options”: {}
},
“type”: “n8n-nodes-base.set”,
“typeVersion”: 3.4,
“position”: \[
-400,
448
\],
“id”: “6c272e23-997c-45a5-be5f-756a1fad440c”,
“name”: “Select only text content”
},
{
“parameters”: {
“mode”: “raw”,
“jsonOutput”: "={\\n  "fromLarkFinalQuery": "{{ $json.query }}"\\n}   ",
“options”: {}
},
“type”: “n8n-nodes-base.set”,
“typeVersion”: 3.4,
“position”: \[
16,
304
\],
“id”: “02d941f6-d6b7-4270-9c19-e065fd716461”,
“name”: “fromLarkFinalQuery”
},
{
“parameters”: {
“mode”: “raw”,
“jsonOutput”: "={\\n  "fromLarkFinalQuery": "{{ $json.output }}"\\n}  ",
“options”: {}
},
“type”: “n8n-nodes-base.set”,
“typeVersion”: 3.4,
“position”: \[
320,
512
\],
“id”: “fd5abab3-280f-4d0c-8cd9-d3c92fa25a86”,
“name”: “fromLarkFinalQuery OpenAI”
},
{
“parameters”: {
“method”: “POST”,
“url”: “https://2536951710982325.5.gcp.databricks.com/api/2.2/jobs/run-now”,
“authentication”: “genericCredentialType”,
“genericAuthType”: “httpBearerAuth”,
“sendQuery”: true,
“specifyQuery”: “json”,
“jsonQuery”: "={\\n  "job_id" : "569943055844936"\\n}\\n ",
“sendBody”: true,
“specifyBody”: “json”,
“jsonBody”: “={\\n"job_id" : "569943055844936",\\n"notebook_params" : {\\n"queryContent" : "{{ $json.fromLarkFinalQuery }}"\\n}\\n}”,
“options”: {}
},
“type”: “n8n-nodes-base.httpRequest”,
“typeVersion”: 4.2,
“position”: \[
512,
304
\],
“id”: “20458962-b5f6-4e8c-8df9-4fe03f276494”,
“name”: “HTTP Request to Databrick”,
“credentials”: {
“httpBearerAuth”: {
“id”: “yIM9hKjEcs0QRBeM”,
“name”: “Databrick - Bearer Auth account”
}
}
},
{
“parameters”: {
“method”: “POST”,
“url”: “https://2536951710982325.5.gcp.databricks.com/api/2.2/jobs/run-now”,
“authentication”: “genericCredentialType”,
“genericAuthType”: “httpBearerAuth”,
“sendQuery”: true,
“specifyQuery”: “json”,
“jsonQuery”: "={\\n  "job_id" : "569943055844936"\\n}\\n ",
“sendBody”: true,
“specifyBody”: “json”,
“jsonBody”: “={\\n"job_id" : "569943055844936",\\n"notebook_params" : {\\n"queryContent" : "{{ $json.fromLarkFinalQuery }}"\\n}\\n}”,
“options”: {}
},
“type”: “n8n-nodes-base.httpRequest”,
“typeVersion”: 4.2,
“position”: \[
512,
512
\],
“id”: “6e21efa0-04f5-4b04-add2-5571beaa5fdd”,
“name”: “HTTP Request to Databrick1”,
“credentials”: {
“httpBearerAuth”: {
“id”: “yIM9hKjEcs0QRBeM”,
“name”: “Databrick - Bearer Auth account”
}
}
},
{
“parameters”: {
“respondWith”: “json”,
“responseBody”: “{{ JSON.stringify($input.all()\[0\].json) }}”,
“options”: {}
},
“type”: “n8n-nodes-base.respondToWebhook”,
“typeVersion”: 1.4,
“position”: \[
1088,
304
\],
“id”: “dc563eb2-c582-4b5d-b833-e78f76aff26f”,
“name”: “Respond to Webhook”,
“disabled”: true
},
{
“parameters”: {
“respondWith”: “json”,
“responseBody”: “{{ JSON.stringify($input.all()\[0\].json) }}”,
“options”: {}
},
“type”: “n8n-nodes-base.respondToWebhook”,
“typeVersion”: 1.4,
“position”: \[
1088,
512
\],
“id”: “435871a0-a212-4586-b445-7fd4eeb85cc5”,
“name”: “Respond to Webhook1”,
“disabled”: true
},
{
“parameters”: {
“workflowId”: {
“\__rl”: true,
“value”: “vRbVE289duanAqV4”,
“mode”: “list”,
“cachedResultName”: “Knowledge based project — Databrick listener sub-workflow”
},
“workflowInputs”: {
“mappingMode”: “defineBelow”,
“value”: {},
“matchingColumns”: [ ],
“schema”: [ ],
“attemptToConvertTypes”: false,
“convertFieldsToString”: true
},
“options”: {
“waitForSubWorkflow”: true
}
},
“type”: “n8n-nodes-base.executeWorkflow”,
“typeVersion”: 1.2,
“position”: \[
704,
304
\],
“id”: “bfcee77c-8248-424e-b839-8c3ab2b0bc4f”,
“name”: “Databrick listening”,
“disabled”: true
},
{
“parameters”: {
“workflowId”: {
“\__rl”: true,
“value”: “vRbVE289duanAqV4”,
“mode”: “list”,
“cachedResultName”: “Knowledge based project — Databrick listener sub-workflow”
},
“workflowInputs”: {
“mappingMode”: “defineBelow”,
“value”: {},
“matchingColumns”: [ ],
“schema”: [ ],
“attemptToConvertTypes”: false,
“convertFieldsToString”: true
},
“options”: {
“waitForSubWorkflow”: true
}
},
“type”: “n8n-nodes-base.executeWorkflow”,
“typeVersion”: 1.2,
“position”: \[
704,
512
\],
“id”: “37b60f5d-5cc4-4c8a-9193-ca1dfe5384ed”,
“name”: “Databrick listening1”,
“disabled”: true
},
{
“parameters”: {
“amount”: 2,
“unit”: “minutes”
},
“type”: “n8n-nodes-base.wait”,
“typeVersion”: 1.1,
“position”: \[
896,
512
\],
“id”: “540c2cee-6d17-499b-a003-3cdc541bf8a0”,
“name”: “Wait”,
“webhookId”: “c81ea56e-2cbb-4d62-b137-8f97cad6d166”,
“disabled”: true
},
{
“parameters”: {
“amount”: 2,
“unit”: “minutes”
},
“type”: “n8n-nodes-base.wait”,
“typeVersion”: 1.1,
“position”: \[
896,
304
\],
“id”: “16586515-1ad1-4cba-a525-d44264189c60”,
“name”: “Wait1”,
“webhookId”: “c81ea56e-2cbb-4d62-b137-8f97cad6d166”,
“disabled”: true
}
\],
“connections”: {
“Lark listener”: {
“main”: \[
\[
{
“node”: “Select only text content”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“If”: {
“main”: \[
\[
{
“node”: “fromLarkFinalQuery”,
“type”: “main”,
“index”: 0
}
\],
\[
{
“node”: “AI Agent”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“AI Agent”: {
“main”: \[
\[
{
“node”: “fromLarkFinalQuery OpenAI”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“OpenAI Chat Model”: {
“ai_languageModel”: \[
\[
{
“node”: “AI Agent”,
“type”: “ai_languageModel”,
“index”: 0
}
\]
\]
},
“Select only text content”: {
“main”: \[
\[
{
“node”: “If”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“fromLarkFinalQuery”: {
“main”: \[
\[
{
“node”: “HTTP Request to Databrick”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“fromLarkFinalQuery OpenAI”: {
“main”: \[
\[
{
“node”: “HTTP Request to Databrick1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“HTTP Request to Databrick”: {
“main”: \[
\[
{
“node”: “Databrick listening”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“HTTP Request to Databrick1”: {
“main”: \[
\[
{
“node”: “Databrick listening1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Respond to Webhook”: {
“main”: \[
[ ]
\]
},
“Databrick listening”: {
“main”: \[
\[
{
“node”: “Wait1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Databrick listening1”: {
“main”: \[
\[
{
“node”: “Wait”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Wait”: {
“main”: \[
\[
{
“node”: “Respond to Webhook1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Wait1”: {
“main”: \[
\[
{
“node”: “Respond to Webhook”,
“type”: “main”,
“index”: 0
}
\]
\]
}
},
“pinData”: {},
“meta”: {
“templateCredsSetupCompleted”: true,
“instanceId”: “0468f76c80d61f1e4ff92210c64de7e69e9bb1b7f99550f2e12e2e965f8f8a43”
}
}

the rusults from HTTP request databrick will be the one who trigger Databrick listener in that sub-workflow (the workflow on this topic)

krisn0x · September 19, 2025, 9:59am

Hey, sorry, the code is broken again, could you follow these steps to re-paste it:

Highlight all the nodes you want to copy
Ctrl+C / Cmd+C
In the reply, type ``` on a new line to open a code box
Paste in the code box

ampol_jon · September 19, 2025, 6:22pm

{
“nodes”: \[
{
“parameters”: {
“httpMethod”: “POST”,
“path”: “n8n-lark-to-webhook-listener”,
“authentication”: “basicAuth”,
“responseMode”: “responseNode”,
“options”: {}
},
“type”: “n8n-nodes-base.webhook”,
“typeVersion”: 2.1,
“position”: \[
-608,
448
\],
“id”: “bcd84fca-92db-4cc0-b7aa-192f16a8c129”,
“name”: “Lark listener”,
“webhookId”: “d364e6bd-bb35-4a53-8e83-df5c4388572e”,
“credentials”: {
“httpBasicAuth”: {
“id”: “r9mgjrXU1qnt55Sq”,
“name”: “lark-to-n8n”
}
}
},
{
“parameters”: {
“conditions”: {
“options”: {
“caseSensitive”: true,
“leftValue”: “”,
“typeValidation”: “strict”,
“version”: 2
},
“conditions”: \[
{
“id”: “74babfca-2109-4f97-9e55-42b726deef1e”,
“leftValue”: “={{ $json.query }}”,
“rightValue”: “\[^\\x00-\\x7F\]”,
“operator”: {
“type”: “string”,
“operation”: “notRegex”
}
}
\],
“combinator”: “or”
},
“options”: {}
},
“type”: “n8n-nodes-base.if”,
“typeVersion”: 2.2,
“position”: \[
-208,
448
\],
“id”: “3fb86ec0-60ec-4f59-94c6-ead44628a96d”,
“name”: “If”
},
{
“parameters”: {
“promptType”: “define”,
“text”: “=Translate this >> {{ $json.query }}\\n”,
“options”: {
“systemMessage”: “You are translator who aware of thai language to english which always looking for some specific keyword to make an exception such as student’s class or student’s school results retuen must not include double quote, only return the translated rusult without the command you gave”
}
},
“type”: “@n8n/n8n-nodes-langchain.agent”,
“typeVersion”: 2.2,
“position”: \[
16,
512
\],
“id”: “257c9364-d7ea-484b-bedb-8bc2d114e1c0”,
“name”: “AI Agent”
},
{
“parameters”: {
“model”: {
“\__rl”: true,
“value”: “gpt-4o”,
“mode”: “list”,
“cachedResultName”: “gpt-4o”
},
“options”: {}
},
“type”: “@n8n/n8n-nodes-langchain.lmChatOpenAi”,
“typeVersion”: 1.2,
“position”: \[
16,
688
\],
“id”: “7c73a618-e4d4-45c9-ac95-f0dc4299a202”,
“name”: “OpenAI Chat Model”,
“credentials”: {
“openAiApi”: {
“id”: “LTALH8M8UkR0YTWn”,
“name”: “OpenAi account”
}
}
},
{
“parameters”: {
“assignments”: {
“assignments”: \[
{
“id”: “f9aef9eb-e64e-4246-9d3b-c22b3248b722”,
“name”: “query”,
“value”: “={{ $json.body.queryContent }}”,
“type”: “string”
}
\]
},
“options”: {}
},
“type”: “n8n-nodes-base.set”,
“typeVersion”: 3.4,
“position”: \[
-400,
448
\],
“id”: “6c272e23-997c-45a5-be5f-756a1fad440c”,
“name”: “Select only text content”
},
{
“parameters”: {
“mode”: “raw”,
“jsonOutput”: "={\\n  "fromLarkFinalQuery": "{{ $json.query }}"\\n}   ",
“options”: {}
},
“type”: “n8n-nodes-base.set”,
“typeVersion”: 3.4,
“position”: \[
16,
304
\],
“id”: “02d941f6-d6b7-4270-9c19-e065fd716461”,
“name”: “fromLarkFinalQuery”
},
{
“parameters”: {
“mode”: “raw”,
“jsonOutput”: "={\\n  "fromLarkFinalQuery": "{{ $json.output }}"\\n}  ",
“options”: {}
},
“type”: “n8n-nodes-base.set”,
“typeVersion”: 3.4,
“position”: \[
320,
512
\],
“id”: “fd5abab3-280f-4d0c-8cd9-d3c92fa25a86”,
“name”: “fromLarkFinalQuery OpenAI”
},
{
“parameters”: {
“method”: “POST”,
“url”: “https://2536951710982325.5.gcp.databricks.com/api/2.2/jobs/run-now”,
“authentication”: “genericCredentialType”,
“genericAuthType”: “httpBearerAuth”,
“sendQuery”: true,
“specifyQuery”: “json”,
“jsonQuery”: "={\\n  "job_id" : "569943055844936"\\n}\\n ",
“sendBody”: true,
“specifyBody”: “json”,
“jsonBody”: “={\\n"job_id" : "569943055844936",\\n"notebook_params" : {\\n"queryContent" : "{{ $json.fromLarkFinalQuery }}"\\n}\\n}”,
“options”: {}
},
“type”: “n8n-nodes-base.httpRequest”,
“typeVersion”: 4.2,
“position”: \[
512,
304
\],
“id”: “20458962-b5f6-4e8c-8df9-4fe03f276494”,
“name”: “HTTP Request to Databrick”,
“credentials”: {
“httpBearerAuth”: {
“id”: “yIM9hKjEcs0QRBeM”,
“name”: “Databrick - Bearer Auth account”
}
}
},
{
“parameters”: {
“method”: “POST”,
“url”: “https://2536951710982325.5.gcp.databricks.com/api/2.2/jobs/run-now”,
“authentication”: “genericCredentialType”,
“genericAuthType”: “httpBearerAuth”,
“sendQuery”: true,
“specifyQuery”: “json”,
“jsonQuery”: "={\\n  "job_id" : "569943055844936"\\n}\\n ",
“sendBody”: true,
“specifyBody”: “json”,
“jsonBody”: “={\\n"job_id" : "569943055844936",\\n"notebook_params" : {\\n"queryContent" : "{{ $json.fromLarkFinalQuery }}"\\n}\\n}”,
“options”: {}
},
“type”: “n8n-nodes-base.httpRequest”,
“typeVersion”: 4.2,
“position”: \[
512,
512
\],
“id”: “6e21efa0-04f5-4b04-add2-5571beaa5fdd”,
“name”: “HTTP Request to Databrick1”,
“credentials”: {
“httpBearerAuth”: {
“id”: “yIM9hKjEcs0QRBeM”,
“name”: “Databrick - Bearer Auth account”
}
}
},
{
“parameters”: {
“respondWith”: “json”,
“responseBody”: “{{ JSON.stringify($input.all()\[0\].json) }}”,
“options”: {}
},
“type”: “n8n-nodes-base.respondToWebhook”,
“typeVersion”: 1.4,
“position”: \[
1088,
304
\],
“id”: “dc563eb2-c582-4b5d-b833-e78f76aff26f”,
“name”: “Respond to Webhook”,
“disabled”: true
},
{
“parameters”: {
“respondWith”: “json”,
“responseBody”: “{{ JSON.stringify($input.all()\[0\].json) }}”,
“options”: {}
},
“type”: “n8n-nodes-base.respondToWebhook”,
“typeVersion”: 1.4,
“position”: \[
1088,
512
\],
“id”: “435871a0-a212-4586-b445-7fd4eeb85cc5”,
“name”: “Respond to Webhook1”,
“disabled”: true
},
{
“parameters”: {
“workflowId”: {
“\__rl”: true,
“value”: “vRbVE289duanAqV4”,
“mode”: “list”,
“cachedResultName”: “Knowledge based project — Databrick listener sub-workflow”
},
“workflowInputs”: {
“mappingMode”: “defineBelow”,
“value”: {},
“matchingColumns”: [ ],
“schema”: [ ],
“attemptToConvertTypes”: false,
“convertFieldsToString”: true
},
“options”: {
“waitForSubWorkflow”: true
}
},
“type”: “n8n-nodes-base.executeWorkflow”,
“typeVersion”: 1.2,
“position”: \[
704,
304
\],
“id”: “bfcee77c-8248-424e-b839-8c3ab2b0bc4f”,
“name”: “Databrick listening”,
“disabled”: true
},
{
“parameters”: {
“workflowId”: {
“\__rl”: true,
“value”: “vRbVE289duanAqV4”,
“mode”: “list”,
“cachedResultName”: “Knowledge based project — Databrick listener sub-workflow”
},
“workflowInputs”: {
“mappingMode”: “defineBelow”,
“value”: {},
“matchingColumns”: [ ],
“schema”: [ ],
“attemptToConvertTypes”: false,
“convertFieldsToString”: true
},
“options”: {
“waitForSubWorkflow”: true
}
},
“type”: “n8n-nodes-base.executeWorkflow”,
“typeVersion”: 1.2,
“position”: \[
704,
512
\],
“id”: “37b60f5d-5cc4-4c8a-9193-ca1dfe5384ed”,
“name”: “Databrick listening1”,
“disabled”: true
},
{
“parameters”: {
“amount”: 2,
“unit”: “minutes”
},
“type”: “n8n-nodes-base.wait”,
“typeVersion”: 1.1,
“position”: \[
896,
512
\],
“id”: “540c2cee-6d17-499b-a003-3cdc541bf8a0”,
“name”: “Wait”,
“webhookId”: “c81ea56e-2cbb-4d62-b137-8f97cad6d166”,
“disabled”: true
},
{
“parameters”: {
“amount”: 2,
“unit”: “minutes”
},
“type”: “n8n-nodes-base.wait”,
“typeVersion”: 1.1,
“position”: \[
896,
304
\],
“id”: “16586515-1ad1-4cba-a525-d44264189c60”,
“name”: “Wait1”,
“webhookId”: “c81ea56e-2cbb-4d62-b137-8f97cad6d166”,
“disabled”: true
}
\],
“connections”: {
“Lark listener”: {
“main”: \[
\[
{
“node”: “Select only text content”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“If”: {
“main”: \[
\[
{
“node”: “fromLarkFinalQuery”,
“type”: “main”,
“index”: 0
}
\],
\[
{
“node”: “AI Agent”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“AI Agent”: {
“main”: \[
\[
{
“node”: “fromLarkFinalQuery OpenAI”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“OpenAI Chat Model”: {
“ai_languageModel”: \[
\[
{
“node”: “AI Agent”,
“type”: “ai_languageModel”,
“index”: 0
}
\]
\]
},
“Select only text content”: {
“main”: \[
\[
{
“node”: “If”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“fromLarkFinalQuery”: {
“main”: \[
\[
{
“node”: “HTTP Request to Databrick”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“fromLarkFinalQuery OpenAI”: {
“main”: \[
\[
{
“node”: “HTTP Request to Databrick1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“HTTP Request to Databrick”: {
“main”: \[
\[
{
“node”: “Databrick listening”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“HTTP Request to Databrick1”: {
“main”: \[
\[
{
“node”: “Databrick listening1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Respond to Webhook”: {
“main”: \[
[ ]
\]
},
“Databrick listening”: {
“main”: \[
\[
{
“node”: “Wait1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Databrick listening1”: {
“main”: \[
\[
{
“node”: “Wait”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Wait”: {
“main”: \[
\[
{
“node”: “Respond to Webhook1”,
“type”: “main”,
“index”: 0
}
\]
\]
},
“Wait1”: {
“main”: \[
\[
{
“node”: “Respond to Webhook”,
“type”: “main”,
“index”: 0
}
\]
\]
}
},
“pinData”: {},
“meta”: {
“templateCredsSetupCompleted”: true,
“instanceId”: “0468f76c80d61f1e4ff92210c64de7e69e9bb1b7f99550f2e12e2e965f8f8a43”
}
}

seems like it is not working…

krisn0x · September 19, 2025, 6:40pm

No worries, can you save it as a .json file and upload it here instead?

system · December 18, 2025, 6:41pm

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