This workflow follows the Chainllm → Google Gemini Chat recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "Summarize",
"nodes": [
{
"parameters": {
"path": "autopiahire/summarize",
"authentication": "headerAuth",
"responseMode": "responseNode",
"options": {}
},
"type": "n8n-nodes-base.webhook",
"typeVersion": 2.1,
"position": [
-512,
544
],
"id": "edc438d9-5ddf-4c42-822f-e8844558fd89",
"name": "Webhook",
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"destinationFieldName": "Certifications",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
208,
272
],
"id": "53812203-518a-49d6-be49-ad9b4d1f5a54",
"name": "Aggregate"
},
{
"parameters": {
"operation": "getAll",
"tableId": "certifications",
"returnAll": true,
"filters": {
"conditions": [
{
"keyName": "user_id",
"condition": "eq",
"keyValue": "={{ $('Webhook').item.json.query.user_id }}"
}
]
}
},
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-176,
272
],
"id": "0607ce21-81c7-4725-bf99-3523aea60d7f",
"name": "Certifications",
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"destinationFieldName": "Projects",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
208,
432
],
"id": "a15f78b4-ebd9-4d7e-a6d9-e34809da67ab",
"name": "Aggregate1"
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"destinationFieldName": "Skills",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
208,
592
],
"id": "79eae994-7a91-44ac-b015-e79cd93fdf4f",
"name": "Aggregate3"
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"destinationFieldName": "Experience",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
208,
768
],
"id": "ecdc788e-b272-47e7-a744-0c2192ac107b",
"name": "Aggregate4"
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"destinationFieldName": "Education",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
208,
944
],
"id": "99a18be3-71bb-41eb-af24-57c153214109",
"name": "Aggregate5"
},
{
"parameters": {
"numberInputs": 7
},
"type": "n8n-nodes-base.merge",
"typeVersion": 3.2,
"position": [
496,
448
],
"id": "53ad797c-f569-448a-b3f2-8387161c0715",
"name": "Merge"
},
{
"parameters": {
"promptType": "define",
"text": "={{ $json.data }}",
"hasOutputParser": true,
"messages": {
"messageValues": [
{
"message": "=You are a smart assistant whose job is to summarize a candidate\u2019s r\u00e9sum\u00e9 into a concise paragraph suitable for semantic job matching. Focus on extracting the candidate\u2019s main role, top 10 relevant skills, and key experience. Ignore personal details, education dates, or unrelated information. \n\nStart the paragraph with \"I\u2019m looking for\u2026\" as if the candidate is describing their professional profile for the type of jobs they want. Use clear, professional language that can be embedded for similarity search with job offers.\n\nExample format:\n\"I\u2019m looking for [main role] with skills in [skill1, skill2, \u2026, skill10], and experience in [key experience points].\""
}
]
},
"batching": {}
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.7,
"position": [
864,
528
],
"id": "5b42533e-14bc-4c52-8be1-73b2dbf7e397",
"name": "Basic LLM Chain",
"retryOnFail": false
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
864,
720
],
"id": "71f7ca8b-78d9-4b62-a98f-269f9f177b3b",
"name": "Google Gemini Chat Model",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "getAll",
"tableId": "projects",
"returnAll": true,
"filters": {
"conditions": [
{
"keyName": "user_id",
"condition": "eq",
"keyValue": "={{ $('Webhook').item.json.query.user_id }}"
}
]
}
},
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-176,
432
],
"id": "64c332a8-b462-4b9c-a7ab-53597227dcda",
"name": "Projects",
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "getAll",
"tableId": "skills",
"returnAll": true,
"filters": {
"conditions": [
{
"keyName": "user_id",
"condition": "eq",
"keyValue": "={{ $('Webhook').item.json.query.user_id }}"
}
]
}
},
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-176,
592
],
"id": "1a5f30aa-0f31-4dcd-9612-5134231763b6",
"name": "Skills",
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "getAll",
"tableId": "experiences",
"returnAll": true,
"filters": {
"conditions": [
{
"keyName": "user_id",
"condition": "eq",
"keyValue": "={{ $('Webhook').item.json.query.user_id }}"
}
]
}
},
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-176,
768
],
"id": "a8f22390-35b8-4edb-bcb1-613507415ece",
"name": "Experience",
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "getAll",
"tableId": "education",
"returnAll": true,
"filters": {
"conditions": [
{
"keyName": "user_id",
"condition": "eq",
"keyValue": "={{ $('Webhook').item.json.query.user_id }}"
}
]
}
},
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-176,
944
],
"id": "e65c4b04-c557-4d81-bfea-16acf4dc2b56",
"name": "Education",
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "getAll",
"tableId": "profiles",
"returnAll": true,
"filters": {
"conditions": [
{
"keyName": "id",
"condition": "eq",
"keyValue": "={{ $('Webhook').item.json.query.user_id }}"
}
]
}
},
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-96,
128
],
"id": "39a373c6-213f-4636-abcb-cded44d785af",
"name": "Profile",
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
672,
528
],
"id": "dd04f4a9-e3b5-473a-a0b8-0d1648b17f5d",
"name": "Aggregate6"
},
{
"parameters": {
"jsonSchemaExample": "{\n\t\"summary\": \"LaTex Resume here\"\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.3,
"position": [
1008,
720
],
"id": "a9156a6c-8e45-472d-a3b3-52e4f9abf4b2",
"name": "Structured Output Parser"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "e2cb5662-6000-4cfe-9b0c-1c440bc9dffa",
"name": "headline",
"value": "={{ $json.headline }}",
"type": "string"
},
{
"id": "34881916-471e-44f6-a01a-a49b045f0f84",
"name": "bio",
"value": "={{ $json.bio }}",
"type": "string"
},
{
"id": "6c9f7f56-1f7d-4500-94f4-dea1d6d946c9",
"name": "",
"value": "",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
112,
128
],
"id": "c1414dbe-e4d0-4729-bba7-17eb96e1198f",
"name": "Edit Fields1"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "6deefb86-f096-46d2-9b53-a4eb95886b75",
"name": "institution",
"value": "={{ $json.institution }}",
"type": "string"
},
{
"id": "cf54da59-8f1d-4961-b186-a5b944d5d554",
"name": "degree",
"value": "={{ $json.degree }}",
"type": "string"
},
{
"id": "7312f883-99e2-4e27-8489-d51527429534",
"name": "field_of_study",
"value": "={{ $json.field_of_study }}",
"type": "string"
},
{
"id": "acbebca3-2bf5-4c6d-8144-f0775424d0d1",
"name": "start_year",
"value": "={{ $json.start_year }}",
"type": "string"
},
{
"id": "737ffe03-ba56-4739-a413-ed34f00035c3",
"name": "end_year",
"value": "={{ $json.end_year }}",
"type": "string"
},
{
"id": "88b4ed48-9703-4f27-9383-1b067304d7cd",
"name": "description",
"value": "={{ $json.description }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
16,
944
],
"id": "64b60e6d-647e-410c-8f2f-dd3fd122eb18",
"name": "Edit Fields2"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "44dcaeee-c02b-4784-ae8d-c4937281d98c",
"name": "title",
"value": "={{ $json.title }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
16,
768
],
"id": "8acf5919-7fbd-44a8-acfe-63ff052519d6",
"name": "Edit Fields3"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "8c6ae517-831e-43b9-b8ae-7f6155e4515f",
"name": "name",
"value": "={{ $json.name }}",
"type": "string"
},
{
"id": "4ea7643e-fbbc-4ebe-9bc9-9b58ad2edaaf",
"name": "category",
"value": "={{ $json.category }}",
"type": "string"
},
{
"id": "14358c3a-4dfd-466f-bb4e-8597db91c4ab",
"name": "level",
"value": "={{ $json.level }}",
"type": "string"
},
{
"id": "aee5e9d4-bbe9-43ba-af49-a42c18505557",
"name": "verified",
"value": "={{ $json.verified }}",
"type": "string"
},
{
"id": "0b36d57d-095c-4fe0-9c50-b334c3dd9559",
"name": "verification_source",
"value": "={{ $json.verification_source }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
16,
592
],
"id": "63b0ee74-175b-46fc-9a6c-20fc3641ecad",
"name": "Edit Fields4"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "43eff227-fb14-4121-9a77-eed0ee2240b9",
"name": "title",
"value": "={{ $json.title }}",
"type": "string"
},
{
"id": "14877f47-083c-490c-a164-8cd1b7859a5a",
"name": "description",
"value": "={{ $json.description }}",
"type": "string"
},
{
"id": "b1c55a46-ee37-493c-9b21-894eaf66286c",
"name": "tech_stack",
"value": "={{ $json.tech_stack }}",
"type": "array"
},
{
"id": "2d136e14-eb09-4f6b-bdd1-bfd202fb3e6e",
"name": "role",
"value": "={{ $json.role }}",
"type": "string"
},
{
"id": "5ac69ebc-809c-47bd-9542-251a0126b6a1",
"name": "links",
"value": "={{ $json.links }}",
"type": "string"
},
{
"id": "2f0b6248-038e-4d4e-97f2-255e2afd8b87",
"name": "impact",
"value": "={{ $json.impact }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
16,
432
],
"id": "772a0b90-0992-4058-9a86-a334fee673c4",
"name": "Edit Fields6"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "0a78af73-4080-488d-b9c8-23c665d5cf86",
"name": "name",
"value": "={{ $json.name }}",
"type": "string"
},
{
"id": "2f46758d-e31c-4395-a58c-d29058ee2552",
"name": "issuer",
"value": "={{ $json.issuer }}",
"type": "string"
},
{
"id": "a5bc9eea-992f-4457-818e-ddbe583ae14e",
"name": "year",
"value": "={{ $json.year }}",
"type": "string"
},
{
"id": "24d3c684-0c61-4a7a-97e4-5782fc9f474d",
"name": "credential_url",
"value": "={{ $json.credential_url }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
16,
272
],
"id": "ad0ab4fc-ac27-422a-899f-76b70c89deaf",
"name": "Edit Fields7"
},
{
"parameters": {
"respondWith": "json",
"responseBody": "={\n \"summary\": \"{{ $('Basic LLM Chain').item.json.output.summary}}\"\n}",
"options": {
"responseCode": 200
}
},
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1.4,
"position": [
1344,
528
],
"id": "dbc29054-6a69-4ab8-b804-d7d24a3b954f",
"name": "Respond to Webhook"
}
],
"connections": {
"Webhook": {
"main": [
[
{
"node": "Certifications",
"type": "main",
"index": 0
},
{
"node": "Projects",
"type": "main",
"index": 0
},
{
"node": "Skills",
"type": "main",
"index": 0
},
{
"node": "Experience",
"type": "main",
"index": 0
},
{
"node": "Education",
"type": "main",
"index": 0
},
{
"node": "Profile",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"Certifications": {
"main": [
[
{
"node": "Edit Fields7",
"type": "main",
"index": 0
}
]
]
},
"Aggregate1": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 2
}
]
]
},
"Aggregate3": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 4
}
]
]
},
"Aggregate4": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 5
}
]
]
},
"Aggregate5": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 6
}
]
]
},
"Merge": {
"main": [
[
{
"node": "Aggregate6",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Projects": {
"main": [
[
{
"node": "Edit Fields6",
"type": "main",
"index": 0
}
]
]
},
"Skills": {
"main": [
[
{
"node": "Edit Fields4",
"type": "main",
"index": 0
}
]
]
},
"Experience": {
"main": [
[
{
"node": "Edit Fields3",
"type": "main",
"index": 0
}
]
]
},
"Education": {
"main": [
[
{
"node": "Edit Fields2",
"type": "main",
"index": 0
}
]
]
},
"Profile": {
"main": [
[
{
"node": "Edit Fields1",
"type": "main",
"index": 0
}
]
]
},
"Aggregate6": {
"main": [
[
{
"node": "Basic LLM Chain",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Basic LLM Chain",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Edit Fields1": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields2": {
"main": [
[
{
"node": "Aggregate5",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields3": {
"main": [
[
{
"node": "Aggregate4",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields4": {
"main": [
[
{
"node": "Aggregate3",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields6": {
"main": [
[
{
"node": "Aggregate1",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields7": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Basic LLM Chain": {
"main": [
[
{
"node": "Respond to Webhook",
"type": "main",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "bae1cdf6-7808-47bf-8663-1161b2a1d150",
"id": "pSmuzKeeqT1j4Vyr",
"tags": []
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googlePalmApihttpHeaderAuthsupabaseApi
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
Summarize. Uses supabase, chainLlm, lmChatGoogleGemini, outputParserStructured. Webhook trigger; 24 nodes.
Source: https://github.com/seif2003/utopiahire/blob/82dbc4fa8c5b10f63fc84777bd5b6725bb8f2569/n8n/Summarize.json — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
leads. Uses supabase, gmail, formTrigger, httpRequest. Webhook trigger; 62 nodes.
⏺ 🚀 How it works
Resume Screening & Behavioral Interviews with Gemini, Elevenlabs, & Notion ATS copy. Uses outputParserStructured, chainLlm, googleDrive, stickyNote. Webhook trigger; 67 nodes.
Candidate Engagement | Resume Screening | AI Voice Interviews | Applicant Insights
SEO Articles to Github Publish Workflow. Uses outputParserAutofixing, outputParserStructured, github, lmChatGoogleGemini. Webhook trigger; 44 nodes.