RAG Ingestion Pipeline with Postgres

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": "RAG Ingestion Pipeline",
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "rag/ingest",
        "responseMode": "lastNode"
      },
      "name": "Webhook Trigger",
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2,
      "position": [
        250,
        300
      ],
      "id": "node-webhook-ingest"
    },
    {
      "parameters": {
        "resource": "textSplitter",
        "operation": "splitText",
        "text": "={{ $json.body.text }}",
        "chunkSize": 1000,
        "chunkOverlap": 200
      },
      "name": "Split Text",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "typeVersion": 1,
      "position": [
        500,
        300
      ],
      "id": "node-text-splitter"
    },
    {
      "parameters": {
        "url": "http://litellm-svc:4000/v1/embeddings",
        "method": "POST",
        "sendHeaders": true,
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer {{ $env.LITELLM_MASTER_KEY }}"
            },
            {
              "name": "Content-Type",
              "value": "application/json"
            }
          ]
        },
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "model",
              "value": "text-embedding-3-small"
            },
            {
              "name": "input",
              "value": "={{ $json.text }}"
            }
          ]
        }
      },
      "name": "Generate Embeddings",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        750,
        300
      ],
      "id": "node-embeddings"
    },
    {
      "parameters": {
        "operation": "executeQuery",
        "query": "INSERT INTO documents (content, metadata, embedding) VALUES ($1, $2, $3::vector)",
        "additionalFields": {
          "queryParams": "={{ [$json.text, JSON.stringify($json.metadata || {}), '[' + $json.data[0].embedding.join(',') + ']'] }}"
        }
      },
      "name": "Store in pgvector",
      "type": "n8n-nodes-base.postgres",
      "typeVersion": 2,
      "position": [
        1000,
        300
      ],
      "id": "node-pgvector-store",
      "credentials": {
        "postgres": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {},
      "name": "Success Response",
      "type": "n8n-nodes-base.respondToWebhook",
      "typeVersion": 1,
      "position": [
        1250,
        300
      ],
      "id": "node-respond"
    }
  ],
  "connections": {
    "Webhook Trigger": {
      "main": [
        [
          {
            "node": "Split Text",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Split Text": {
      "main": [
        [
          {
            "node": "Generate Embeddings",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Generate Embeddings": {
      "main": [
        [
          {
            "node": "Store in pgvector",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Store in pgvector": {
      "main": [
        [
          {
            "node": "Success Response",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  },
  "tags": [
    {
      "name": "rag"
    },
    {
      "name": "ingestion"
    }
  ]
}

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.

• postgres

About this workflow

RAG Ingestion Pipeline. Uses textSplitterRecursiveCharacterTextSplitter, httpRequest, postgres. Webhook trigger; 5 nodes.

Source: https://github.com/Embernet-ai/Ember-AI/blob/3ad03892d9aba348a8b7fcd0b3134f4c2e3c4d39/workflows/rag-ingestion.json — original creator credit. Request a take-down →

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