AutomationFlowsAI & RAG › AI Case Law Summarizer

AI Case Law Summarizer

Original n8n title: Case Law Summarizer

Case Law Summarizer. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 11 nodes.

Webhook trigger★★★☆☆ complexityAI-powered11 nodesText Splitter Character Text SplitterCohere EmbeddingsSupabase Vector StoreTool Vector StoreMemory Buffer WindowOpenAI ChatAgentGoogle Sheets
AI & RAG Trigger: Webhook Nodes: 11 Complexity: ★★★☆☆ AI nodes: yes Added:

This workflow follows the Agent → Cohere Embeddings 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 →

Download .json
{
  "name": "Case Law Summarizer",
  "nodes": [
    {
      "parameters": {
        "content": "## Case Law Summarizer",
        "height": 520,
        "width": 1100
      },
      "id": "006b4ac8-2240-4377-8187-c75ea40decd4",
      "name": "Sticky",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        -500,
        -250
      ]
    },
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "case_law_summarizer"
      },
      "id": "227c2cd5-dac0-4605-ad24-ece826a73ecd",
      "name": "Webhook",
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 1,
      "position": [
        -300,
        0
      ]
    },
    {
      "parameters": {
        "chunkSize": 400,
        "chunkOverlap": 40
      },
      "id": "0a8ac20a-08b4-42d4-b262-d5ff3c038f00",
      "name": "Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter",
      "typeVersion": 1,
      "position": [
        -100,
        0
      ]
    },
    {
      "parameters": {
        "model": "default"
      },
      "id": "63a3c905-3d2c-4abe-bf0f-495545792f87",
      "name": "Embeddings",
      "type": "@n8n/n8n-nodes-langchain.embeddingsCohere",
      "typeVersion": 1,
      "position": [
        100,
        0
      ],
      "credentials": {
        "cohereApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "mode": "insert",
        "indexName": "case_law_summarizer"
      },
      "id": "892173fb-f931-44d9-9e1e-134c71ec790e",
      "name": "Insert",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
      "typeVersion": 1,
      "position": [
        300,
        0
      ],
      "credentials": {
        "supabaseApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "indexName": "case_law_summarizer"
      },
      "id": "4f1f0bf3-db65-4714-9f4a-da40a9e379dc",
      "name": "Query",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
      "typeVersion": 1,
      "position": [
        300,
        -180
      ],
      "credentials": {
        "supabaseApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "name": "Supabase"
      },
      "id": "d5912b1d-60d5-4b91-851a-915fb49b1ae9",
      "name": "Tool",
      "type": "@n8n/n8n-nodes-langchain.toolVectorStore",
      "typeVersion": 1,
      "position": [
        480,
        -180
      ]
    },
    {
      "parameters": {},
      "id": "b7fd299a-99b0-4ae0-bda0-fc77583f869e",
      "name": "Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "typeVersion": 1.3,
      "position": [
        480,
        -40
      ]
    },
    {
      "parameters": {},
      "id": "16c7cd0f-ad11-4869-940e-13d321d445b5",
      "name": "Chat",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1,
      "position": [
        480,
        -340
      ],
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json }}"
      },
      "id": "e5198aee-0eeb-40dc-9b5b-113a423049dc",
      "name": "Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 1,
      "position": [
        760,
        -40
      ]
    },
    {
      "parameters": {
        "operation": "append",
        "documentId": "SHEET_ID",
        "sheetName": "Log"
      },
      "id": "fc62655e-9611-4eba-a44e-63f56903c218",
      "name": "Sheet",
      "type": "n8n-nodes-base.googleSheets",
      "typeVersion": 4,
      "position": [
        960,
        -40
      ],
      "credentials": {
        "googleSheetsOAuth2Api": {
          "name": "<your credential>"
        }
      }
    }
  ],
  "connections": {
    "Webhook": {
      "main": [
        [
          {
            "node": "Splitter",
            "type": "main",
            "index": 0
          },
          {
            "node": "Memory",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Splitter": {
      "main": [
        [
          {
            "node": "Embeddings",
            "type": "main",
            "index": 0
          }
        ]
      ],
      "ai_textSplitter": [
        [
          {
            "node": "Insert",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings": {
      "ai_embedding": [
        [
          {
            "node": "Insert",
            "type": "ai_embedding",
            "index": 0
          },
          {
            "node": "Query",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Insert": {
      "ai_document": [
        []
      ]
    },
    "Query": {
      "ai_vectorStore": [
        [
          {
            "node": "Tool",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "Tool": {
      "ai_tool": [
        [
          {
            "node": "Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Memory": {
      "ai_memory": [
        [
          {
            "node": "Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Chat": {
      "ai_languageModel": [
        [
          {
            "node": "Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Agent": {
      "main": [
        [
          {
            "node": "Sheet",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}

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About this workflow

Case Law Summarizer. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 11 nodes.

Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →

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