{
  "name": "Stock Q&A Workflow",
  "nodes": [
    {
      "id": "ec3b86be-4113-4fd5-8365-02adb67693e9",
      "name": "Embeddings OpenAI1",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        1960,
        720
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "42fd8020-3861-4d0f-a7a2-70e2c35f0bed",
      "name": "On new manual Chat Message",
      "type": "@n8n/n8n-nodes-langchain.manualChatTrigger",
      "disabled": true,
      "position": [
        1620,
        240
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "a9b48d04-691e-4537-90f8-d7a4aa6153af",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1560,
        120
      ],
      "parameters": {
        "color": 6,
        "width": 903.0896125323785,
        "height": 733.5099670584011,
        "content": "## Step 2: Setup the Q&A \n### The incoming message from the webhook is queried from the Supabase Vector Store. The response is provided in the response webhook. "
      },
      "typeVersion": 1
    },
    {
      "id": "472b4800-745a-4337-9545-163247f7e9ae",
      "name": "Retrieval QA Chain",
      "type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
      "position": [
        1880,
        240
      ],
      "parameters": {
        "query": "={{ $json.body.input }}"
      },
      "typeVersion": 1
    },
    {
      "id": "e58bd82d-abc6-44ed-8e93-ec5436126d66",
      "name": "Respond to Webhook",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        2280,
        240
      ],
      "parameters": {
        "options": {},
        "respondWith": "text",
        "responseBody": "={{ $json.response.text }}"
      },
      "typeVersion": 1
    },
    {
      "id": "04bbf01e-8269-47c7-897d-4ea94a1bd1c0",
      "name": "Vector Store Retriever",
      "type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
      "position": [
        2020,
        440
      ],
      "parameters": {
        "topK": 5
      },
      "typeVersion": 1
    },
    {
      "id": "feee6d68-2e0d-4d40-897e-c1d833a13bf2",
      "name": "Webhook1",
      "type": "n8n-nodes-base.webhook",
      "position": [
        1620,
        420
      ],
      "parameters": {
        "path": "19f5499a-3083-4783-93a0-e8ed76a9f742",
        "options": {},
        "httpMethod": "POST",
        "responseMode": "responseNode"
      },
      "typeVersion": 1.1
    },
    {
      "id": "1b8d251f-7069-4d7d-b6d6-4bfa683d4ad1",
      "name": "When clicking \"Execute Workflow\"",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        280,
        260
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "b746a7a4-ed94-4332-bf7b-65aadcf54130",
      "name": "Google Drive",
      "type": "n8n-nodes-base.googleDrive",
      "position": [
        580,
        260
      ],
      "parameters": {
        "fileId": {
          "__rl": true,
          "mode": "list",
          "value": "REPLACE_WITH_RESOURCE"
        },
        "options": {},
        "operation": "download"
      },
      "typeVersion": 3
    },
    {
      "id": "83a7d470-f934-436d-ba3f-1ae7c776f5a5",
      "name": "Binary to Document",
      "type": "@n8n/n8n-nodes-langchain.documentBinaryInputLoader",
      "position": [
        860,
        480
      ],
      "parameters": {
        "loader": "pdfLoader",
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "b52b4a90-99a1-49cc-a6f0-7551d6754496",
      "name": "Recursive Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        860,
        640
      ],
      "parameters": {
        "options": {},
        "chunkSize": 3000,
        "chunkOverlap": 200
      },
      "typeVersion": 1
    },
    {
      "id": "b525e130-2029-4f55-a603-1fdc05a19c17",
      "name": "Embeddings OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        1160,
        480
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "5358c53f-55f9-431d-8956-c6bae7ad25bc",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        540,
        120
      ],
      "parameters": {
        "color": 6,
        "width": 772.0680602743597,
        "height": 732.3675002130781,
        "content": "## Step 1: Upserting the PDF\n### Fetch file from Google Drive, split it into chunks and insert into Supabase index\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "fb91e2da-0eeb-47a5-aa49-65bf56986857",
      "name": "Qdrant Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        940,
        260
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "qdrantCollection": {
          "__rl": true,
          "mode": "id",
          "value": "=crowd"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "89e14837-d1fc-4b1e-9ebc-7cf3e7fd9a70",
      "name": "Qdrant Vector Store1",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        1980,
        600
      ],
      "parameters": {
        "qdrantCollection": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $json.body.company }}"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "c619245b-5ea0-4354-974d-21ec6b8efa93",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1880,
        460
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "e4aa780d-8069-4308-a61f-82ed876af71a",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -560,
        120
      ],
      "parameters": {
        "color": 6,
        "width": 710.9124489067698,
        "height": 726.4452519516944,
        "content": "## Start here: Step-by Step Youtube Tutorial :star:\n\n[![Building an AI Crew to Analyze Financial Data with CrewAI and n8n](https://img.youtube.com/vi/pMvizUx5n1g/sddefault.jpg)](https://www.youtube.com/watch?v=pMvizUx5n1g)\n"
      },
      "typeVersion": 1
    },
    {
      "id": "9a9346ba-33dc-5673-8526-eca4c18cf79b",
      "name": "Publication · Overview and setup",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        -1360,
        0
      ],
      "parameters": {
        "content": "# Stock Q&A Workflow\n\n## Purpose and structure\nThis folder contains the **Stock Q&A Workflow** workflow. Its executable nodes use `chainRetrievalQa`, `documentBinaryInputLoader`, `embeddingsOpenAi`, `googleDrive`, `lmChatOpenAi`, `manualChatTrigger`, `manualTrigger`, `respondToWebhook`, `retrieverVectorStore`, `textSplitterRecursiveCharacterTextSplitter`, `vectorStoreQdrant`, `webhook`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nOn new manual Chat Message, Webhook1, When clicking \"Execute Workflow\"\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nhttps://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Webhook/1255_Webhook_Respondtowebhook_Automate_Webhook.json\nMIT; preserve source notices.",
        "width": 700,
        "height": 800,
        "color": 1
      }
    }
  ],
  "active": false,
  "settings": {},
  "connections": {
    "Webhook1": {
      "main": [
        [
          {
            "node": "Retrieval QA Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Drive": {
      "main": [
        [
          {
            "node": "Qdrant Vector Store",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings OpenAI": {
      "ai_embedding": [
        [
          {
            "node": "Qdrant Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Retrieval QA Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Binary to Document": {
      "ai_document": [
        [
          {
            "node": "Qdrant Vector Store",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings OpenAI1": {
      "ai_embedding": [
        [
          {
            "node": "Qdrant Vector Store1",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Retrieval QA Chain": {
      "main": [
        [
          {
            "node": "Respond to Webhook",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Qdrant Vector Store1": {
      "ai_vectorStore": [
        [
          {
            "node": "Vector Store Retriever",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "Vector Store Retriever": {
      "ai_retriever": [
        [
          {
            "node": "Retrieval QA Chain",
            "type": "ai_retriever",
            "index": 0
          }
        ]
      ]
    },
    "On new manual Chat Message": {
      "main": [
        [
          {
            "node": "Retrieval QA Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking \"Execute Workflow\"": {
      "main": [
        [
          {
            "node": "Google Drive",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Recursive Character Text Splitter": {
      "ai_textSplitter": [
        [
          {
            "node": "Binary to Document",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    }
  }
}