{
  "workflow": {
    "id": 2341,
    "name": "Build a tax code assistant with Qdrant, Mistral.ai and OpenAI",
    "views": 10412,
    "recentViews": 0,
    "totalViews": 10412,
    "createdAt": "2024-07-11T10:41:27.677Z",
    "description": "This n8n workflows builds another example of creating a knowledgebase assistant but demonstrates how a more deliberate and targeted approach to ingesting the data can produce much better results for your chatbot.\n\nIn this example, a government tax code policy document is used. Whilst we could split the document into chunks by content length, we often lose the context of chapters and sections which may be required by the user.\n\nOur approach then is to first split the document into chapters and sections before importing into our vector store. Additionally, using metadata correctly is key to allow filtering and scoped queries.\n\n## Example\n\n**Human**: \"Tell me about what the tax code says about cargo for intentional commerce?\"\n\n**AI**: \"Section 11.25 of the Texas Property Tax Code pertains to \"MARINE CARGO CONTAINERS USED EXCLUSIVELY IN INTERNATIONAL COMMERCE.\" In this section, a person who is a citizen of a foreign country or an en...\"\n\n## How it works\n\n* The tax code policy document is downloaded as a zip file from the government website and its pages are extracted as separate chapters.\n* Each chapter is then parsed and split into its sections using data manipulation expressions.\n* Each section is then inserted into our Qdrant vector store tagged with its source, chapter and section numbers as metadata.\n* When our AI Agent needs to retrieve data from our vector store, we use a custom workflow tool to perform the query to Qdrant.\n* Because we're relying on Qdrant's advanced filtering capabilities, we perform the search using the Qdrant API rather than the Qdrant node.\n* When the AI Agent, needs to pull full wording or extracts, we can use Qdrant's scroll API and metadata filtering to do so. This makes Qdrant behave like a key-value store for our document.\n\n## Requirements\n* A Qdrant instance is required for the vector store and specifically for it's filtering functionality.\n* Mistral.ai account for Embeddings and AI models.\n\n## Customising this workflow\n\nDepending on your use-case, consider returning actual PDF pages (or links) to the user for the extra confirmation and to build trust.\n\nNot using Mistral? You are able to replace but note to match the distance and dimension size of Qdrant collection to your chosen embedding model.",
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          "name": "When clicking ‘Test workflow’",
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                  },
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            "jsonMode": "expressionData"
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          ],
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            "url": "https://statutes.capitol.texas.gov/Docs/Zips/TX.pdf.zip",
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          "type": "n8n-nodes-base.splitOut",
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          ],
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            "include": "allOtherFields",
            "options": {},
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            "operation": "pdf",
            "binaryPropertyName": "=file_{{ $itemIndex }}"
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            "assignments": {
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          "name": "Execute Workflow Trigger",
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          "parameters": {},
          "typeVersion": 1
        },
        {
          "id": "3a93c19b-09d9-4e38-8b0c-2008fc03f7fc",
          "name": "Get Mistral Embeddings",
          "type": "n8n-nodes-base.httpRequest",
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            "url": "https://api.mistral.ai/v1/embeddings",
            "method": "POST",
            "options": {},
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            "bodyParameters": {
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                  "value": "mistral-embed"
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                  "name": "input",
                  "value": "={{ $json.query }}"
                }
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            },
            "nodeCredentialType": "mistralCloudApi"
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            "mistralCloudApi": {
              "id": "credential-id",
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            "assignments": {
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                  "name": "=content",
                  "type": "array",
                  "value": "={{ new Array(Math.round($json.content.length / Math.min($json.content.length, 30000))).fill('').map((_,idx) => $json.content.substring(idx * 30000, idx * 50000 + 30000)) }}"
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          ],
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            "fieldToSplitOut": "content"
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          "name": "For Each Section...",
          "type": "n8n-nodes-base.splitInBatches",
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            "batchSize": 5
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            "conditions": {
              "options": {
                "leftValue": "",
                "caseSensitive": true,
                "typeValidation": "strict"
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              "conditions": [
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                  },
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                  "rightValue": ""
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        {
          "id": "dfe1818f-93b7-4116-8a6e-dcb2e6c23fcf",
          "name": "Use Qdrant Search API1",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
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          ],
          "parameters": {
            "url": "=http://qdrant:6333/collections/texas_tax_codes/points/search",
            "method": "POST",
            "options": {},
            "sendBody": true,
            "authentication": "predefinedCredentialType",
            "bodyParameters": {
              "parameters": [
                {
                  "name": "limit",
                  "value": "={{ 4 }}"
                },
                {
                  "name": "vector",
                  "value": "={{ $json.data[0].embedding }}"
                },
                {
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                  "value": "={{ true }}"
                }
              ]
            },
            "nodeCredentialType": "qdrantApi"
          },
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          ],
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              "pagination": {
                "pagination": {
                  "parameters": {
                    "parameters": [
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                        "name": "next_page_offset",
                        "type": "body",
                        "value": "={{ $response.body.result.next_page_offset }}"
                      }
                    ]
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                  "completeExpression": "={{ $response.body.result.next_page_offset === null }}",
                  "paginationCompleteWhen": "other"
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                  "name": "limit",
                  "value": "={{ 100 }}"
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                },
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                  "value": "={{\n{\n  \"must\": [\n    ($json.query.section\n      ? { \"key\": \"metadata.section\", \"match\": { \"value\": $json.query.section } }\n      : { \"key\": \"metadata.chapter\", \"match\": { \"value\": $json.query.chapter } }\n    )\n  ]\n}\n}}"
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              "id": "credential-id",
              "name": "qdrantApi Credential"
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        },
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          "name": "Get Search Response",
          "type": "n8n-nodes-base.set",
          "position": [
            1860,
            1320
          ],
          "parameters": {
            "options": {},
            "assignments": {
              "assignments": [
                {
                  "id": "08ad2d6e-4ed1-409e-b89c-1f0c7fdf1b64",
                  "name": "response",
                  "type": "string",
                  "value": "=---\nchapter: {{ $json.result.points.first().payload.metadata.chapter }}\nsection: {{ $json.result.points.first().payload.metadata.section }}\ntitle: {{ $json.result.points.first().payload.metadata.title }}\n---\n{{ $json.result.points\n      .toSorted((a,b) => (a.payload.metadata.content_order || 0) - (b.payload.metadata.content_order || 0))\n      .map(point => point.payload.content).join('\\n') }}"
                }
              ]
            }
          },
          "typeVersion": 3.3
        },
        {
          "id": "3b23ff5e-158a-470f-a262-d001d52feeba",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -100,
            183.38345554113084
          ],
          "parameters": {
            "color": 7,
            "width": 571.4359274276384,
            "height": 352.65642339230595,
            "content": "## Step 1. Download the Tax Code PDF\n[Read more about handling Zip Files](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.compression/)\n\nLet's begin by pulling a zip file containing all the tax codes as separate PDF files. We can unzip on the fly with n8n's compression node."
          },
          "typeVersion": 1
        },
        {
          "id": "02826887-eb26-48a0-928e-fe56ee008425",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            500,
            199.87747230655896
          ],
          "parameters": {
            "color": 7,
            "width": 777.897719182587,
            "height": 503.3459981018574,
            "content": "## Step 2. Extract and Partition Into Chapters & Sections\n[Learn more about reading PDF Files](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.extractfromfile)\n\nRather than ingest the raw text of the PDF, we'll be a little more strategic and extract the tax code sections separately instead. Not only will this provide cleaner results, we'll also be able to fetch sections in isolation if required."
          },
          "typeVersion": 1
        },
        {
          "id": "31a34972-31ab-4b96-9d09-cd30a3b184cf",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1300,
            108.82958126396
          ],
          "parameters": {
            "color": 7,
            "width": 1045.1698686248747,
            "height": 771.1260499456115,
            "content": "## Step 3. Save into Qdrant VectorStore\n[Read more about using the Qdrant Vectorstore](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoreqdrant)\n\nWe'll save our data into a Qdrant collection being mindful to use metadata to take full advantage of Qdrant's filtering capabilities later.\nThough not always required, since the tax code documents can be quite large we'll implement a loop here to throttle the number of tokens being processed as to not trip the Mistral.ai rate limits for embeddings."
          },
          "typeVersion": 1
        },
        {
          "id": "27039fa6-6388-45ee-a2d5-6bb68554944b",
          "name": "Qdrant Vector Store",
          "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
          "position": [
            1760,
            400
          ],
          "parameters": {
            "mode": "insert",
            "options": {},
            "qdrantCollection": {
              "__rl": true,
              "mode": "list",
              "value": "texas_tax_codes",
              "cachedResultName": "texas_tax_codes"
            }
          },
          "credentials": {
            "qdrantApi": {
              "id": "credential-id",
              "name": "qdrantApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "5ec16c20-eb1e-454a-8165-594d83dd8711",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            360,
            900
          ],
          "parameters": {
            "color": 7,
            "width": 858.1415560000298,
            "height": 513.2269439624808,
            "content": "## Step 4. Build a Tax Code Assistant ChatBot\n[Learn more about using AI Agents in n8n](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent)\n\nFor our chatbot, we'll use an AI agent node because we want to achieve more than one functionality. The first will be querying to relevant texts to answer a user's question and secondly, a direct search feature to pull full section text when requested."
          },
          "typeVersion": 1
        },
        {
          "id": "d5145c6f-768b-42d8-a045-20e045f52b0b",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1240,
            904.6076722083936
          ],
          "parameters": {
            "color": 7,
            "width": 1030.0926850706744,
            "height": 577.7854680142904,
            "content": "## Step 5. Use Qdrant API as Tools\n[Learn more about using AI Agents in n8n](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent)\n\nOur Ask Tool will generate embeddings using Mistral.ai and query our Qdrant collection using the Qdrant Search API.\nOur Search Tool will use filter our Qdrant collection using the Qdrant Scroll API, matching on each doc's section metadata key."
          },
          "typeVersion": 1
        },
        {
          "id": "ccf50479-53d8-4edf-8f2b-73060a6a6e0f",
          "name": "AI Agent",
          "type": "@n8n/n8n-nodes-langchain.agent",
          "position": [
            700,
            1063
          ],
          "parameters": {
            "options": {
              "systemMessage": "You are a helpful assistant answering user questions on the tax code legistration for the state of Texas, united states of america.\n\nAlong with your response also note in which chapter and section number the information was found. "
            }
          },
          "typeVersion": 1.6
        },
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          "id": "d7e7fa9e-73ba-4df3-862e-25af63d9d9b4",
          "name": "Window Buffer Memory",
          "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
          "position": [
            820,
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          ],
          "parameters": {},
          "typeVersion": 1.2
        },
        {
          "id": "a79bdbcd-7157-470a-aadc-bd3f8a4c40d2",
          "name": "When chat message received",
          "type": "@n8n/n8n-nodes-langchain.chatTrigger",
          "position": [
            420,
            1063
          ],
          "webhookId": "db2b118d-942e-4be9-b154-7df887232f97",
          "parameters": {
            "public": true,
            "options": {
              "loadPreviousSession": "memory"
            },
            "initialMessages": ""
          },
          "typeVersion": 1
        },
        {
          "id": "6046f137-b508-484f-8577-ac51a35eee09",
          "name": "Window Buffer Memory1",
          "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
          "position": [
            420,
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          ],
          "parameters": {},
          "typeVersion": 1.2
        },
        {
          "id": "30f238f8-1987-4d6d-b06d-ac2106ea3734",
          "name": "OpenAI Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
          "position": [
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          ],
          "parameters": {
            "options": {}
          },
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              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "8a8490f6-5957-495c-a7af-15cec669f39c",
          "name": "1sec",
          "type": "n8n-nodes-base.wait",
          "position": [
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          ],
          "webhookId": "852317f0-aadf-4658-ae44-d05e5de29302",
          "parameters": {
            "amount": 1
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          "executeOnce": false,
          "typeVersion": 1.1
        },
        {
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          "name": "Ask Tool",
          "type": "@n8n/n8n-nodes-langchain.toolWorkflow",
          "position": [
            960,
            1223
          ],
          "parameters": {
            "name": "query_tax_code_knowledgebase",
            "fields": {
              "values": [
                {
                  "name": "route",
                  "stringValue": "ask_tool"
                }
              ]
            },
            "workflowId": "={{ $workflow.id }}",
            "description": "Call this tool to query the tax code database for information. Structure your query in the form of a question for best results."
          },
          "typeVersion": 1.1
        },
        {
          "id": "ee455a4e-c9a1-49b2-a036-d3f3d34099c6",
          "name": "Search Tool",
          "type": "@n8n/n8n-nodes-langchain.toolWorkflow",
          "position": [
            1060,
            1223
          ],
          "parameters": {
            "name": "get_tax_code_section",
            "fields": {
              "values": [
                {
                  "name": "route",
                  "stringValue": "search_tool"
                }
              ]
            },
            "workflowId": "={{ $workflow.id }}",
            "description": "Call this tool to search for specific sections of the tax code document. Pass in either a known section number/id to get the section's text or a known chapter name to return all sections for the chapter.",
            "jsonSchemaExample": "{\n\t\"chapter\": \"some_value\",\n    \"section\": \"Sec 1.01\"\n}",
            "specifyInputSchema": true
          },
          "typeVersion": 1.1
        },
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          "name": "Switch",
          "type": "n8n-nodes-base.switch",
          "position": [
            1473,
            1200
          ],
          "parameters": {
            "rules": {
              "values": [
                {
                  "outputKey": "ask_tool",
                  "conditions": {
                    "options": {
                      "leftValue": "",
                      "caseSensitive": true,
                      "typeValidation": "strict"
                    },
                    "combinator": "and",
                    "conditions": [
                      {
                        "operator": {
                          "type": "string",
                          "operation": "equals"
                        },
                        "leftValue": "={{ $json.route }}",
                        "rightValue": "ask_tool"
                      }
                    ]
                  },
                  "renameOutput": true
                },
                {
                  "outputKey": "search_tool",
                  "conditions": {
                    "options": {
                      "leftValue": "",
                      "caseSensitive": true,
                      "typeValidation": "strict"
                    },
                    "combinator": "and",
                    "conditions": [
                      {
                        "id": "909362ed-eb97-405c-9f2f-f404a3bfeaf3",
                        "operator": {
                          "name": "filter.operator.equals",
                          "type": "string",
                          "operation": "equals"
                        },
                        "leftValue": "={{ $json.route }}",
                        "rightValue": "search_tool"
                      }
                    ]
                  },
                  "renameOutput": true
                }
              ]
            },
            "options": {}
          },
          "typeVersion": 3
        },
        {
          "id": "71441b5a-099b-49e0-a212-3087d958b38b",
          "name": "Get Ask Response",
          "type": "n8n-nodes-base.set",
          "position": [
            2060,
            1060
          ],
          "parameters": {
            "options": {},
            "assignments": {
              "assignments": [
                {
                  "id": "eb5f2b3c-bb88-4cae-a960-164016c9a9e4",
                  "name": "response",
                  "type": "string",
                  "value": "=|chapter|section|title|content|\n|-|-|-|-|\n{{\n  $json.result.map(row => [\n    '',\n    row.payload.metadata.chapter,\n    row.payload.metadata.section,\n    row.payload.metadata.title,\n    row.payload.content,\n    ''\n  ].join('|')).join('\\n')\n}}"
                }
              ]
            }
          },
          "typeVersion": 3.3
        },
        {
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          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -520,
            -79.56762868134751
          ],
          "parameters": {
            "width": 383.14868794462586,
            "height": 563.604204119637,
            "content": "## Try Me Out!\n### This workflow builds an AI powered Legal assistant who answers questions about tax codes.\n* Download publically available tax code PDFs from the relevant government website.\n* Strategically exact tax code sections and store these in our Qdrant Vectorstore using Mistral.ai embeddings.\n* Use an AI Agent to answer user's tax questions by attaching tools which query our Qdrant vectorstore.\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
          },
          "typeVersion": 1
        },
        {
          "id": "7f802f12-03e0-4b8e-a880-8c26242c1152",
          "name": "Sticky Note6",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            790.1971986436472,
            720
          ],
          "parameters": {
            "color": 5,
            "width": 489.3944544742706,
            "height": 131.61363932813174,
            "content": "### 🙋‍♀️What's the difference?\nWith raw PDF data, we may blur the boundaries between chapters and sections making later results hard to find, incoherent or misleading.\nDepending on your use-case, store your data in a way you intend to retrieve it!"
          },
          "typeVersion": 1
        }
      ],
      "pinData": {},
      "connections": {
        "1sec": {
          "main": [
            [
              {
                "node": "For Each Section...",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Switch": {
          "main": [
            [
              {
                "node": "Get Mistral Embeddings",
                "type": "main",
                "index": 0
              }
            ],
            [
              {
                "node": "Use Qdrant Scroll API",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Ask Tool": {
          "ai_tool": [
            [
              {
                "node": "AI Agent",
                "type": "ai_tool",
                "index": 0
              }
            ]
          ]
        },
        "Search Tool": {
          "ai_tool": [
            [
              {
                "node": "AI Agent",
                "type": "ai_tool",
                "index": 0
              }
            ]
          ]
        },
        "Files as Items": {
          "main": [
            [
              {
                "node": "Extract PDF Contents",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Map To Sections": {
          "main": [
            [
              {
                "node": "Sections To List",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Sections To List": {
          "main": [
            [
              {
                "node": "Only Valid Sections",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Split Out Chunks": {
          "main": [
            [
              {
                "node": "Qdrant Vector Store",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Extract Zip Files": {
          "main": [
            [
              {
                "node": "Files as Items",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "OpenAI Chat Model": {
          "ai_languageModel": [
            [
              {
                "node": "AI Agent",
                "type": "ai_languageModel",
                "index": 0
              }
            ]
          ]
        },
        "Default Data Loader": {
          "ai_document": [
            [
              {
                "node": "Qdrant Vector Store",
                "type": "ai_document",
                "index": 0
              }
            ]
          ]
        },
        "For Each Section...": {
          "main": [
            null,
            [
              {
                "node": "Content Chunking @ 50k Chars",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Only Valid Sections": {
          "main": [
            [
              {
                "node": "For Each Section...",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Qdrant Vector Store": {
          "main": [
            [
              {
                "node": "1sec",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Extract From Chapter": {
          "main": [
            [
              {
                "node": "Map To Sections",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Extract PDF Contents": {
          "main": [
            [
              {
                "node": "Extract From Chapter",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Window Buffer Memory": {
          "ai_memory": [
            [
              {
                "node": "AI Agent",
                "type": "ai_memory",
                "index": 0
              }
            ]
          ]
        },
        "Get Tax Code Zip File": {
          "main": [
            [
              {
                "node": "Extract Zip Files",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Use Qdrant Scroll API": {
          "main": [
            [
              {
                "node": "Get Search Response",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Window Buffer Memory1": {
          "ai_memory": [
            [
              {
                "node": "When chat message received",
                "type": "ai_memory",
                "index": 0
              }
            ]
          ]
        },
        "Get Mistral Embeddings": {
          "main": [
            [
              {
                "node": "Use Qdrant Search API1",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Use Qdrant Search API1": {
          "main": [
            [
              {
                "node": "Get Ask Response",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Embeddings Mistral Cloud": {
          "ai_embedding": [
            [
              {
                "node": "Qdrant Vector Store",
                "type": "ai_embedding",
                "index": 0
              }
            ]
          ]
        },
        "Execute Workflow Trigger": {
          "main": [
            [
              {
                "node": "Switch",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "When chat message received": {
          "main": [
            [
              {
                "node": "AI Agent",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Content Chunking @ 50k Chars": {
          "main": [
            [
              {
                "node": "Split Out Chunks",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Recursive Character Text Splitter": {
          "ai_textSplitter": [
            [
              {
                "node": "Default Data Loader",
                "type": "ai_textSplitter",
                "index": 0
              }
            ]
          ]
        },
        "When clicking ‘Test workflow’": {
          "main": [
            [
              {
                "node": "Get Tax Code Zip File",
                "type": "main",
                "index": 0
              }
            ]
          ]
        }
      }
    },
    "lastUpdatedBy": null,
    "workflowInfo": {
      "nodeCount": 38,
      "nodeTypes": {
        "n8n-nodes-base.set": {
          "count": 5
        },
        "n8n-nodes-base.wait": {
          "count": 1
        },
        "n8n-nodes-base.filter": {
          "count": 1
        },
        "n8n-nodes-base.switch": {
          "count": 1
        },
        "n8n-nodes-base.splitOut": {
          "count": 3
        },
        "n8n-nodes-base.stickyNote": {
          "count": 7
        },
        "n8n-nodes-base.compression": {
          "count": 1
        },
        "n8n-nodes-base.httpRequest": {
          "count": 4
        },
        "n8n-nodes-base.manualTrigger": {
          "count": 1
        },
        "n8n-nodes-base.splitInBatches": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.agent": {
          "count": 1
        },
        "n8n-nodes-base.extractFromFile": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.chatTrigger": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.lmChatOpenAi": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.toolWorkflow": {
          "count": 2
        },
        "n8n-nodes-base.executeWorkflowTrigger": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.vectorStoreQdrant": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.memoryBufferWindow": {
          "count": 2
        },
        "@n8n/n8n-nodes-langchain.embeddingsMistralCloud": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.documentDefaultDataLoader": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter": {
          "count": 1
        }
      }
    },
    "status": "published",
    "user": {
      "name": "Jimleuk",
      "username": "jimleuk",
      "bio": "Founder @ Subworkflow.ai - the fastest way to build durable RAG applications.\n\nFreelance AI Automation Engineer based in London, UK. Since 2024, my n8n templates have documented my journey into applied AI and have helped hundreds of businesses and organisations get up to speed with AI automation. Today, I continue to explore use-cases as AI evolves and occasionally upload templates which I find novel and interesting.\n\nSubscribe to the RSS Feed: https://cdn.subworkflow.ai/n8n-templates/rss.xml",
      "verified": true,
      "links": [
        "https://linkedin.com/in/jimleuk"
      ],
      "avatar": "https://gravatar.com/avatar/4ab99e51473df76838beeaac908747f7928c625f869794815cabe34016967d51?r=pg&d=retro&size=200"
    },
    "nodes": [
      {
        "id": 19,
        "icon": "file:httprequest.svg",
        "name": "n8n-nodes-base.httpRequest",
        "codex": {
          "data": {
            "alias": [
              "API",
              "Request",
              "URL",
              "Build",
              "cURL"
            ],
            "resources": {
              "generic": [
                {
                  "url": "https://n8n.io/blog/2021-the-year-to-automate-the-new-you-with-n8n/",
                  "icon": "☀️",
                  "label": "2021: The Year to Automate the New You with n8n"
                },
                {
                  "url": "https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/",
                  "icon": "🧬",
                  "label": "Why business process automation with n8n can change your daily life"
                },
                {
                  "url": "https://n8n.io/blog/automatically-pulling-and-visualizing-data-with-n8n/",
                  "icon": "📈",
                  "label": "Automatically pulling and visualizing data with n8n"
                },
                {
                  "url": "https://n8n.io/blog/learn-how-to-automatically-cross-post-your-content-with-n8n/",
                  "icon": "✍️",
                  "label": "Learn how to automatically cross-post your content with n8n"
                },
                {
                  "url": "https://n8n.io/blog/automatically-adding-expense-receipts-to-google-sheets-with-telegram-mindee-twilio-and-n8n/",
                  "icon": "🧾",
                  "label": "Automatically Adding Expense Receipts to Google Sheets with Telegram, Mindee, Twilio, and n8n"
                },
                {
                  "url": "https://n8n.io/blog/running-n8n-on-ships-an-interview-with-maranics/",
                  "icon": "🛳",
                  "label": "Running n8n on ships: An interview with Maranics"
                },
                {
                  "url": "https://n8n.io/blog/what-are-apis-how-to-use-them-with-no-code/",
                  "icon": " 🪢",
                  "label": "What are APIs and how to use them with no code"
                },
                {
                  "url": "https://n8n.io/blog/5-tasks-you-can-automate-with-notion-api/",
                  "icon": "⚡️",
                  "label": "5 tasks you can automate with the new Notion API "
                },
                {
                  "url": "https://n8n.io/blog/world-poetry-day-workflow/",
                  "icon": "📜",
                  "label": "Celebrating World Poetry Day with a daily poem in Telegram"
                },
                {
                  "url": "https://n8n.io/blog/automate-google-apps-for-productivity/",
                  "icon": "💡",
                  "label": "15 Google apps you can combine and automate to increase productivity"
                },
                {
                  "url": "https://n8n.io/blog/automate-designs-with-bannerbear-and-n8n/",
                  "icon": "🎨",
                  "label": "Automate Designs with Bannerbear and n8n"
                },
                {
                  "url": "https://n8n.io/blog/how-uproc-scraped-a-multi-page-website-with-a-low-code-workflow/",
                  "icon": " 🕸️",
                  "label": "How uProc scraped a multi-page website with a low-code workflow"
                },
                {
                  "url": "https://n8n.io/blog/building-an-expense-tracking-app-in-10-minutes/",
                  "icon": "📱",
                  "label": "Building an expense tracking app in 10 minutes"
                },
                {
                  "url": "https://n8n.io/blog/5-workflow-automations-for-mattermost-that-we-love-at-n8n/",
                  "icon": "🤖",
                  "label": "5 workflow automations for Mattermost that we love at n8n"
                },
                {
                  "url": "https://n8n.io/blog/how-to-use-the-http-request-node-the-swiss-army-knife-for-workflow-automation/",
                  "icon": "🧰",
                  "label": "How to use the HTTP Request Node - The Swiss Army Knife for Workflow Automation"
                },
                {
                  "url": "https://n8n.io/blog/learn-how-to-use-webhooks-with-mattermost-slash-commands/",
                  "icon": "🦄",
                  "label": "Learn how to use webhooks with Mattermost slash commands"
                },
                {
                  "url": "https://n8n.io/blog/how-a-membership-development-manager-automates-his-work-and-investments/",
                  "icon": "📈",
                  "label": "How a Membership Development Manager automates his work and investments"
                },
                {
                  "url": "https://n8n.io/blog/a-low-code-bitcoin-ticker-built-with-questdb-and-n8n-io/",
                  "icon": "📈",
                  "label": "A low-code bitcoin ticker built with QuestDB and n8n.io"
                },
                {
                  "url": "https://n8n.io/blog/how-to-set-up-a-ci-cd-pipeline-with-no-code/",
                  "icon": "🎡",
                  "label": "How to set up a no-code CI/CD pipeline with GitHub and TravisCI"
                },
                {
                  "url": "https://n8n.io/blog/automations-for-activists/",
                  "icon": "✨",
                  "label": "How Common Knowledge use workflow automation for activism"
                },
                {
                  "url": "https://n8n.io/blog/creating-scheduled-text-affirmations-with-n8n/",
                  "icon": "🤟",
                  "label": "Creating scheduled text affirmations with n8n"
                },
                {
                  "url": "https://n8n.io/blog/how-goomer-automated-their-operations-with-over-200-n8n-workflows/",
                  "icon": "🛵",
                  "label": "How Goomer automated their operations with over 200 n8n workflows"
                },
                {
                  "url": "https://n8n.io/blog/aws-workflow-automation/",
                  "label": "7 no-code workflow automations for Amazon Web Services"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.httprequest/"
                }
              ]
            },
            "categories": [
              "Development",
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"output\"]",
        "defaults": {
          "name": "HTTP Request",
          "color": "#0004F5"
        },
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        "displayName": "HTTP Request",
        "typeVersion": 4,
        "nodeCategories": [
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            "id": 5,
            "name": "Development"
          },
          {
            "id": 9,
            "name": "Core Nodes"
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        ]
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        "id": 38,
        "icon": "fa:pen",
        "name": "n8n-nodes-base.set",
        "codex": {
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              "Set",
              "JS",
              "JSON",
              "Filter",
              "Transform",
              "Map"
            ],
            "resources": {
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                  "url": "https://n8n.io/blog/learn-to-automate-your-factorys-incident-reporting-a-step-by-step-guide/",
                  "icon": "🏭",
                  "label": "Learn to Automate Your Factory's Incident Reporting: A Step by Step Guide"
                },
                {
                  "url": "https://n8n.io/blog/2021-the-year-to-automate-the-new-you-with-n8n/",
                  "icon": "☀️",
                  "label": "2021: The Year to Automate the New You with n8n"
                },
                {
                  "url": "https://n8n.io/blog/automatically-pulling-and-visualizing-data-with-n8n/",
                  "icon": "📈",
                  "label": "Automatically pulling and visualizing data with n8n"
                },
                {
                  "url": "https://n8n.io/blog/database-monitoring-and-alerting-with-n8n/",
                  "icon": "📡",
                  "label": "Database Monitoring and Alerting with n8n"
                },
                {
                  "url": "https://n8n.io/blog/automatically-adding-expense-receipts-to-google-sheets-with-telegram-mindee-twilio-and-n8n/",
                  "icon": "🧾",
                  "label": "Automatically Adding Expense Receipts to Google Sheets with Telegram, Mindee, Twilio, and n8n"
                },
                {
                  "url": "https://n8n.io/blog/no-code-ecommerce-workflow-automations/",
                  "icon": "store",
                  "label": "6 e-commerce workflows to power up your Shopify s"
                },
                {
                  "url": "https://n8n.io/blog/how-to-build-a-low-code-self-hosted-url-shortener/",
                  "icon": "🔗",
                  "label": "How to build a low-code, self-hosted URL shortener in 3 steps"
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                {
                  "url": "https://n8n.io/blog/automate-your-data-processing-pipeline-in-9-steps-with-n8n/",
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                {
                  "url": "https://n8n.io/blog/5-tasks-you-can-automate-with-notion-api/",
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                  "label": "15 Google apps you can combine and automate to increase productivity"
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                  "label": "How a Membership Development Manager automates his work and investments"
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                {
                  "url": "https://n8n.io/blog/a-low-code-bitcoin-ticker-built-with-questdb-and-n8n-io/",
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                  "label": "A low-code bitcoin ticker built with QuestDB and n8n.io"
                },
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                  "icon": "🎖",
                  "label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin"
                },
                {
                  "url": "https://n8n.io/blog/how-goomer-automated-their-operations-with-over-200-n8n-workflows/",
                  "icon": "🛵",
                  "label": "How Goomer automated their operations with over 200 n8n workflows"
                },
                {
                  "url": "https://n8n.io/blog/aws-workflow-automation/",
                  "label": "7 no-code workflow automations for Amazon Web Services"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.set/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Edit Fields"
        },
        "iconData": {
          "icon": "pen",
          "type": "icon"
        },
        "displayName": "Edit Fields (Set)",
        "typeVersion": 3,
        "nodeCategories": [
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            "name": "Core Nodes"
          }
        ]
      },
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        "id": 39,
        "icon": "fa:sync",
        "name": "n8n-nodes-base.splitInBatches",
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              "Split",
              "Split In Batches"
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            "resources": {
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                  "url": "https://n8n.io/blog/how-uproc-scraped-a-multi-page-website-with-a-low-code-workflow/",
                  "icon": " 🕸️",
                  "label": "How uProc scraped a multi-page website with a low-code workflow"
                },
                {
                  "url": "https://n8n.io/blog/benefits-of-automation-and-n8n-an-interview-with-hubspots-hugh-durkin/",
                  "icon": "🎖",
                  "label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin"
                }
              ],
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                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.splitinbatches/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Flow"
              ]
            }
          }
        },
        "group": "[\"organization\"]",
        "defaults": {
          "name": "Loop Over Items",
          "color": "#007755"
        },
        "iconData": {
          "icon": "sync",
          "type": "icon"
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        "displayName": "Loop Over Items (Split in Batches)",
        "typeVersion": 3,
        "nodeCategories": [
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            "name": "Core Nodes"
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        "icon": "fa:map-signs",
        "name": "n8n-nodes-base.switch",
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                  "url": "https://n8n.io/blog/2021-the-year-to-automate-the-new-you-with-n8n/",
                  "icon": "☀️",
                  "label": "2021: The Year to Automate the New You with n8n"
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                {
                  "url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
                  "icon": "👥",
                  "label": "How to get started with CRM automation (with 3 no-code workflow ideas"
                },
                {
                  "url": "https://n8n.io/blog/build-your-own-virtual-assistant-with-n8n-a-step-by-step-guide/",
                  "icon": "👦",
                  "label": "Build your own virtual assistant with n8n: A step by step guide"
                },
                {
                  "url": "https://n8n.io/blog/automation-for-maintainers-of-open-source-projects/",
                  "icon": "🏷️",
                  "label": "How to automatically manage contributions to open-source projects"
                }
              ],
              "primaryDocumentation": [
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                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.switch/"
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            },
            "categories": [
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Flow"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Switch",
          "color": "#506000"
        },
        "iconData": {
          "icon": "map-signs",
          "type": "icon"
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        "displayName": "Switch",
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            "name": "Core Nodes"
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        "icon": "fa:file-archive",
        "name": "n8n-nodes-base.compression",
        "codex": {
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            "alias": [
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              "Gzip",
              "uncompress",
              "compress",
              "decompress",
              "archive",
              "unarchive",
              "Binary",
              "Files",
              "File"
            ],
            "details": "The Compression node is useful when you want to compress files to either gzip or zip format. You can even use this node to decompress your gzip and zip files.",
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.compression/"
                }
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              "Data & Storage"
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
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                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Compression",
          "color": "#408000"
        },
        "iconData": {
          "icon": "file-archive",
          "type": "icon"
        },
        "displayName": "Compression",
        "typeVersion": 1,
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            "name": "Data & Storage"
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            "name": "Core Nodes"
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        "icon": "fa:pause-circle",
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              "timeout"
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                  "url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
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                  "label": "How to get started with CRM automation (with 3 no-code workflow ideas"
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                {
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                  "label": "7 no-code workflow automations for Amazon Web Services"
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers",
                "Flow"
              ]
            }
          }
        },
        "group": "[\"organization\"]",
        "defaults": {
          "name": "Wait",
          "color": "#804050"
        },
        "iconData": {
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          "type": "icon"
        },
        "displayName": "Wait",
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            "name": "Core Nodes"
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        ]
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        "id": 565,
        "icon": "fa:sticky-note",
        "name": "n8n-nodes-base.stickyNote",
        "codex": {
          "data": {
            "alias": [
              "Comments",
              "Notes",
              "Sticky"
            ],
            "categories": [
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            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Sticky Note",
          "color": "#FFD233"
        },
        "iconData": {
          "icon": "sticky-note",
          "type": "icon"
        },
        "displayName": "Sticky Note",
        "typeVersion": 1,
        "nodeCategories": [
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            "id": 9,
            "name": "Core Nodes"
          }
        ]
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        "icon": "fa:sign-out-alt",
        "name": "n8n-nodes-base.executeWorkflowTrigger",
        "codex": {
          "data": {
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.executeworkflowtrigger/"
                }
              ]
            },
            "categories": [
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "When Executed by Another Workflow",
          "color": "#ff6d5a"
        },
        "iconData": {
          "icon": "sign-out-alt",
          "type": "icon"
        },
        "displayName": "Execute Workflow Trigger",
        "typeVersion": 1,
        "nodeCategories": [
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            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 838,
        "icon": "fa:mouse-pointer",
        "name": "n8n-nodes-base.manualTrigger",
        "codex": {
          "data": {
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.manualworkflowtrigger/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "When clicking ‘Execute workflow’",
          "color": "#909298"
        },
        "iconData": {
          "icon": "mouse-pointer",
          "type": "icon"
        },
        "displayName": "Manual Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
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        "id": 844,
        "icon": "fa:filter",
        "name": "n8n-nodes-base.filter",
        "codex": {
          "data": {
            "alias": [
              "Router",
              "Filter",
              "Condition",
              "Logic",
              "Boolean",
              "Branch"
            ],
            "details": "The Filter node can be used to filter items based on a condition. If the condition is met, the item will be passed on to the next node. If the condition is not met, the item will be omitted. Conditions can be combined together by AND(meet all conditions), or OR(meet at least one condition).",
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.filter/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Flow",
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Filter",
          "color": "#229eff"
        },
        "iconData": {
          "icon": "filter",
          "type": "icon"
        },
        "displayName": "Filter",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 1119,
        "icon": "fa:robot",
        "name": "@n8n/n8n-nodes-langchain.agent",
        "codex": {
          "data": {
            "alias": [
              "LangChain",
              "Chat",
              "Conversational",
              "Plan and Execute",
              "ReAct",
              "Tools"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Agents",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
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          "name": "AI Agent",
          "color": "#404040"
        },
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          "type": "icon"
        },
        "displayName": "AI Agent",
        "typeVersion": 3,
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            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
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        "id": 1153,
        "icon": "file:openAiLight.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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              "Language Models": [
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              "Memory": [
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          "type": "icon"
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            "name": "AI"
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        "icon": "fa:grip-lines-vertical",
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            "subcategories": {
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              "AI": [
                "Tools"
              ],
              "Tools": [
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              ]
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          }
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            "id": 26,
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        "icon": "file:extractFromFile.svg",
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              "xls",
              "xlsx",
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              "tabular",
              "decode",
              "decoding",
              "Move Binary Data",
              "Binary",
              "File",
              "PDF",
              "JSON",
              "HTML",
              "ICS",
              "iCal",
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              "RTF",
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              "Base64",
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                "Data Transformation"
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            "subcategories": {
              "Core Nodes": [
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      },
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        "icon": "file:binary.svg",
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        "codex": {
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              ]
            },
            "categories": [
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              "Langchain"
            ],
            "subcategories": {
              "AI": [
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              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Default Data Loader"
        },
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