Steuerrechtlicher Assistent mit Qdrant, Mistral.ai und OpenAI bauen

Experte

Dies ist ein Finance, AI-Bereich Automatisierungsworkflow mit 38 Nodes. Hauptsächlich werden Set, Wait, Filter, Switch, SplitOut und andere Nodes verwendet, kombiniert mit KI-Technologie für intelligente Automatisierung. Steuerrechtlichen Assistenten mit Qdrant, Mistral.ai und OpenAI bauen

Voraussetzungen
  • Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • OpenAI API Key
  • Qdrant-Serververbindungsdaten
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "meta": {
    "instanceId": "26ba763460b97c249b82942b23b6384876dfeb9327513332e743c5f6219c2b8e"
  },
  "nodes": [
    {
      "id": "1bb3c94e-326e-41ca-82e4-102a598dba39",
      "name": "Bei Klick auf 'Workflow testen'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -320,
        300
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "751b283b-ea88-4fcd-ace3-3c86631f8876",
      "name": "Embeddings Mistral Cloud",
      "type": "@n8n/n8n-nodes-langchain.embeddingsMistralCloud",
      "position": [
        1760,
        560
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "mistralCloudApi": {
          "id": "EIl2QxhXAS9Hkg37",
          "name": "Mistral Cloud account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "f0851949-1036-4040-84df-61295cc5db74",
      "name": "Standard-Datenlader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        1900,
        560
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "chapter",
                "value": "={{ $('For Each Section...').item.json.chapter }}"
              },
              {
                "name": "section",
                "value": "={{ $('For Each Section...').item.json.label }}"
              },
              {
                "name": "=title",
                "value": "={{ $('For Each Section...').item.json.title }}"
              },
              {
                "name": "content_order",
                "value": "={{ $itemIndex }}"
              }
            ]
          }
        },
        "jsonData": "={{ $json.content }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "41d10b61-9fbe-446e-a65a-0db6e0116e5b",
      "name": "Rekursiver Zeichentext-Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1920,
        680
      ],
      "parameters": {
        "options": {},
        "chunkSize": 2000
      },
      "typeVersion": 1
    },
    {
      "id": "a1ecb096-4d31-4993-b801-ca3f09a9edc7",
      "name": "Steuergesetz-Zip-Datei abrufen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -20,
        340
      ],
      "parameters": {
        "url": "https://statutes.capitol.texas.gov/Docs/Zips/TX.pdf.zip",
        "options": {
          "response": {
            "response": {
              "responseFormat": "file"
            }
          }
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "cf983315-fe2a-43c1-8dc6-b17a217b845e",
      "name": "Zip-Dateien extrahieren",
      "type": "n8n-nodes-base.compression",
      "position": [
        140,
        340
      ],
      "parameters": {},
      "typeVersion": 1.1
    },
    {
      "id": "8d02dd80-d14a-4e56-ab40-f2c4a445c57b",
      "name": "Dateien als Elemente",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        300,
        340
      ],
      "parameters": {
        "include": "allOtherFields",
        "options": {},
        "fieldToSplitOut": "$binary"
      },
      "typeVersion": 1
    },
    {
      "id": "038060dc-e01d-40ae-878d-5043bc36ab91",
      "name": "PDF-Inhalte extrahieren",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        560,
        380
      ],
      "parameters": {
        "options": {},
        "operation": "pdf",
        "binaryPropertyName": "=file_{{ $itemIndex }}"
      },
      "typeVersion": 1
    },
    {
      "id": "4a85003b-b988-467b-b1cb-29206cbed879",
      "name": "Aus Kapitel extrahieren",
      "type": "n8n-nodes-base.set",
      "position": [
        740,
        380
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "d791928a-d775-48cc-9004-a92cbe2403d3",
              "name": "contents",
              "type": "array",
              "value": "={{\n  $json.text\n    .substring($json.text.search(/\\nSec\\.\\nA[0-9]{1,4}\\.[0-9]{1,5}\\.AA/), $json.text.length)\n    .split(/\\nSec\\.\\nA[0-9]{1,2}\\.[0-9]{1,2}\\.AA/g)\n    .filter(text => !text.isEmpty())\n    .map(text => {\n      const output = text.replaceAll('AA', ' ').replaceAll('\\nA', ' ');\n      const title = output.substring(0, output.indexOf('.'));\n      const content = output.substring(output.indexOf('.')+1, output.length).replaceAll('\\n', ' ').trim();\n      return { title, content };\n    })\n}}"
            },
            {
              "id": "bc06641f-0b75-4a35-8752-78803231d5d6",
              "name": "labels",
              "type": "array",
              "value": "={{\n  $json.text\n    .match(/\\nSec\\.\\nA[0-9]{1,4}\\.[0-9]{1,5}\\.AA/g)\n    .map(text => ({\n        label: text.replaceAll('AA', ' ')\n                  .replaceAll('\\nA', ' ')\n                  .replaceAll('\\n', '')\n                  .trim()\n    }))\n}}"
            }
          ]
        }
      },
      "typeVersion": 3.3
    },
    {
      "id": "ee338786-91df-4784-bd7e-f86c0e13ca26",
      "name": "Auf Abschnitte abbilden",
      "type": "n8n-nodes-base.set",
      "position": [
        740,
        520
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "60109e60-d760-45bb-be09-7cb2b5eb85bc",
              "name": "section",
              "type": "array",
              "value": "={{\n  $json.labels.map((label, idx) => ({\n    label: label.label.match(/\\d.+/)[0].replace(/\\.$/, ''),\n    title: $json.contents[idx].title,\n    content: $json.contents[idx].content,\n    chapter: $('Extract PDF Contents').first().json.info.Title,\n  }))\n}}"
            }
          ]
        }
      },
      "typeVersion": 3.3
    },
    {
      "id": "41c9899d-26d7-48af-9af2-8563ab0fb7e4",
      "name": "Workflow-Trigger ausführen",
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "position": [
        1313,
        1200
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "3a93c19b-09d9-4e38-8b0c-2008fc03f7fc",
      "name": "Mistral Embeddings abrufen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1660,
        1060
      ],
      "parameters": {
        "url": "https://api.mistral.ai/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "model",
              "value": "mistral-embed"
            },
            {
              "name": "encoding_format",
              "value": "float"
            },
            {
              "name": "input",
              "value": "={{ $json.query }}"
            }
          ]
        },
        "nodeCredentialType": "mistralCloudApi"
      },
      "credentials": {
        "mistralCloudApi": {
          "id": "EIl2QxhXAS9Hkg37",
          "name": "Mistral Cloud account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "1adc12bd-ba61-4f1a-b1f9-3f19a542e294",
      "name": "Inhaltsaufteilung @ 50k Zeichen",
      "type": "n8n-nodes-base.set",
      "position": [
        1580,
        400
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "7753a4f4-3ec2-4c05-81df-3d5e8979a478",
              "name": "=content",
              "type": "array",
              "value": "={{ new Array(Math.round($json.content.length / Math.min($json.content.length, 30000))).fill('').map((_,idx) => $json.content.substring(idx * 30000, idx * 50000 + 30000)) }}"
            }
          ]
        }
      },
      "typeVersion": 3.3
    },
    {
      "id": "ff8adce2-8f73-4a8f-b512-5aa560ca0954",
      "name": "Chunks ausgliedern",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        1580,
        580
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "content"
      },
      "typeVersion": 1
    },
    {
      "id": "5f08ce3c-240d-4c91-bb23-953866fd0361",
      "name": "Für jeden Abschnitt...",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        1400,
        280
      ],
      "parameters": {
        "options": {},
        "batchSize": 5
      },
      "typeVersion": 3
    },
    {
      "id": "6346cf67-7d93-4315-bb0d-2e016c9853b9",
      "name": "Abschnitte in Liste",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        940,
        380
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "section"
      },
      "typeVersion": 1
    },
    {
      "id": "95e34952-03e2-40e3-a245-9da8c9e1f249",
      "name": "Nur gültige Abschnitte",
      "type": "n8n-nodes-base.filter",
      "position": [
        1100,
        380
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "or",
          "conditions": [
            {
              "id": "121e8f86-2ead-47e0-8e17-52d7c6ba8265",
              "operator": {
                "type": "string",
                "operation": "notEmpty",
                "singleValue": true
              },
              "leftValue": "={{ $json.content }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2
    },
    {
      "id": "dfe1818f-93b7-4116-8a6e-dcb2e6c23fcf",
      "name": "Qdrant Search API1 nutzen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1860,
        1060
      ],
      "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 }}"
            },
            {
              "name": "with_payload",
              "value": "={{ true }}"
            }
          ]
        },
        "nodeCredentialType": "qdrantApi"
      },
      "credentials": {
        "qdrantApi": {
          "id": "NyinAS3Pgfik66w5",
          "name": "QdrantApi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "588318e6-e188-4d99-9c11-39b2f3fb1c18",
      "name": "Qdrant Scroll API nutzen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1660,
        1320
      ],
      "parameters": {
        "url": "=http://qdrant:6333/collections/texas_tax_codes/points/scroll",
        "method": "POST",
        "options": {
          "pagination": {
            "pagination": {
              "parameters": {
                "parameters": [
                  {
                    "name": "next_page_offset",
                    "type": "body",
                    "value": "={{ $response.body.result.next_page_offset }}"
                  }
                ]
              },
              "completeExpression": "={{ $response.body.result.next_page_offset === null }}",
              "paginationCompleteWhen": "other"
            }
          }
        },
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "limit",
              "value": "={{ 100 }}"
            },
            {
              "name": "with_payload",
              "value": "={{ true }}"
            },
            {
              "name": "filter",
              "value": "={{\n{\n  \"must\": [\n    ($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}}"
            }
          ]
        },
        "nodeCredentialType": "qdrantApi"
      },
      "credentials": {
        "qdrantApi": {
          "id": "NyinAS3Pgfik66w5",
          "name": "QdrantApi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "bbf01344-c60e-42b3-8d7d-2bb360876d79",
      "name": "Suchantwort abrufen",
      "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": "Notizzettel",
      "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": "Notizzettel1",
      "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": "Notizzettel2",
      "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": "NyinAS3Pgfik66w5",
          "name": "QdrantApi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "5ec16c20-eb1e-454a-8165-594d83dd8711",
      "name": "Notizzettel3",
      "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": "Notizzettel4",
      "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": "KI-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
    },
    {
      "id": "d7e7fa9e-73ba-4df3-862e-25af63d9d9b4",
      "name": "Fensterpuffer-Speicher",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        820,
        1223
      ],
      "parameters": {},
      "typeVersion": 1.2
    },
    {
      "id": "a79bdbcd-7157-470a-aadc-bd3f8a4c40d2",
      "name": "Bei Chatnachricht empfangen",
      "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": "Fensterpuffer-Speicher1",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        420,
        1223
      ],
      "parameters": {},
      "typeVersion": 1.2
    },
    {
      "id": "30f238f8-1987-4d6d-b06d-ac2106ea3734",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        700,
        1223
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "8a8490f6-5957-495c-a7af-15cec669f39c",
      "name": "1 Sekunde",
      "type": "n8n-nodes-base.wait",
      "position": [
        2160,
        660
      ],
      "webhookId": "852317f0-aadf-4658-ae44-d05e5de29302",
      "parameters": {
        "amount": 1
      },
      "executeOnce": false,
      "typeVersion": 1.1
    },
    {
      "id": "142450f5-8ec1-4ae6-b25c-df3233394d4e",
      "name": "Frage-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": "Such-Tool",
      "type": "@n8n/n8n-nodes-langchain.toolWorkflow",
      "position": [
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      "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
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      "typeVersion": 1.1
    },
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      "name": "Weiche",
      "type": "n8n-nodes-base.switch",
      "position": [
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      "parameters": {
        "rules": {
          "values": [
            {
              "outputKey": "ask_tool",
              "conditions": {
                "options": {
                  "leftValue": "",
                  "caseSensitive": true,
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                "combinator": "and",
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                    "leftValue": "={{ $json.route }}",
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              "renameOutput": true
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            {
              "outputKey": "search_tool",
              "conditions": {
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                  "typeValidation": "strict"
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                      "operation": "equals"
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                    "leftValue": "={{ $json.route }}",
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              "renameOutput": true
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        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "71441b5a-099b-49e0-a212-3087d958b38b",
      "name": "Fragenantwort abrufen",
      "type": "n8n-nodes-base.set",
      "position": [
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        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}}"
            }
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      "typeVersion": 3.3
    },
    {
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      "name": "Notizzettel5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "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": "Notizzettel6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "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
    }
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Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Experte - Finanzen, Künstliche Intelligenz

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Experte
Anzahl der Nodes38
Kategorie2
Node-Typen21
Schwierigkeitsbeschreibung

Für fortgeschrittene Benutzer, komplexe Workflows mit 16+ Nodes

Autor
Jimleuk

Jimleuk

@jimleuk

Freelance consultant based in the UK specialising in AI-powered automations. I work with select clients tackling their most challenging projects. For business enquiries, send me an email at hello@jimle.uk LinkedIn: https://www.linkedin.com/in/jimleuk/ X/Twitter: https://x.com/jimle_uk

Externe Links
Auf n8n.io ansehen

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Kategorien

Kategorien: 34