使用Qdrant、Mistral.ai和OpenAI构建税法助手

• •可能需要目标 API 的认证凭证
• •OpenAI API Key
• •Qdrant 服务器连接信息

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        "operation": "pdf",
        "binaryPropertyName": "=file_{{ $itemIndex }}"
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      "id": "4a85003b-b988-467b-b1cb-29206cbed879",
      "name": "Extract From Chapter",
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      "id": "41c9899d-26d7-48af-9af2-8563ab0fb7e4",
      "name": "Execute Workflow Trigger",
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "position": [
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      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "3a93c19b-09d9-4e38-8b0c-2008fc03f7fc",
      "name": "Get Mistral Embeddings",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
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      ],
      "parameters": {
        "url": "https://api.mistral.ai/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "model",
              "value": "mistral-embed"
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            {
              "name": "encoding_format",
              "value": "float"
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            {
              "name": "input",
              "value": "={{ $json.query }}"
            }
          ]
        },
        "nodeCredentialType": "mistralCloudApi"
      },
      "credentials": {
        "mistralCloudApi": {
          "id": "EIl2QxhXAS9Hkg37",
          "name": "Mistral Cloud account"
        }
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        "conditions": {
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            "caseSensitive": true,
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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 }}"
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        "nodeCredentialType": "qdrantApi"
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              "value": "={{ 100 }}"
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    },
    {
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      "name": "Get Search Response",
      "type": "n8n-nodes-base.set",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "assignments": {
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              "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": "NyinAS3Pgfik66w5",
          "name": "QdrantApi account"
        }
      },
      "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": [
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        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
    },
    {
      "id": "d7e7fa9e-73ba-4df3-862e-25af63d9d9b4",
      "name": "Window Buffer Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        820,
        1223
      ],
      "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": [
        700,
        1223
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "8a8490f6-5957-495c-a7af-15cec669f39c",
      "name": "1sec",
      "type": "n8n-nodes-base.wait",
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      ],
      "webhookId": "852317f0-aadf-4658-ae44-d05e5de29302",
      "parameters": {
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      "executeOnce": false,
      "typeVersion": 1.1
    },
    {
      "id": "142450f5-8ec1-4ae6-b25c-df3233394d4e",
      "name": "Ask Tool",
      "type": "@n8n/n8n-nodes-langchain.toolWorkflow",
      "position": [
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      ],
      "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": [
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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
      },
      "typeVersion": 1.1
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