自动化文档合规性验证

• •HTTP Webhook 端点（n8n 会自动生成）
• •可能需要目标 API 的认证凭证
• •Qdrant 服务器连接信息

{
  "meta": {
    "instanceId": "3fe077479b444bdcfece7286c569713d43d4aa028a4ec663ca89692157527a79",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "22c5f212-aeca-46d1-a684-41147efc6547",
      "name": "审计文档上传",
      "type": "n8n-nodes-base.webhook",
      "position": [
        -464,
        -272
      ],
      "webhookId": "ede6ddb4-91a5-4a3c-9f91-5600939bf5a8",
      "parameters": {
        "path": "creatorhub/audit-document-upload",
        "options": {},
        "httpMethod": "POST",
        "responseMode": "lastNode"
      },
      "typeVersion": 2
    },
    {
      "id": "bf8f5941-db69-4db3-b344-183e23b010ca",
      "name": "流程提交",
      "type": "n8n-nodes-base.webhook",
      "position": [
        -464,
        288
      ],
      "webhookId": "9bbf9e5b-1582-40c2-9324-6927f62ca31d",
      "parameters": {
        "path": "creatorhub/procedure-validate",
        "options": {},
        "httpMethod": "POST",
        "responseMode": "responseNode"
      },
      "typeVersion": 2
    },
    {
      "id": "35b34dc7-27f0-446d-b052-1bf7eb990ce2",
      "name": "获取文档（Microsoft Graph）",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -256,
        -272
      ],
      "parameters": {
        "url": "={{$env.GRAPH_BASE_URL || \"https://graph.microsoft.com\"}}/v1.0/drives/{{$json.body.spDriveId}}/items/{{$json.body.spDocumentId}}/content",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "a9520145-7f98-4f22-a477-cb24caa599b2",
      "name": "删除旧文档向量",
      "type": "@n8n/n8n-nodes-langchain.code",
      "position": [
        0,
        -272
      ],
      "parameters": {
        "code": {
          "execute": {
            "code": "const { QdrantVectorStore } = require(\"@langchain/qdrant\");\nconst { OllamaEmbeddings } = require(\"@langchain/community/embeddings/ollama\");\n\nconst OLLAMA_BASE_URL = $env.OLLAMA_BASE_URL || \"http://localhost:11434\";\nconst QDRANT_BASE_URL = $env.QDRANT_BASE_URL || \"http://localhost:6333\";\nconst QDRANT_COLLECTION = $env.QDRANT_COLLECTION || \"audit-docs\";\nconst EMBED_MODEL = $env.OLLAMA_EMBED_MODEL || \"nomic-embed-text\";\n\nconst embeddings = new OllamaEmbeddings({ model: EMBED_MODEL, baseUrl: OLLAMA_BASE_URL });\nconst vectorStore = await QdrantVectorStore.fromExistingCollection(embeddings, { url: QDRANT_BASE_URL, collectionName: QDRANT_COLLECTION });\n\nconst items = this.getInputData();\nconst fileIdToDelete = items[0].json.body.spDocumentId;\n\nconst filter = { must: [ { key: \"metadata.file_id\", match: { value: fileIdToDelete } } ] };\n\ntry {\n  if (vectorStore?.client?.delete) {\n    await vectorStore.client.delete(QDRANT_COLLECTION, { filter });\n  }\n} catch (e) {\n  // Non-fatal: continue import/index even if delete fails\n  this.logger?.warn?.(`Qdrant delete skipped/failed: ${e?.message || e}`);\n}\n\nreturn items.map(item => ({ json: { ...item.json, file_id: fileIdToDelete }, binary: item.binary }));"
          }
        },
        "inputs": {
          "input": [
            {
              "type": "main",
              "required": true
            }
          ]
        },
        "outputs": {
          "output": [
            {
              "type": "main"
            }
          ]
        }
      },
      "typeVersion": 1,
      "alwaysOutputData": false
    },
    {
      "id": "a0be08c7-54b0-41ad-9b8a-326601c0e6b8",
      "name": "提取PDF文本",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        416,
        -272
      ],
      "parameters": {
        "options": {},
        "operation": "pdf",
        "binaryPropertyName": "=data"
      },
      "executeOnce": true,
      "typeVersion": 1,
      "alwaysOutputData": true
    },
    {
      "id": "c8a629c8-80d6-484f-ade6-e3a969c1a353",
      "name": "生成文档嵌入",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
      "position": [
        560,
        -80
      ],
      "parameters": {
        "model": "={{ $env.OLLAMA_EMBED_MODEL || \"nomic-embed-text:latest\" }}"
      },
      "credentials": {
        "ollamaApi": {
          "id": "FLDXCk6C8NH00TJu",
          "name": "Ollama account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0e2b9829-03bf-4dfb-b557-94d79f13c5d7",
      "name": "将向量插入 Qdrant",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        656,
        -272
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "qdrantCollection": {
          "__rl": true,
          "mode": "list",
          "value": "={{ $env.QDRANT_COLLECTION || \"audit-docs\" }}",
          "cachedResultName": "audit-docs"
        }
      },
      "credentials": {
        "qdrantApi": {
          "id": "efX2OG1ibQmRYvUA",
          "name": "QdrantApi account"
        }
      },
      "typeVersion": 1.3
    },
    {
      "id": "250e006a-d815-475e-a0f6-daa88c0b2a71",
      "name": "加载文档元数据",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        768,
        -96
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "documentId",
                "value": "={{ $('Delete Old Document Vectors').item.json.body.spDocumentId }}"
              },
              {
                "name": "documentName",
                "value": "={{ $('Delete Old Document Vectors').item.json.body.fileName }}"
              }
            ]
          }
        },
        "textSplittingMode": "custom"
      },
      "typeVersion": 1.1
    },
    {
      "id": "53151c0a-7fbe-4a35-a9a9-9d082842f05f",
      "name": "将文本分割成块",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        880,
        48
      ],
      "parameters": {
        "options": {},
        "chunkOverlap": 10
      },
      "typeVersion": 1
    },
    {
      "id": "1970eb10-01aa-4108-b686-47e6fa955cf8",
      "name": "格式化流程负载",
      "type": "n8n-nodes-base.code",
      "position": [
        -224,
        288
      ],
      "parameters": {
        "jsCode": "const {procedures, spDocumentId, description} = $input.first().json.body;\nconst result = procedures.map(procedure => ({ json: { spDocumentId, procedure, description } }));\nreturn result;"
      },
      "typeVersion": 2
    },
    {
      "id": "a9d11ff6-6cf0-4efa-a120-b7d86ecb48fa",
      "name": "AI 合规验证器",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        112,
        288
      ],
      "parameters": {
        "text": "=# Role\nYou are an expert internal auditor with extensive experience in compliance analysis, document review, and gap identification. Your analytical skills, attention to detail, and ability to extract relevant information from complex documents are unmatched in the industry.\n\n# Inputs\n\n**Procedure**\n{{ $json.procedure }}\n \n**spDocumentId**\n{{ $json.spDocumentId }}\n \n**description**\n{{ $json.description }}\n\n# Task\nAnalyze the provided procedure and related documents by following these steps:\n\n1. Carefully review the procedure and description text to understand all requirements and compliance standards.\n2. With the spDocumentId passed in, generate effective search queries based on key requirements in the procedure.\n3. Use these queries to retrieve relevant text from the Qdrant datastore that relates to compliance requirements.\n4. Systematically analyze the retrieved documents to:\n   - Identify sections that meet the procedure's requirements\n   - Identify gaps where requirements are not met\n   - Document specific citations for both compliant and non-compliant findings\n5. Organize your findings into a structured JSON response with clear summaries and supporting evidence.\n6. Assign an appropriate confidence level to your analysis based on the quality and relevance of the evidence found.\n\n# Specifics\n- This compliance analysis is critically important to our organization's regulatory standing, and your thorough evaluation will directly impact our business operations.\n- When generating search queries, focus on specific requirements, standards, and action items mentioned in the procedure.\n- For each compliance or non-compliance finding, provide specific text citations including page numbers or section references.\n- Your expertise in identifying subtle compliance gaps is greatly valued and will help protect our organization from potential regulatory issues.\n- If certain requirements have no corresponding evidence in the documents, clearly indicate this as a gap in the non-compliance summary.\n- Ensure your confidence level accurately reflects the strength of evidence found in the documents.\n\n# Context\nYou are conducting an internal audit for a regulated organization that must demonstrate compliance with specific procedures. The Qdrant vector datastore contains the full text of all relevant documents that need to be evaluated against the procedure requirements. Your analysis will be used by compliance officers and management to address any gaps and prepare for potential external audits. The procedure document contains the standards against which all other documents must be measured, and your task is to determine whether these standards are being met based on the evidence in the documents.\n\n# Examples\n## Example 1\nQ:\n{\n  \"output\": {\n    \"procedure\": \"Analyze financial and operational highlights, identify key issues, and develop strategic recommendations.\",\n    \"spDocumentId\": \"SP123456\",\n    \"confidenceLevel\": 40,\n    \"summaryOfCompliance\": \"The meeting transcript provided detailed insights into Apollo's financial performance and operational strategies. The summary of compliance includes a thorough analysis of sales trends, pricing adjustments, R&D projects, cost-saving measures, marketing efforts, and legal considerations.\",\n    \"summaryOfNonCompliance\": \"There are no specific non-compliances noted in the provided transcript; however, potential risks such as market research gaps, cost-cutting strategies impacting innovation, and pending litigation pose challenges that need to be addressed.\",\n    \"supportingTextCitations\": \"Based on the meeting transcript, key financial highlights include decreased sales of premium shoes, increased product prices by approximately 10%, cessation of the Phoneshoe project, labor reallocation, reduced postage and phone expenses, Superbowl commercial costs increase, and pending litigation.\"\n  }\n}\n\n## Example 2\nQ:\n[\n  {\n    \"output\": {\n      \"procedure\": \"Implement all recommendations from Charter for Corporate Responsibility in Environmental Protection (CREP) related to cement plants.\",\n      \"spDocumentId\": \"SP-DOC-00123\",\n      \"confidenceLevel\": 40,\n      \"summaryOfCompliance\": \"All commitments made during the Public Hearing on July 18, 2012, will be satisfactorily implemented. A separate budget has been allocated for this purpose and progress reports will be submitted to the Ministry's Regional Office in Bangalore.\",\n      \"summaryOfNonCompliance\": \"None were found.\",\n      \"supportingTextCitations\": \"citation on page 3\"\n    }\n  }\n]\n\n# Notes\n- Return only a structured JSON response matching the required schema.\n- If any fields would be empty, provide \"No Additional Feedback\" as the value.\n- Place special emphasis on the accuracy of citations to ensure traceability of your findings.\n- Ensure your confidence level (0-100) accurately reflects the quality and completeness of evidence found.\n- Remember that both compliance and non-compliance findings are equally important for a comprehensive audit.",
        "options": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "executeOnce": false,
      "typeVersion": 2.1
    },
    {
      "id": "d2cef8a0-0e15-4e06-9c5c-3eae0aa2fc93",
      "name": "语言模型（AI 代理）",
      "type": "@n8n/n8n-nodes-langchain.lmChatOllama",
      "position": [
        16,
        496
      ],
      "parameters": {
        "model": "={{ $env.OLLAMA_CHAT_MODEL || \"qwen2.5:7b\" }}",
        "options": {
          "numCtx": 2048
        }
      },
      "credentials": {
        "ollamaApi": {
          "id": "FLDXCk6C8NH00TJu",
          "name": "Ollama account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "26ff7b08-8fd3-4ea6-baee-ca215382cffb",
      "name": "检索相关文档块",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        192,
        496
      ],
      "parameters": {
        "mode": "retrieve-as-tool",
        "topK": 8,
        "options": {
          "searchFilterJson": "={\n  \"should\": [\n    {\n      \"key\": \"metadata.documentId\",\n      \"match\": { \"value\": \"{{ $('Format Procedure Payload').first().json.spDocumentId }}\" }\n    }\n  ]\n}"
        },
        "toolDescription": "Query document text from uploaded documents.",
        "qdrantCollection": {
          "__rl": true,
          "mode": "list",
          "value": "={{ $env.QDRANT_COLLECTION || \"audit-docs\" }}",
          "cachedResultName": "audit-docs"
        }
      },
      "credentials": {
        "qdrantApi": {
          "id": "efX2OG1ibQmRYvUA",
          "name": "QdrantApi account"
        }
      },
      "typeVersion": 1.3
    },
    {
      "id": "b5f941e6-699f-4146-9ac5-98881a6e350c",
      "name": "生成查询嵌入",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
      "position": [
        256,
        640
      ],
      "parameters": {
        "model": "={{ $env.OLLAMA_EMBED_MODEL || \"nomic-embed-text:latest\" }}"
      },
      "credentials": {
        "ollamaApi": {
          "id": "FLDXCk6C8NH00TJu",
          "name": "Ollama account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0f05420f-46ff-4388-9ac4-1873769b27fa",
      "name": "语言模型（结构化输出）",
      "type": "@n8n/n8n-nodes-langchain.lmChatOllama",
      "position": [
        560,
        640
      ],
      "parameters": {
        "model": "={{ $env.OLLAMA_CHAT_MODEL || \"qwen2.5:7b\" }}",
        "options": {}
      },
      "credentials": {
        "ollamaApi": {
          "id": "FLDXCk6C8NH00TJu",
          "name": "Ollama account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "cc4d8ab4-4fb6-43e1-bac2-608d7cde44b9",
      "name": "解析AI响应",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        496,
        496
      ],
      "parameters": {
        "autoFix": true,
        "schemaType": "manual",
        "inputSchema": "{\n  \"type\": \"object\",\n  \"required\": [\"confidenceLevel\",\"summaryOfCompliance\",\"summaryOfNonCompliance\",\"supportingTextCitations\"],\n  \"properties\": {\n    \"procedure\": {\"type\": \"string\"},\n    \"spDocumentId\": {\"type\": \"string\"},\n    \"confidenceLevel\": {\"type\": \"integer\"},\n    \"summaryOfCompliance\": {\"type\": \"string\"},\n    \"summaryOfNonCompliance\": {\"type\": \"string\"},\n    \"supportingTextCitations\": {\"type\": \"string\"}\n  }\n}"
      },
      "typeVersion": 1.3
    },
    {
      "id": "d67b5769-ef38-4e94-b0eb-9052c43dd113",
      "name": "返回合规报告",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        608,
        288
      ],
      "parameters": {
        "options": {},
        "respondWith": "allIncomingItems"
      },
      "typeVersion": 1.4
    },
    {
      "id": "a07e2a08-6304-4abf-81b0-d2ab0ae90c5d",
      "name": "便签",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -464,
        -480
      ],
      "parameters": {
        "content": "### 1. 开始：上传文档"
      },
      "typeVersion": 1
    },
    {
      "id": "5bfb1299-0b6b-4c45-abce-f2c725c22581",
      "name": "便签1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -16,
        -480
      ],
      "parameters": {
        "content": "### 2. 文档预处理"
      },
      "typeVersion": 1
    },
    {
      "id": "3b49fd17-f85d-4ad4-9ad3-e8274faf9fef",
      "name": "便签2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -464,
        80
      ],
      "parameters": {
        "content": "### 3. 流程提交"
      },
      "typeVersion": 1
    },
    {
      "id": "cb5b5349-47d3-4c01-ac2a-ea7a9b596503",
      "name": "便签3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        96,
        80
      ],
      "parameters": {
        "content": "### 4. AI 合规验证"
      },
      "typeVersion": 1
    },
    {
      "id": "d6b8d7c6-d14d-4625-97de-ac6fdd792156",
      "name": "便签4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        576,
        80
      ],
      "parameters": {
        "content": "### 5. 返回结果"
      },
      "typeVersion": 1
    }
  ],
  "pinData": {},
  "connections": {
    "Extract PDF Text": {
      "main": [
        [
          {
            "node": "Insert Vectors into Qdrant",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Parse AI Response": {
      "ai_outputParser": [
        [
          {
            "node": "AI Compliance Validator",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Procedure Submission": {
      "main": [
        [
          {
            "node": "Format Procedure Payload",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Audit Document Upload": {
      "main": [
        [
          {
            "node": "Fetch Document (Microsoft Graph)",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Load Document Metadata": {
      "ai_document": [
        [
          {
            "node": "Insert Vectors into Qdrant",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Split Text into Chunks": {
      "ai_textSplitter": [
        [
          {
            "node": "Load Document Metadata",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "AI Compliance Validator": {
      "main": [
        [
          {
            "node": "Return Compliance Report",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Format Procedure Payload": {
      "main": [
        [
          {
            "node": "AI Compliance Validator",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Generate Query Embeddings": {
      "ai_embedding": [
        [
          {
            "node": "Retrieve Relevant Document Chunks",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Language Model (AI Agent)": {
      "ai_languageModel": [
        [
          {
            "node": "AI Compliance Validator",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Delete Old Document Vectors": {
      "main": [
        [
          {
            "node": "Extract PDF Text",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Generate Document Embeddings": {
      "ai_embedding": [
        [
          {
            "node": "Insert Vectors into Qdrant",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Fetch Document (Microsoft Graph)": {
      "main": [
        [
          {
            "node": "Delete Old Document Vectors",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Retrieve Relevant Document Chunks": {
      "ai_tool": [
        [
          {
            "node": "AI Compliance Validator",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Language Model (Structured Output)": {
      "ai_languageModel": [
        [
          {
            "node": "Parse AI Response",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}