现金核对
中级
这是一个Content Creation, Multimodal AI领域的自动化工作流，包含 15 个节点。主要使用 Code, MistralAi, ManualTrigger, MicrosoftExcel, Agent 等节点。 通过 Mistral AI 和 OpenAI GPT-4 实现发票与银行对账单核对的自动化
前置要求
- •OpenAI API Key
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"id": "n4bNr0cnmlkuN8fy",
"meta": {
"instanceId": "db1715da5f21adba44ce4ea3b08abb06cd1771e876f5ad2751fcafd78c5eb9dc",
"templateCredsSetupCompleted": true
},
"name": "现金核对",
"tags": [
{
"id": "7Hqs1zOnO1KyMmlS",
"name": "Cashreconciliation",
"createdAt": "2025-09-25T22:03:57.474Z",
"updatedAt": "2025-09-25T22:03:57.474Z"
},
{
"id": "HdENOIIKDc5O1stL",
"name": "Accountant",
"createdAt": "2025-09-25T22:04:06.515Z",
"updatedAt": "2025-09-25T22:04:06.515Z"
},
{
"id": "kAdvJMsTQvyVnrF9",
"name": "AccountReceivable",
"createdAt": "2025-09-25T22:04:25.528Z",
"updatedAt": "2025-09-25T22:04:25.528Z"
},
{
"id": "lsoR6uHgfiOrR6C6",
"name": "OrdertoCash",
"createdAt": "2025-09-25T22:04:29.775Z",
"updatedAt": "2025-09-25T22:04:29.775Z"
},
{
"id": "uKun50piys98JE3C",
"name": "Invoices",
"createdAt": "2025-09-18T00:47:51.695Z",
"updatedAt": "2025-09-18T00:47:51.695Z"
}
],
"nodes": [
{
"id": "451c356d-2215-4c59-8f92-40678b080c2b",
"name": "点击\"执行工作流\"时",
"type": "n8n-nodes-base.manualTrigger",
"position": [
224,
0
],
"parameters": {},
"typeVersion": 1
},
{
"id": "8e42332e-f1cb-41f8-a0e1-f37b6ab3e75a",
"name": "提取文本",
"type": "n8n-nodes-base.mistralAi",
"position": [
1344,
0
],
"parameters": {
"options": {
"batch": false
},
"binaryProperty": "Data"
},
"credentials": {
"mistralCloudApi": {
"id": "<Mistral OCR API KEY>",
"name": "Mistral Cloud account"
}
},
"typeVersion": 1
},
{
"id": "a8014539-db77-4ade-97c5-d42077119291",
"name": "获取银行对账单",
"type": "n8n-nodes-base.microsoftOneDrive",
"position": [
896,
0
],
"parameters": {
"fileId": "01WVQSKIIAS4II25G37JGK6QHSYCDROS76",
"operation": "get"
},
"credentials": {
"microsoftOneDriveOAuth2Api": {
"id": "<Microsoft One Drive API KEY>",
"name": "Microsoft Drive account"
}
},
"typeVersion": 1
},
{
"id": "822968f4-1066-417d-9521-d1064f511bb7",
"name": "JavaScript 代码",
"type": "n8n-nodes-base.code",
"position": [
672,
0
],
"parameters": {
"jsCode": "// n8n Code node\n// Input: 1 item that contains `json.data` array\n// Output: one item with a single JSON array erpLedger\n\nconst data = items[0].json.data; // all rows live here\n\nconst ledger = data\n .map(d => {\n const row = d.values?.[0]; // [\"Ansys\", 1, \"08-15-2025\", 5096.96]\n if (!row || row.length < 4) return null;\n\n return {\n CustomerName: row[0], // first column\n invoice_number: row[1], // second column\n invoice_due_date: row[2], // third column\n amount: Number(row[3]), // fourth column\n id: String(row[1]) // use invoice number as ID\n };\n })\n .filter(r => r !== null);\n\nreturn [\n {\n json: {\n erpLedger: ledger\n }\n }\n];\n"
},
"typeVersion": 2
},
{
"id": "3a9cc7b1-aeeb-4f5f-b61f-db5fe3dfc402",
"name": "OpenAI 聊天模型1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1568,
224
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-mini"
},
"options": {
"temperature": 0
}
},
"credentials": {
"openAiApi": {
"id": "<OPENAI API KEY>",
"name": "OpenAi account 2"
}
},
"typeVersion": 1.2
},
{
"id": "99f88b81-4e58-4a5d-a47a-67f6ba0771a4",
"name": "获取交易、匹配项、摘要",
"type": "n8n-nodes-base.code",
"position": [
1920,
0
],
"parameters": {
"jsCode": "// n8n Code node\n// Input: one item with .json.output (string containing transactions, matches, summary)\n// Output: multiple items (one per row in the reconciliation table)\n\nconst raw = $input.first().json.output;\n\n// ---------- Step 1: Parse safely ----------\nlet transactions = [];\nlet matches = [];\nlet summary = {};\n\ntry {\n // Normalize separators: replace triple dashes with blank lines\n const normalized = raw.replace(/---/g, \"\\n\\n\");\n\n // Split into JSON blocks\n const blocks = normalized\n .split(/\\n\\s*\\n/)\n .map(b => b.trim())\n .filter(Boolean);\n\n if (blocks[0]) {\n transactions = JSON.parse(blocks[0]);\n }\n if (blocks[1]) {\n matches = JSON.parse(blocks[1]);\n }\n if (blocks[2]) {\n summary = JSON.parse(blocks[2]);\n }\n} catch (e) {\n return [{\n json: { error: \"Parse failed\", message: e.message, rawStart: raw.substring(0, 200) }\n }];\n}\n\n// ---------- Step 2: Index matches by transaction_id ----------\nconst matchMap = {};\nfor (const m of matches) {\n matchMap[m.transaction_id] = {\n ...m,\n // Normalize classification fields\n unmatched_classification: m.unmatched_classification || m.classification || null\n };\n}\n\n// ---------- Step 3: Build reconciliation rows ----------\nconst rows = [];\n\nfor (const txn of transactions) {\n const m = matchMap[txn.transaction_id];\n\n if (m && Array.isArray(m.matches) && m.matches.length > 0) {\n // Matched transaction (can have multiple invoices)\n for (const match of m.matches) {\n rows.push({\n \"Bank Transaction Date\": new Date(txn.date).toLocaleDateString(\"en-US\"),\n \"Bank Transaction Description\": txn.description,\n \"Bank Amount\": txn.amount,\n \"ERP Invoice Number(s)\": match.invoice_number || null,\n \"ERP Customer Name(s)\": \"N/A\", // not provided in your JSON\n \"ERP Amount(s)\": txn.amount,\n \"Match Status\": \"Matched\",\n \"Confidence Score\": match.confidence || null,\n \"Reason\": match.reason || \"\"\n });\n }\n } else {\n // Unmatched transaction\n rows.push({\n \"Bank Transaction Date\": new Date(txn.date).toLocaleDateString(\"en-US\"),\n \"Bank Transaction Description\": txn.description,\n \"Bank Amount\": txn.amount,\n \"ERP Invoice Number(s)\": null,\n \"ERP Customer Name(s)\": \"N/A\",\n \"ERP Amount(s)\": null,\n \"Match Status\": m?.unmatched_classification || \"Unapplied\",\n \"Confidence Score\": null,\n \"Reason\": m?.reason || \"No match\"\n });\n }\n}\n\n// ---------- Step 4: Return as n8n items ----------\nreturn rows.map(r => ({ json: r }));\n"
},
"typeVersion": 2,
"alwaysOutputData": true
},
{
"id": "b9395a80-9e22-4e11-8e8e-85f558cc618f",
"name": "从非结构化文件中提取数据",
"type": "n8n-nodes-base.microsoftOneDrive",
"position": [
1120,
0
],
"parameters": {
"fileId": "={{ $json.id }}",
"operation": "download",
"binaryPropertyName": "=Data"
},
"credentials": {
"microsoftOneDriveOAuth2Api": {
"id": "<Microsoft One Drive API KEY>",
"name": "Microsoft Drive account"
}
},
"typeVersion": 1
},
{
"id": "464d6980-ee91-4509-b433-012adb2bcf88",
"name": "处理发票与银行对账单数据",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1568,
0
],
"parameters": {
"text": "=You are a cash reconciliation specialist.\n\nINPUT DATA:\n- Bank transactions (raw text): {{ $json.extractedText }}\n- ERP ledger entries (JSON): {{ JSON.stringify($('Code in JavaScript').item.json.erpLedger) }}\n\nTASKS\n1) Parse bank text into JSON rows with fields:\n [{\"date\":\"YYYY-MM-DD\",\"description\":\"string\",\"amount\":number,\"currency\":\"string\",\"transaction_id\":\"string\"}]\n2) Match each bank transaction to one or more ERP entries (keys: exact amount, date ±2 days, reference similarity).\n3) Unmatched items: classify as \"unapplied\", \"suspense\", or \"needs_review\" with reasons.\n4) For partial/one-to-many matches, propose splits with allocation amounts.\n5) Provide a summary: total_txns, total_matched, total_unmatched, reconciliation_rate_pct.\n6) Add a confidence score (0–1) and a short reason for each match/split.\n\nCONSTRAINTS\n- Return JSON ONLY. No prose, no markdown.\n- Limit candidates to top 3 per transaction by confidence.\n- If best confidence < 0.6, treat as unmatched.\n- Use transaction_id and invoice numbers from the inputs.\n\nI want the output in Tabular format\n",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2.2
},
{
"id": "84487907-0767-4877-89cf-d8ce56a9ac39",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
-432
],
"parameters": {
"color": 4,
"width": 2080,
"height": 272,
"content": "## **问题陈述**"
},
"typeVersion": 1
},
{
"id": "f02dc91c-34e1-48b5-8aca-51ad5c3001db",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
-64
],
"parameters": {
"color": 6,
"width": 736,
"height": 288,
"content": "## **价值**:"
},
"typeVersion": 1
},
{
"id": "5e1cd291-8e85-4869-ad70-f8a3958ac55b",
"name": "便签2",
"type": "n8n-nodes-base.stickyNote",
"position": [
208,
176
],
"parameters": {
"color": 4,
"width": 1312,
"height": 176,
"content": "## ***输入***:"
},
"typeVersion": 1
},
{
"id": "a45de2dd-7ee6-4fa9-a167-d22ceab156e2",
"name": "便签3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1712,
240
],
"parameters": {
"color": 4,
"width": 784,
"height": 240,
"content": "## ***AI 处理***:"
},
"typeVersion": 1
},
{
"id": "123cec6b-f238-4a07-a75f-2646c3ce0106",
"name": "便签4",
"type": "n8n-nodes-base.stickyNote",
"position": [
208,
368
],
"parameters": {
"color": 4,
"width": 1328,
"height": 496,
"content": "## ***后处理***:"
},
"typeVersion": 1
},
{
"id": "38449472-1724-44cc-aa6b-af80c8eaeb6b",
"name": "获取发票数据",
"type": "n8n-nodes-base.microsoftExcel",
"position": [
448,
0
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "{6220E30B-55BD-614F-AA73-5C275D263361}",
"cachedResultUrl": "https://netorg17303936x-my.sharepoint.com/personal/vinay_optinext_ca/_layouts/15/Doc.aspx?sourcedoc=%7B3B366271-85B1-4FF7-9FE1-BDD145027E90%7D&file=CashARData.xlsx&action=default&mobileredirect=true&DefaultItemOpen=1&activeCell=Sheet1!A1:D51",
"cachedResultName": "Table1"
},
"filters": {},
"rawData": true,
"resource": "table",
"workbook": {
"__rl": true,
"mode": "list",
"value": "01WVQSKILRMI3DXMMF65HZ7YN52FCQE7UQ",
"cachedResultUrl": "https://netorg17303936x-my.sharepoint.com/personal/vinay_optinext_ca/_layouts/15/Doc.aspx?sourcedoc=%7B3B366271-85B1-4FF7-9FE1-BDD145027E90%7D&file=CashARData.xlsx&action=default&mobileredirect=true&DefaultItemOpen=1",
"cachedResultName": "CashARData"
},
"operation": "getRows",
"returnAll": true,
"worksheet": {
"__rl": true,
"mode": "list",
"value": "{A31DAD5C-F7E0-2A4B-B868-E4B2444E9398}",
"cachedResultUrl": "https://netorg17303936x-my.sharepoint.com/personal/vinay_optinext_ca/_layouts/15/Doc.aspx?sourcedoc=%7B3B366271-85B1-4FF7-9FE1-BDD145027E90%7D&file=CashARData.xlsx&action=default&mobileredirect=true&DefaultItemOpen=1&activeCell=Sheet1!A1",
"cachedResultName": "Sheet1"
}
},
"credentials": {
"microsoftExcelOAuth2Api": {
"id": "<Microsoft Account API KEY>",
"name": "Microsoft Excel account"
}
},
"typeVersion": 2.1
},
{
"id": "7c23ec26-e63b-4dfe-b82b-79b5a892c91d",
"name": "便签5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
272
],
"parameters": {
"color": 2,
"width": 704,
"height": 176,
"content": "***可能的增强***:"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "983d50ae-2007-4b12-9645-838649f3db28",
"connections": {
"Extract text": {
"main": [
[
{
"node": "Process the Invoice Vs Bank Statement Data",
"type": "main",
"index": 0
}
]
]
},
"Get Invoice Data": {
"main": [
[
{
"node": "Code in JavaScript",
"type": "main",
"index": 0
}
]
]
},
"Code in JavaScript": {
"main": [
[
{
"node": "Get Bank Statement",
"type": "main",
"index": 0
}
]
]
},
"Get Bank Statement": {
"main": [
[
{
"node": "Extract the Data from Unstructured File",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Process the Invoice Vs Bank Statement Data",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Get Transaction, Matches, Summary": {
"main": [
[]
]
},
"When clicking ‘Execute workflow’": {
"main": [
[
{
"node": "Get Invoice Data",
"type": "main",
"index": 0
}
]
]
},
"Extract the Data from Unstructured File": {
"main": [
[
{
"node": "Extract text",
"type": "main",
"index": 0
}
]
]
},
"Process the Invoice Vs Bank Statement Data": {
"main": [
[
{
"node": "Get Transaction, Matches, Summary",
"type": "main",
"index": 0
}
]
]
}
}
}常见问题
如何使用这个工作流？
复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景？
中级 - 内容创作, 多模态 AI
需要付费吗？
本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。
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