Agent CFO d'examen des dépenses

• •Clé API Airtable
• •Clé API OpenAI
• •Clé API Pinecone

{
  "id": "zA3j2ZTGRt82vwa6",
  "meta": {
    "instanceId": "84ad02d6104594179f43f1ce9cfe3a81637b2faedb57dafcb9e649b7542988db",
    "templateCredsSetupCompleted": true
  },
  "name": "CFO Expense Reviewer Agent",
  "tags": [],
  "nodes": [
    {
      "id": "7fec5e7c-abea-4caf-b8e2-718e7abc44ef",
      "name": "Surveiller les Nouvelles Demandes de Dépenses",
      "type": "n8n-nodes-base.airtableTrigger",
      "position": [
        0,
        0
      ],
      "parameters": {
        "baseId": {
          "__rl": true,
          "mode": "url",
          "value": "https://airtable.com/appjaqV0O7FkXT2qj/shrst7GnlbzMDz4te"
        },
        "tableId": {
          "__rl": true,
          "mode": "url",
          "value": "https://airtable.com/appjaqV0O7FkXT2qj/tblTAvRqVFOo5AVDF/viwEp0ssaidZOo4nl?blocks=hide"
        },
        "pollTimes": {
          "item": [
            {
              "mode": "everyHour"
            }
          ]
        },
        "triggerField": "Amount",
        "authentication": "airtableTokenApi",
        "additionalFields": {}
      },
      "credentials": {
        "airtableTokenApi": {
          "id": "OQJxQX3N8GKNxEOl",
          "name": "Airtable Personal Access Token account 2"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "8e0fa6f3-df8c-42b6-af2a-f2cfb25f1e6d",
      "name": "Agent de Vérification des Dépenses CFO",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        440,
        0
      ],
      "parameters": {
        "text": "=An employee submitted an expense:\nAmount: ${{ $json.fields.Amount }}\nSubmitted by: {{ $json.fields['Submitted By'] }}\nCategory: {{ $json.fields.Category }}\nDescription: {{ $json.fields.Description }}\nDate Submitted: {{ $json.fields['Date Submitted'] }}\nStatus: {{ $json.fields.Status }}",
        "options": {
          "systemMessage": "You are a CFO expense analysis agent. Flag suspicious expenses with the reason. When you answer try to give answer with all the given details"
        },
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.9
    },
    {
      "id": "e53c34b4-fe86-4c70-ad90-e61ec4f8c72b",
      "name": "Modèle OpenAI GPT-4",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        360,
        260
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "wYwTjEv45IzlAOAu",
          "name": "OpenAi account 2"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "a561418a-2ef0-44bb-9683-ba239d58a3af",
      "name": "Analyser la Réponse de l'Agent CFO",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        620,
        220
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"amount\": 4500,\n  \"submitted_by\": \"Alice\",\n  \"category\": \"Travel\",\n  \"description\": \"Business class flight to Tokyo\",\n  \"date_submitted\": \"2025-05-29\",\n  \"status\": \"Pending\",\n  \"decision\": \"Flagged\",\n  \"reason\": \"The amount of $4500 for a business class flight appears unusually high and requires verification against standard travel policies and previous similar expenses. Additionally, the submission date is in the future (2025), which raises concerns about the legitimacy of the expense. It is advisable to confirm the travel plans and the necessity of the business class flight for this trip.\"\n}\n"
      },
      "typeVersion": 1.2
    },
    {
      "id": "1cba2b01-faeb-44ce-97e3-b3ada02ce748",
      "name": "Stocker la Décision dans Pinecone",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        1040,
        0
      ],
      "parameters": {
        "mode": "insert",
        "options": {
          "pineconeNamespace": "={{ $json.output.decision }}"
        },
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "new",
          "cachedResultName": "new"
        }
      },
      "credentials": {
        "pineconeApi": {
          "id": "PSI5CiZnLRSkEgJg",
          "name": "PineconeApi account"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "5a80d379-907e-43c0-946e-fc82be36c288",
      "name": "Générer des Embeddings",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        980,
        240
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "wYwTjEv45IzlAOAu",
          "name": "OpenAi account 2"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "50c1a961-cc58-4b6a-bf46-da0925b617e2",
      "name": "Préparer les Données pour Pinecone",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        1180,
        220
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "2484db3c-bef8-4b0e-a324-116dc70644a9",
      "name": "Diviser le Texte de Raisonnement",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1120,
        440
      ],
      "parameters": {
        "options": {},
        "chunkSize": 100,
        "chunkOverlap": 20
      },
      "typeVersion": 1
    },
    {
      "id": "cd1a7b50-edd7-400a-8fc8-ff237492749b",
      "name": "Mettre à Jour l'Enregistrement Airtable",
      "type": "n8n-nodes-base.airtable",
      "position": [
        1680,
        0
      ],
      "parameters": {
        "base": {
          "__rl": true,
          "mode": "list",
          "value": "appjaqV0O7FkXT2qj",
          "cachedResultUrl": "https://airtable.com/appjaqV0O7FkXT2qj",
          "cachedResultName": "Table no.1"
        },
        "table": {
          "__rl": true,
          "mode": "list",
          "value": "tblTAvRqVFOo5AVDF",
          "cachedResultUrl": "https://airtable.com/appjaqV0O7FkXT2qj/tblTAvRqVFOo5AVDF",
          "cachedResultName": "Table 1"
        },
        "columns": {
          "value": {
            "id": "={{ $('Watch New Expense Requests').item.json.id }}",
            "Amount": "={{ $('CFO Expense Review Agent').item.json.output.amount }}",
            "Reason": "={{ $('CFO Expense Review Agent').item.json.output.reason }}",
            "Status": "=completed",
            "Category": "={{ $('CFO Expense Review Agent').item.json.output.category }}",
            "decision": "={{ $('CFO Expense Review Agent').item.json.output.decision }}",
            "Description": "={{ $('CFO Expense Review Agent').item.json.output.description }}",
            "Submitted By": "={{ $('CFO Expense Review Agent').item.json.output.submitted_by }}"
          },
          "schema": [
            {
              "id": "id",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": true,
              "required": false,
              "displayName": "id",
              "defaultMatch": true
            },
            {
              "id": "Amount",
              "type": "number",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "Amount",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Category",
              "type": "options",
              "display": true,
              "options": [
                {
                  "name": "Self-cleaning, keeps drinks cold for 24 hrs, BPA-free",
                  "value": "Self-cleaning, keeps drinks cold for 24 hrs, BPA-free"
                },
                {
                  "name": "Travel",
                  "value": "Travel"
                }
              ],
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "Category",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Description",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "Description",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Submitted By",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "Submitted By",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Date Submitted",
              "type": "string",
              "display": true,
              "removed": true,
              "readOnly": true,
              "required": false,
              "displayName": "Date Submitted",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Status",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "Status",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "decision",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "decision",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Reason",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "Reason",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "id"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "update"
      },
      "credentials": {
        "airtableTokenApi": {
          "id": "OQJxQX3N8GKNxEOl",
          "name": "Airtable Personal Access Token account 2"
        }
      },
      "typeVersion": 2.1
    },
    {
      "id": "a45e7430-d205-4930-9b15-b52e51139d58",
      "name": "Note Adhésive",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -100,
        -480
      ],
      "parameters": {
        "color": 2,
        "width": 340,
        "height": 680,
        "content": "## 🔁 **Section 1: Intake – Monitoring Expense Requests**\n\n### 1. **Watch New Expense Requests**\n\n**(Airtable Trigger)**\n\n* **Purpose:** Continuously monitors the Airtable `Expenses` table for new or updated entries with `Status = Pending`.\n* **What it does:** Triggers the entire workflow when a new expense is submitted or an existing one is updated for review.\n\n> 💡 Ensures real-time detection of incoming requests that need analysis."
      },
      "typeVersion": 1
    },
    {
      "id": "6d6229ee-a86b-442f-ab8e-25d44b9bbe24",
      "name": "Note Adhésive1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        320,
        -600
      ],
      "parameters": {
        "color": 6,
        "width": 500,
        "height": 1020,
        "content": "🧠 Section 2: AI Analysis – CFO Reasoning Engine\n2. CFO Expense Review Agent\n(AI Agent - Tools Agent)\n\nPurpose: Acts as a virtual CFO. It receives the expense data and reasons through the submission using a language model.\n\nConnected To: OpenAI GPT-4 Model and Structured Output Parser\n\n3. OpenAI GPT-4 Model\n(OpenAI Chat Model)\n\nPurpose: Powers the logic behind the CFO's decision-making.\n\nPrompt Format: Given structured context about the expense, it determines whether it should be flagged and explains why.\n\n4. Parse CFO Agent Response\n(Structured Output Parser)\n\nPurpose: Transforms the unstructured response from GPT into a clean JSON object.\n\nOutput: Fields like decision, reason, amount, submitted_by, category, etc., which can be used for downstream processing.\n\n🧩 This section gives intelligence to the system, allowing it to make smart and explainable decisions."
      },
      "typeVersion": 1
    },
    {
      "id": "66201323-99aa-4d5e-ab1d-afcc3951e271",
      "name": "Note Adhésive2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        920,
        -740
      ],
      "parameters": {
        "color": 7,
        "width": 580,
        "height": 1320,
        "content": "🧬 Section 3: Audit Trail – Embedding & Storage\n5. Prepare Data for Pinecone\n(Default Data Loader)\n\nPurpose: Loads the document (usually the reasoning or description) for embedding.\n\nInput: Reasoning text or metadata generated by the AI agent.\n\n6. Split Reasoning Text\n(Recursive Character Text Splitter)\n\nPurpose: Splits long reasoning content into smaller chunks (if needed) to fit OpenAI embedding limits.\n\n7. Generate Embeddings\n(Embeddings OpenAI)\n\nPurpose: Converts the textual reasoning into a vector representation using OpenAI's embedding model.\n\n8. Store Decision in Pinecone\n(Pinecone Vector Store)\n\nPurpose: Saves the embedded vector along with metadata like decision, amount, and reason.\n\nGoal: Creates a searchable, auditable archive of past decisions for future reference and pattern learning.\n\n🧾 This section builds a scalable memory system for compliance and insights over time."
      },
      "typeVersion": 1
    },
    {
      "id": "117ba355-f8cd-465d-bbe6-1b37261f4640",
      "name": "Note Adhésive3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1600,
        -340
      ],
      "parameters": {
        "color": 3,
        "width": 300,
        "height": 540,
        "content": "✅ Section 4: Output – Updating Records\n9. Update Airtable Record\n(Airtable Update Node)\n\nPurpose: Writes the final decision (Approved or Flagged) and the reasoning back to the original Airtable record.\n\nFields Updated: Status, Reason, and optionally an ReviewedAt timestamp.\n\n📥 Ensures that Airtable remains the source of truth, visibly updated with the CFO agent’s input."
      },
      "typeVersion": 1
    },
    {
      "id": "e379569e-98b3-47d6-b60d-9faa1babdf1d",
      "name": "Note Adhésive9",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1880,
        -500
      ],
      "parameters": {
        "color": 4,
        "width": 1300,
        "height": 320,
        "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
      },
      "typeVersion": 1
    },
    {
      "id": "ec9af853-11be-4651-9978-c9f2f9a120ae",
      "name": "Note Adhésive4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1880,
        -160
      ],
      "parameters": {
        "color": 4,
        "width": 1289,
        "height": 2258,
        "content": "## 📊 **CFO Expense Approval Workflow Overview**\n\nThis workflow automates the process of monitoring, analyzing, and auditing expense requests using Airtable, OpenAI, and Pinecone. It is organized into the following four sections:\n\n---\n\n## 🔁 **Section 1: Intake – Monitoring Expense Requests**\n\n### 1. **Watch New Expense Requests**\n\n**(Airtable Trigger)**\n\n* **Purpose:** Continuously monitors the Airtable `Expenses` table for new or updated entries with `Status = Pending`.\n* **What it does:** Triggers the entire workflow when a new expense is submitted or an existing one is updated for review.\n\n> 💡 Ensures real-time detection of incoming requests that need analysis.\n\n---\n\n## 🧠 **Section 2: AI Analysis – CFO Reasoning Engine**\n\n### 2. **CFO Expense Review Agent**\n\n**(AI Agent - Tools Agent)**\n\n* **Purpose:** Acts as a virtual CFO. It receives the expense data and reasons through the submission using a language model.\n* **Connected To:** OpenAI GPT-4 Model and Structured Output Parser\n\n### 3. **OpenAI GPT-4 Model**\n\n**(OpenAI Chat Model)**\n\n* **Purpose:** Powers the logic behind the CFO's decision-making.\n* **Prompt Format:** Given structured context about the expense, it determines whether it should be flagged and explains why.\n\n### 4. **Parse CFO Agent Response**\n\n**(Structured Output Parser)**\n\n* **Purpose:** Transforms the unstructured response from GPT into a clean JSON object.\n* **Output:** Fields like `decision`, `reason`, `amount`, `submitted_by`, `category`, etc., which can be used for downstream processing.\n\n> 🧩 This section gives intelligence to the system, allowing it to make smart and explainable decisions.\n\n---\n\n## 🧬 **Section 3: Audit Trail – Embedding & Storage**\n\n### 5. **Prepare Data for Pinecone**\n\n**(Default Data Loader)**\n\n* **Purpose:** Loads the document (usually the reasoning or description) for embedding.\n* **Input:** Reasoning text or metadata generated by the AI agent.\n\n### 6. **Split Reasoning Text**\n\n**(Recursive Character Text Splitter)**\n\n* **Purpose:** Splits long reasoning content into smaller chunks (if needed) to fit OpenAI embedding limits.\n\n### 7. **Generate Embeddings**\n\n**(Embeddings OpenAI)**\n\n* **Purpose:** Converts the textual reasoning into a vector representation using OpenAI's embedding model.\n\n### 8. **Store Decision in Pinecone**\n\n**(Pinecone Vector Store)**\n\n* **Purpose:** Saves the embedded vector along with metadata like decision, amount, and reason.\n* **Goal:** Creates a searchable, auditable archive of past decisions for future reference and pattern learning.\n\n> 🧾 This section builds a scalable **memory system** for compliance and insights over time.\n\n---\n\n## ✅ **Section 4: Output – Updating Records**\n\n### 9. **Update Airtable Record**\n\n**(Airtable Update Node)**\n\n* **Purpose:** Writes the final decision (`Approved` or `Flagged`) and the reasoning back to the original Airtable record.\n* **Fields Updated:** `Status`, `Reason`, and optionally an `ReviewedAt` timestamp.\n\n> 📥 Ensures that Airtable remains the **source of truth**, visibly updated with the CFO agent’s input.\n"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "40c83424-4fdd-4bd8-84fc-4418bdbaf450",
  "connections": {
    "e53c34b4-fe86-4c70-ad90-e61ec4f8c72b": {
      "ai_languageModel": [
        [
          {
            "node": "8e0fa6f3-df8c-42b6-af2a-f2cfb25f1e6d",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "5a80d379-907e-43c0-946e-fc82be36c288": {
      "ai_embedding": [
        [
          {
            "node": "1cba2b01-faeb-44ce-97e3-b3ada02ce748",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "2484db3c-bef8-4b0e-a324-116dc70644a9": {
      "ai_textSplitter": [
        [
          {
            "node": "50c1a961-cc58-4b6a-bf46-da0925b617e2",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "8e0fa6f3-df8c-42b6-af2a-f2cfb25f1e6d": {
      "main": [
        [
          {
            "node": "1cba2b01-faeb-44ce-97e3-b3ada02ce748",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "a561418a-2ef0-44bb-9683-ba239d58a3af": {
      "ai_outputParser": [
        [
          {
            "node": "8e0fa6f3-df8c-42b6-af2a-f2cfb25f1e6d",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "50c1a961-cc58-4b6a-bf46-da0925b617e2": {
      "ai_document": [
        [
          {
            "node": "1cba2b01-faeb-44ce-97e3-b3ada02ce748",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "1cba2b01-faeb-44ce-97e3-b3ada02ce748": {
      "main": [
        [
          {
            "node": "cd1a7b50-edd7-400a-8fc8-ff237492749b",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "7fec5e7c-abea-4caf-b8e2-718e7abc44ef": {
      "main": [
        [
          {
            "node": "8e0fa6f3-df8c-42b6-af2a-f2cfb25f1e6d",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}