Automatiser la gestion des plans de prévention en entreprise

Les plans de prévention sont indispensables pour garantir la sécurité sur site. L’automatisation permet de centraliser chaque plan, de programmer les rappels de mise à jour, de suivre la diffusion auprès des équipes et de tracer les actions réalisées. Ce système prépare les audits, limite les accidents et valorise la démarche sécurité.

				
					{
  "id": "a58HZKwcOy7lmz56",
  "meta": {
    "instanceId": "178ef8a5109fc76c716d40bcadb720c455319f7b7a3fd5a39e4f336a091f524a",
    "templateCredsSetupCompleted": true
  },
  "name": "Building RAG Chatbot for Movie Recommendations with Qdrant and Open AI",
  "tags": [],
  "nodes": [
    {
      "id": "06a34e3b-519a-4b48-afd0-4f2b51d2105d",
      "name": "When clicking u2018Test workflowu2019",
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      "position": [
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        740
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "9213003d-433f-41ab-838b-be93860261b2",
      "name": "GitHub",
      "type": "n8n-nodes-base.github",
      "position": [
        5200,
        740
      ],
      "parameters": {
        "owner": {
          "__rl": true,
          "mode": "name",
          "value": "mrscoopers"
        },
        "filePath": "Top_1000_IMDB_movies.csv",
        "resource": "file",
        "operation": "get",
        "repository": {
          "__rl": true,
          "mode": "list",
          "value": "n8n_demo",
          "cachedResultUrl": "https://github.com/mrscoopers/n8n_demo",
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        },
        "additionalParameters": {}
      },
      "credentials": {
        "githubApi": {
          "id": "VbfC0mqEq24vPIwq",
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      "typeVersion": 1
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    {
      "id": "9850d1a9-3a6f-44c0-9f9d-4d20fda0b602",
      "name": "Extract from File",
      "type": "n8n-nodes-base.extractFromFile",
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      ],
      "parameters": {
        "options": {}
      },
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    {
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      "name": "Embeddings OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        5560,
        940
      ],
      "parameters": {
        "model": "text-embedding-3-small",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "deYJUwkgL1Euu613",
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      },
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    {
      "id": "bc6dd8e5-0186-4bf9-9c60-2eab6d9b6520",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        5700,
        960
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "movie_name",
                "value": "={{ $('Extract from File').item.json['Movie Name'] }}"
              },
              {
                "name": "movie_release_date",
                "value": "={{ $('Extract from File').item.json['Year of Release'] }}"
              },
              {
                "name": "movie_description",
                "value": "={{ $('Extract from File').item.json.Description }}"
              }
            ]
          }
        },
        "jsonData": "={{ $('Extract from File').item.json.Description }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "f87ea014-fe79-444b-88ea-0c4773872b0a",
      "name": "Token Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterTokenSplitter",
      "position": [
        5700,
        1140
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "d8d28cec-c8e8-4350-9e98-cdbc6da54988",
      "name": "Qdrant Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        5600,
        740
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "qdrantCollection": {
          "__rl": true,
          "mode": "id",
          "value": "imdb"
        }
      },
      "credentials": {
        "qdrantApi": {
          "id": "Zin08PA0RdXVUKK7",
          "name": "QdrantApi n8n demo"
        }
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      "typeVersion": 1
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    {
      "id": "f86e03dc-12ea-4929-9035-4ec3cf46e300",
      "name": "When chat message received",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        4920,
        1140
      ],
      "webhookId": "71bfe0f8-227e-466b-9d07-69fd9fe4a27b",
      "parameters": {
        "options": {}
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      "typeVersion": 1.1
    },
    {
      "id": "ead23ef6-2b6b-428d-b412-b3394bff8248",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        5040,
        1340
      ],
      "parameters": {
        "model": "gpt-4o-mini",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "deYJUwkgL1Euu613",
          "name": "OpenAi account 2"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "7ab936e1-aac8-43bc-a497-f2d02c2c19e5",
      "name": "Call n8n Workflow Tool",
      "type": "@n8n/n8n-nodes-langchain.toolWorkflow",
      "position": [
        5320,
        1340
      ],
      "parameters": {
        "name": "movie_recommender",
        "schemaType": "manual",
        "workflowId": {
          "__rl": true,
          "mode": "id",
          "value": "a58HZKwcOy7lmz56"
        },
        "description": "Call this tool to get a list of recommended movies from a vector database. ",
        "inputSchema": "{n"type": "object",n"properties": {nt"positive_example": {n      "type": "string",n      "description": "A string with a movie description matching the user's positive recommendation request"n    },n    "negative_example": {n      "type": "string",n      "description": "A string with a movie description matching the user's negative anti-recommendation reuqest"n    }n}n}",
        "specifyInputSchema": true
      },
      "typeVersion": 1.2
    },
    {
      "id": "ce55f334-698b-45b1-9e12-0eaa473187d4",
      "name": "Window Buffer Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        5160,
        1340
      ],
      "parameters": {},
      "typeVersion": 1.2
    },
    {
      "id": "41c1ee11-3117-4765-98fc-e56cc6fc8fb2",
      "name": "Execute Workflow Trigger",
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "position": [
        5640,
        1600
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "db8d6ab6-8cd2-4a8c-993d-f1b7d7fdcffd",
      "name": "Merge",
      "type": "n8n-nodes-base.merge",
      "position": [
        6540,
        1500
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineAll"
      },
      "typeVersion": 3
    },
    {
      "id": "c7bc5e04-22b1-40db-ba74-1ab234e51375",
      "name": "Split Out",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        7260,
        1480
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "result"
      },
      "typeVersion": 1
    },
    {
      "id": "a2002d2e-362a-49eb-a42d-7b665ddd67a0",
      "name": "Split Out1",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        7140,
        1260
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "result.points"
      },
      "typeVersion": 1
    },
    {
      "id": "f69a87f1-bfb9-4337-9350-28d2416c1580",
      "name": "Merge1",
      "type": "n8n-nodes-base.merge",
      "position": [
        7520,
        1400
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "fieldsToMatchString": "id"
      },
      "typeVersion": 3
    },
    {
      "id": "b2f2529e-e260-4d72-88ef-09b804226004",
      "name": "Aggregate",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        7960,
        1400
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData",
        "destinationFieldName": "response"
      },
      "typeVersion": 1
    },
    {
      "id": "bedea10f-b4de-4f0e-9d60-cc8117a2b328",
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        5140,
        1140
      ],
      "parameters": {
        "options": {
          "systemMessage": "You are a Movie Recommender Tool using a Vector Database under the hood. Provide top-3 movie recommendations returned by the database, ordered by their recommendation score, but not showing the score to the user."
        }
      },
      "typeVersion": 1.6
    },
    {
      "id": "e04276b5-7d69-437b-bf4f-9717808cc8f6",
      "name": "Embedding Recommendation Request with Open AI",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        5900,
        1460
      ],
      "parameters": {
        "url": "https://api.openai.com/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "input",
              "value": "={{ $json.query.positive_example }}"
            },
            {
              "name": "model",
              "value": "text-embedding-3-small"
            }
          ]
        },
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer $OPENAI_API_KEY"
            }
          ]
        },
        "nodeCredentialType": "openAiApi"
      },
      "credentials": {
        "openAiApi": {
          "id": "deYJUwkgL1Euu613",
          "name": "OpenAi account 2"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "68e99f06-82f5-432c-8b31-8a1ae34981a6",
      "name": "Embedding Anti-Recommendation Request with Open AI",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        5920,
        1660
      ],
      "parameters": {
        "url": "https://api.openai.com/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "input",
              "value": "={{ $json.query.negative_example }}"
            },
            {
              "name": "model",
              "value": "text-embedding-3-small"
            }
          ]
        },
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer $OPENAI_API_KEY"
            }
          ]
        },
        "nodeCredentialType": "openAiApi"
      },
      "credentials": {
        "openAiApi": {
          "id": "deYJUwkgL1Euu613",
          "name": "OpenAi account 2"
        }
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      "typeVersion": 4.2
    },
    {
      "id": "ecb1d7e1-b389-48e8-a34a-176bfc923641",
      "name": "Extracting Embedding",
      "type": "n8n-nodes-base.set",
      "position": [
        6180,
        1460
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "01a28c9d-aeb1-48bb-8a73-f8bddbd73460",
              "name": "positive_example",
              "type": "array",
              "value": "={{ $json.data[0].embedding }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "4ed11142-a734-435f-9f7a-f59e2d423076",
      "name": "Extracting Embedding1",
      "type": "n8n-nodes-base.set",
      "position": [
        6180,
        1660
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "01a28c9d-aeb1-48bb-8a73-f8bddbd73460",
              "name": "negative_example",
              "type": "array",
              "value": "={{ $json.data[0].embedding }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "ce3aa9bc-a5b1-4529-bff5-e0dba43b99f3",
      "name": "Calling Qdrant Recommendation API",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        6840,
        1500
      ],
      "parameters": {
        "url": "https://edcc6735-2ffb-484f-b735-3467043828fe.europe-west3-0.gcp.cloud.qdrant.io:6333/collections/imdb_1000_open_ai/points/query",
        "method": "POST",
        "options": {},
        "jsonBody": "={n  "query": {n    "recommend": {n      "positive": [[{{ $json.positive_example }}]],n      "negative": [[{{ $json.negative_example }}]],n      "strategy": "average_vector"n    }n  },n  "limit":3n}",
        "sendBody": true,
        "specifyBody": "json",
        "authentication": "predefinedCredentialType",
        "nodeCredentialType": "qdrantApi"
      },
      "credentials": {
        "qdrantApi": {
          "id": "Zin08PA0RdXVUKK7",
          "name": "QdrantApi n8n demo"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "9b8a6bdb-16fe-4edc-86d0-136fe059a777",
      "name": "Retrieving Recommended Movies Meta Data",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        7060,
        1460
      ],
      "parameters": {
        "url": "https://edcc6735-2ffb-484f-b735-3467043828fe.europe-west3-0.gcp.cloud.qdrant.io:6333/collections/imdb_1000_open_ai/points",
        "method": "POST",
        "options": {},
        "jsonBody": "={n    "ids": ["{{ $json.result.points[0].id }}", "{{ $json.result.points[1].id }}", "{{ $json.result.points[2].id }}"],n    "with_payload":truen}",
        "sendBody": true,
        "specifyBody": "json",
        "authentication": "predefinedCredentialType",
        "nodeCredentialType": "qdrantApi"
      },
      "credentials": {
        "qdrantApi": {
          "id": "Zin08PA0RdXVUKK7",
          "name": "QdrantApi n8n demo"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "28cdcad5-3dca-48a1-b626-19eef657114c",
      "name": "Selecting Fields Relevant for Agent",
      "type": "n8n-nodes-base.set",
      "position": [
        7740,
        1400
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "b4b520a5-d0e2-4dcb-af9d-0b7748fd44d6",
              "name": "movie_recommendation_score",
              "type": "number",
              "value": "={{ $json.score }}"
            },
            {
              "id": "c9f0982e-bd4e-484b-9eab-7e69e333f706",
              "name": "movie_description",
              "type": "string",
              "value": "={{ $json.payload.content }}"
            },
            {
              "id": "7c7baf11-89cd-4695-9f37-13eca7e01163",
              "name": "movie_name",
              "type": "string",
              "value": "={{ $json.payload.metadata.movie_name }}"
            },
            {
              "id": "1d1d269e-43c7-47b0-859b-268adf2dbc21",
              "name": "movie_release_year",
              "type": "string",
              "value": "={{ $json.payload.metadata.release_year }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "56e73f01-5557-460a-9a63-01357a1b456f",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        5560,
        1780
      ],
      "parameters": {
        "content": "Tool, calling Qdrant's recommendation API based on user's request, transformed by AI agent"
      },
      "typeVersion": 1
    },
    {
      "id": "cce5250e-0285-4fd0-857f-4b117151cd8b",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        4680,
        720
      ],
      "parameters": {
        "content": "Uploading data (movies and their descriptions) to Qdrant Vector Storen"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {
    "Execute Workflow Trigger": [
      {
        "json": {
          "query": {
            "negative_example": "horror bloody movie",
            "positive_example": "romantic comedy"
          }
        }
      }
    ]
  },
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "40d3669b-d333-435f-99fc-db623deda2cb",
  "connections": {
    "Merge": {
      "main": [
        [
          {
            "node": "Calling Qdrant Recommendation API",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "GitHub": {
      "main": [
        [
          {
            "node": "Extract from File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Merge1": {
      "main": [
        [
          {
            "node": "Selecting Fields Relevant for Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Split Out": {
      "main": [
        [
          {
            "node": "Merge1",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Split Out1": {
      "main": [
        [
          {
            "node": "Merge1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Token Splitter": {
      "ai_textSplitter": [
        [
          {
            "node": "Default Data Loader",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings OpenAI": {
      "ai_embedding": [
        [
          {
            "node": "Qdrant Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Extract from File": {
      "main": [
        [
          {
            "node": "Qdrant Vector Store",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Default Data Loader": {
      "ai_document": [
        [
          {
            "node": "Qdrant Vector Store",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Extracting Embedding": {
      "main": [
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Window Buffer Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Extracting Embedding1": {
      "main": [
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Call n8n Workflow Tool": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Execute Workflow Trigger": {
      "main": [
        [
          {
            "node": "Embedding Recommendation Request with Open AI",
            "type": "main",
            "index": 0
          },
          {
            "node": "Embedding Anti-Recommendation Request with Open AI",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When chat message received": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Calling Qdrant Recommendation API": {
      "main": [
        [
          {
            "node": "Retrieving Recommended Movies Meta Data",
            "type": "main",
            "index": 0
          },
          {
            "node": "Split Out1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking u2018Test workflowu2019": {
      "main": [
        [
          {
            "node": "GitHub",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Selecting Fields Relevant for Agent": {
      "main": [
        [
          {
            "node": "Aggregate",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Retrieving Recommended Movies Meta Data": {
      "main": [
        [
          {
            "node": "Split Out",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embedding Recommendation Request with Open AI": {
      "main": [
        [
          {
            "node": "Extracting Embedding",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embedding Anti-Recommendation Request with Open AI": {
      "main": [
        [
          {
            "node": "Extracting Embedding1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
				
			

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