{
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  "meta": {
    "instanceId": "178ef8a5109fc76c716d40bcadb720c455319f7b7a3fd5a39e4f336a091f524a",
    "templateCredsSetupCompleted": true
  },
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      ],
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          "mode": "name",
          "value": "mrscoopers"
        },
        "filePath": "Top_1000_IMDB_movies.csv",
        "resource": "file",
        "operation": "get",
        "repository": {
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          "mode": "list",
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        "additionalParameters": {}
      },
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        940
      ],
      "parameters": {
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      "position": [
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        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"
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      "name": "Token Splitter",
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      ],
      "parameters": {},
      "typeVersion": 1
    },
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        740
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "qdrantCollection": {
          "__rl": true,
          "mode": "id",
          "value": "imdb"
        }
      },
      "credentials": {
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          "id": "Zin08PA0RdXVUKK7",
          "name": "QdrantApi n8n demo"
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      "name": "When chat message received",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
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        1140
      ],
      "webhookId": "71bfe0f8-227e-466b-9d07-69fd9fe4a27b",
      "parameters": {
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      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        5040,
        1340
      ],
      "parameters": {
        "model": "gpt-4o-mini",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
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          "name": "OpenAi account 2"
        }
      },
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    },
    {
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      "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. ",
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        "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"
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      },
      "typeVersion": 4.2
    },
    {
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      "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": {
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        "assignments": {
          "assignments": [
            {
              "id": "01a28c9d-aeb1-48bb-8a73-f8bddbd73460",
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              "type": "array",
              "value": "={{ $json.data[0].embedding }}"
            }
          ]
        }
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      "typeVersion": 3.4
    },
    {
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      "type": "n8n-nodes-base.set",
      "position": [
        6180,
        1660
      ],
      "parameters": {
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        "assignments": {
          "assignments": [
            {
              "id": "01a28c9d-aeb1-48bb-8a73-f8bddbd73460",
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              "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
          }
        ]
      ]
    }
  }
}