{
  "workflow": {
    "id": 7647,
    "name": "Build a self-updating RAG system with OpenAI, Google Gemini, Qdrant and Google Drive",
    "views": 1284,
    "recentViews": 1,
    "totalViews": 1284,
    "createdAt": "2025-08-20T13:56:39.197Z",
    "description": "This workflow implements a **Retrieval-Augmented Generation (RAG) system** that integrates **Google Drive and Qdrant**.\n\nThis setup creates a powerful, **self-updating knowledge base** that provides accurate, context-aware answers to user queries.\n\n---\n\n###  Key Advantages\n\n* **Automated Knowledge Base Updates**\n  No manual intervention is required—documents in Google Drive are automatically synchronized with Qdrant.\n\n* **Efficient Search and Retrieval**\n  Vector embeddings enable fast and precise retrieval of relevant information.\n\n* **Scalable and Flexible**\n  Works with multiple documents and supports continuous growth of your dataset.\n\n* **Seamless AI Integration**\n  Combines **OpenAI embeddings** for vectorization and **Google Gemini** for high-quality natural language answers.\n\n* **Metadata-Enhanced Storage**\n  Each document stores metadata (file ID and name), making it easy to manage and track document versions.\n\n* **End-to-End RAG Pipeline**\n  From document ingestion to AI-powered Q\\&A, everything is handled inside one n8n workflow.\n\n---\n\n### **How It Works**  \nThis workflow implements a **Retrieval-Augmented Generation (RAG)** system that automatically processes, stores, and retrieves document information for AI-powered question answering. Here’s how it functions:\n\n1. **Document Processing & Vectorization**:\n   - The system monitors a specified **Google Drive folder** for new or updated files.\n   - When a file is added or modified, it is downloaded and split into manageable chunks using a **Recursive Character Text Splitter**.\n   - Each chunk is converted into vector embeddings using **OpenAI's embedding model**.\n   - These vectors, along with metadata (file ID, file name), are stored in a **Qdrant vector database**.\n\n2. **Automatic Updates**:\n   - The workflow includes a mechanism to **delete old vectors** associated with an updated file before inserting the new ones, ensuring the knowledge base remains current.\n\n3. **Query Handling & Response Generation**:\n   - When a user sends a chat message (via a chat trigger), the system:\n     - Retrieves the most relevant document chunks from **Qdrant** based on the query's semantic similarity.\n     - Uses a **Google Gemini** language model to generate a context-aware answer grounded in the retrieved documents.\n   - This provides accurate, source-based responses instead of relying solely on the AI's internal knowledge.\n\n4. **Initial Setup & Maintenance**:\n   - The workflow can be triggered manually to **create the Qdrant collection** or **clear all existing data**.\n   - It processes all existing files in the Drive folder during initial setup, populating the vector store.\n\n---\n\n### **Set Up Steps**  \nTo configure this workflow, follow these steps:\n\n**STEP 1: Create Qdrant Collection**\n- Replace `QDRANTURL` in the **\"Create collection\"** and **\"Clear collection\"** nodes with your Qdrant instance URL (e.g., `http://your-qdrant-host:6333`).\n- Replace `COLLECTION` with your desired collection name.\n- Ensure the Qdrant API credentials are correctly set in the respective HTTP Request nodes.\n\n**STEP 2: Configure Google Drive Access**\n- Set up OAuth credentials for **Google Drive** to allow the workflow to:\n  - Read files from a specific folder .\n  - Download files for processing.\n- Update the **Folder ID** in the **\"Search files\"** and **\"Update?\"** trigger nodes to point to your target Google Drive folder.\n\n**STEP 3: Set Up AI Models**\n- Configure the **OpenAI API** credentials in the **Embeddings** nodes for generating text embeddings.\n- Configure the **Google Gemini (PaLM) API** credentials in the **Google Gemini Chat Model** node for generating answers.\n\n**STEP 4: Configure Metadata**\n- The system automatically attaches metadata (`file_id`, `file_name`) to each document chunk. This is set in the **Default Data Loader** nodes.\n- This metadata is crucial for identifying the source of information and for the update mechanism.\n\n**STEP 5: Test the RAG System**\n- The workflow includes a chat trigger (**\"When chat message received\"**) for testing.\n- Send a query to test the retrieval and answer generation process.\n\n---\n### **Need help customizing?**  \n[Contact me](mailto:info@n3w.it) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).",
    "workflow": {
      "id": "Xof38WtIJ3CpwM2D",
      "meta": {
        "instanceId": "a4bfc93e975ca233ac45ed7c9227d84cf5a2329310525917adaf3312e10d5462",
        "templateCredsSetupCompleted": true
      },
      "name": "Complete RAG System with autoUpdate documents Using Qdrant",
      "tags": [],
      "nodes": [
        {
          "id": "478c24a7-6e2a-49bb-93ab-84e701b62dd6",
          "name": "When clicking ‘Test workflow’",
          "type": "n8n-nodes-base.manualTrigger",
          "position": [
            -448,
            80
          ],
          "parameters": {},
          "typeVersion": 1
        },
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          "id": "414f3285-3ecb-4ea3-b4f3-b397112da952",
          "name": "Embeddings OpenAI1",
          "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
          "position": [
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          ],
          "parameters": {
            "options": {}
          },
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            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
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          "name": "Default Data Loader1",
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          ],
          "parameters": {
            "options": {
              "metadata": {
                "metadataValues": [
                  {
                    "name": "file_id",
                    "value": "={{ $('Get files').item.json.id }}"
                  },
                  {
                    "name": "file_name",
                    "value": "={{ $('Get files').item.json.name }}"
                  }
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              }
            },
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            "binaryMode": "specificField"
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          "name": "Create collection",
          "type": "n8n-nodes-base.httpRequest",
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          ],
          "parameters": {
            "url": "http:///collections/test_sparse",
            "method": "PUT",
            "options": {},
            "jsonBody": "{\n  \"vectors\": {\n    \"size\": 1536,\n    \"distance\": \"Cosine\"  \n  },\n  \"sparse_vectors\": {\n        \"text\": { }\n  },\n  \"shard_number\": 1,  \n  \"replication_factor\": 1,  \n  \"write_consistency_factor\": 1 \n}",
            "sendBody": true,
            "sendHeaders": true,
            "specifyBody": "json",
            "authentication": "genericCredentialType",
            "genericAuthType": "httpHeaderAuth",
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                  "value": "application/json"
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              "name": "httpHeaderAuth Credential"
            }
          },
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        },
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            1088,
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          ],
          "parameters": {
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            "chunkOverlap": 50
          },
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        },
        {
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          "name": "Loop Over Items",
          "type": "n8n-nodes-base.splitInBatches",
          "position": [
            432,
            224
          ],
          "parameters": {
            "options": {}
          },
          "typeVersion": 3
        },
        {
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          "name": "Embeddings OpenAI2",
          "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
          "position": [
            512,
            1424
          ],
          "parameters": {
            "options": {}
          },
          "credentials": {
            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
          "typeVersion": 1.1
        },
        {
          "id": "8500aecb-a176-4d7b-98d4-790235fab977",
          "name": "Default Data Loader",
          "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
          "position": [
            640,
            1424
          ],
          "parameters": {
            "options": {
              "metadata": {
                "metadataValues": [
                  {
                    "name": "file_id",
                    "value": "={{ $('Get file').item.json.file_id }}"
                  },
                  {
                    "name": "file_name",
                    "value": "={{ $binary.data.fileName}}"
                  }
                ]
              }
            },
            "dataType": "binary",
            "binaryMode": "specificField"
          },
          "typeVersion": 1
        },
        {
          "id": "a3212d21-f3ba-4970-b7d4-cdcf91cde2ff",
          "name": "Recursive Character Text Splitter1",
          "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
          "position": [
            624,
            1632
          ],
          "parameters": {
            "options": {},
            "chunkSize": 500,
            "chunkOverlap": 50
          },
          "typeVersion": 1
        },
        {
          "id": "0561d614-e10f-40ff-8d2a-eb92f23ffd73",
          "name": "Set file_id",
          "type": "n8n-nodes-base.set",
          "position": [
            -96,
            880
          ],
          "parameters": {
            "options": {},
            "assignments": {
              "assignments": [
                {
                  "id": "b413a226-0641-4ed8-9951-d17b6a6a9a4b",
                  "name": "file_id",
                  "type": "string",
                  "value": "={{ $json.id }}"
                }
              ]
            }
          },
          "typeVersion": 3.4
        },
        {
          "id": "ce097e48-8cb4-4bb8-a717-1213c6134b42",
          "name": "Clear collection",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
            -144,
            224
          ],
          "parameters": {
            "url": "http:/YOUR_AWS_SECRET_KEY_HERE/delete",
            "method": "POST",
            "options": {},
            "jsonBody": "{\n  \"filter\": {}\n}",
            "sendBody": true,
            "sendHeaders": true,
            "specifyBody": "json",
            "authentication": "genericCredentialType",
            "genericAuthType": "httpHeaderAuth",
            "headerParameters": {
              "parameters": [
                {
                  "name": "Content-Type",
                  "value": "application/json"
                }
              ]
            }
          },
          "credentials": {
            "httpHeaderAuth": {
              "id": "credential-id",
              "name": "httpHeaderAuth Credential"
            }
          },
          "typeVersion": 4.2
        },
        {
          "id": "95ec291c-c9d9-42ef-945d-d06bcd6560c0",
          "name": "Delete points by file_id",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
            304,
            768
          ],
          "parameters": {
            "url": "http:/YOUR_AWS_SECRET_KEY_HERE/delete",
            "method": "POST",
            "options": {},
            "jsonBody": "={\n  \"filter\": {\n    \"must\": [\n      {\n          \"key\": \"metadata.file_id\",\n          \"match\": { \"value\": \"{{$json.file_id}}\" }\n        }\n    ]\n  }\n}",
            "sendBody": true,
            "sendHeaders": true,
            "specifyBody": "json",
            "authentication": "genericCredentialType",
            "genericAuthType": "httpHeaderAuth",
            "headerParameters": {
              "parameters": [
                {
                  "name": "Content-Type",
                  "value": "application/json"
                }
              ]
            }
          },
          "credentials": {
            "httpHeaderAuth": {
              "id": "credential-id",
              "name": "httpHeaderAuth Credential"
            }
          },
          "typeVersion": 4.2
        },
        {
          "id": "eb5dbda9-f67f-4d45-b4a3-fac167d4aef2",
          "name": "Search files",
          "type": "n8n-nodes-base.googleDrive",
          "position": [
            128,
            224
          ],
          "parameters": {
            "filter": {
              "driveId": {
                "__rl": true,
                "mode": "list",
                "value": "My Drive",
                "cachedResultUrl": "https://drive.google.com/drive/my-drive",
                "cachedResultName": "My Drive"
              },
              "folderId": {
                "__rl": true,
                "mode": "list",
                "value": "1RO5ByPhq2yvYLmbapTNC_kKdU5lZd4W5",
                "cachedResultUrl": "https://drive.google.com/drive/folders/1RO5ByPhq2yvYLmbapTNC_kKdU5lZd4W5",
                "cachedResultName": "Test Negozio"
              }
            },
            "options": {},
            "resource": "fileFolder"
          },
          "credentials": {
            "googleDriveOAuth2Api": {
              "id": "credential-id",
              "name": "googleDriveOAuth2Api Credential"
            }
          },
          "typeVersion": 3
        },
        {
          "id": "a7a0d544-45f5-4f18-8b45-8b0bbdc47c5b",
          "name": "Wait 5 sec.",
          "type": "n8n-nodes-base.wait",
          "position": [
            1392,
            240
          ],
          "webhookId": "138d379f-88a5-44a1-b45b-1595a05a1eb9",
          "parameters": {},
          "typeVersion": 1.1
        },
        {
          "id": "7790b835-3dde-4b59-b0fe-e3afec02eae8",
          "name": "Update file",
          "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
          "position": [
            544,
            1232
          ],
          "parameters": {
            "mode": "insert",
            "options": {},
            "qdrantCollection": {
              "__rl": true,
              "mode": "list",
              "value": "negozio-emporio-verde",
              "cachedResultName": "negozio-emporio-verde"
            }
          },
          "credentials": {
            "qdrantApi": {
              "id": "credential-id",
              "name": "qdrantApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "bf7ccb97-52a4-4d8e-87a2-f3f3de6ac6d3",
          "name": "Insert file",
          "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
          "position": [
            1008,
            240
          ],
          "parameters": {
            "mode": "insert",
            "options": {},
            "qdrantCollection": {
              "__rl": true,
              "mode": "list",
              "value": "negozio-emporio-verde",
              "cachedResultName": "negozio-emporio-verde"
            }
          },
          "credentials": {
            "qdrantApi": {
              "id": "credential-id",
              "name": "qdrantApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "d65cd402-d2ae-443d-91d0-c5b4979789df",
          "name": "Get file",
          "type": "n8n-nodes-base.googleDrive",
          "position": [
            304,
            1232
          ],
          "parameters": {
            "fileId": {
              "__rl": true,
              "mode": "id",
              "value": "={{ $json.file_id }}"
            },
            "options": {
              "googleFileConversion": {
                "conversion": {
                  "docsToFormat": "text/plain"
                }
              }
            },
            "operation": "download"
          },
          "credentials": {
            "googleDriveOAuth2Api": {
              "id": "credential-id",
              "name": "googleDriveOAuth2Api Credential"
            }
          },
          "typeVersion": 3
        },
        {
          "id": "c0214dc1-ee28-40b3-a043-b1cc3465dd7b",
          "name": "Get files",
          "type": "n8n-nodes-base.googleDrive",
          "position": [
            704,
            240
          ],
          "parameters": {
            "fileId": {
              "__rl": true,
              "mode": "id",
              "value": "={{ $json.id }}"
            },
            "options": {
              "googleFileConversion": {
                "conversion": {
                  "docsToFormat": "text/plain"
                }
              }
            },
            "operation": "download"
          },
          "credentials": {
            "googleDriveOAuth2Api": {
              "id": "credential-id",
              "name": "googleDriveOAuth2Api Credential"
            }
          },
          "typeVersion": 3
        },
        {
          "id": "970e5ac0-51c9-4300-82a9-4420f152db06",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -480,
            -416
          ],
          "parameters": {
            "color": 3,
            "width": 840,
            "height": 220,
            "content": "## Complete RAG System with autoUpdate documents Using Qdrant\n\nThis workflow implements a **Retrieval-Augmented Generation (RAG)** system that:\n\n* Stores vectorized documents in **Qdrant**,\n* Retrieves relevant content based on user input,\n* Generates AI answers using **Google Gemini**,\n* Automatically **update documents** (from Google Drive).\n"
          },
          "typeVersion": 1
        },
        {
          "id": "12c6fa79-4b60-45df-a39f-61b8dd834fe8",
          "name": "When chat message received",
          "type": "@n8n/n8n-nodes-langchain.chatTrigger",
          "position": [
            -384,
            1984
          ],
          "webhookId": "c9460030-9e23-41c4-9fcd-6c4c7fadf784",
          "parameters": {
            "options": {}
          },
          "typeVersion": 1.1
        },
        {
          "id": "28373f4f-28b2-49c6-9253-173e33039ea1",
          "name": "Question and Answer Chain",
          "type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
          "position": [
            -64,
            1984
          ],
          "parameters": {
            "options": {}
          },
          "typeVersion": 1.5
        },
        {
          "id": "c126a969-d3ab-4e1f-847d-3366c56134f3",
          "name": "Google Gemini Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
            -176,
            2224
          ],
          "parameters": {
            "options": {},
            "modelName": "models/gemini-1.5-flash"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "5398d1f7-cf4f-4355-bce4-255b48d4d4ea",
          "name": "Vector Store Retriever",
          "type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
          "position": [
            64,
            2272
          ],
          "parameters": {
            "topK": 5
          },
          "typeVersion": 1
        },
        {
          "id": "1c7614d0-6067-4dca-bbd4-e35e52f44374",
          "name": "Qdrant Vector Store1",
          "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
          "position": [
            -64,
            2480
          ],
          "parameters": {
            "options": {},
            "qdrantCollection": {
              "__rl": true,
              "mode": "list",
              "value": "negozio-emporio-verde",
              "cachedResultName": "negozio-emporio-verde"
            }
          },
          "credentials": {
            "qdrantApi": {
              "id": "credential-id",
              "name": "qdrantApi Credential"
            }
          },
          "typeVersion": 1.1
        },
        {
          "id": "21bb9ac3-4a70-477f-a404-df90328bff53",
          "name": "Embeddings OpenAI",
          "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
          "position": [
            -64,
            2672
          ],
          "parameters": {
            "options": {}
          },
          "credentials": {
            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
          "typeVersion": 1.2
        },
        {
          "id": "01922882-5a91-4a0d-b13d-59528467b89b",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1408,
            480
          ],
          "parameters": {
            "width": 520,
            "height": 420,
            "content": "Set as metadata:\n- FILE_ID from Google Drive\n- FILE_NAME from Google Drive\n\n```\n{\n  \"source\": \"blob\",\n  \"blobType\": \"text/plain\",\n  \"loc\": {\n    \"lines\": {\n      \"from\": 1,\n      \"to\": 15\n    }\n  },\n  \"file_id\": \"xxxxxxxxxxxxxxxxxxxxxxxxxx\",\n  \"file_name\": \"FAQ\"\n}\n```\n\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "2f6b7fd1-5545-46cc-a7e3-7b3c4de52e0c",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -240,
            144
          ],
          "parameters": {
            "color": 4,
            "width": 540,
            "height": 460,
            "content": "# STEP 2\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## Documents vectorization with Qdrant and Google Drive\nChange:\n- QDRANTURL\n- COLLECTION"
          },
          "typeVersion": 1
        },
        {
          "id": "c551c56f-e43d-45dd-922e-da0858008486",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            80,
            -128
          ],
          "parameters": {
            "color": 6,
            "width": 880,
            "height": 220,
            "content": "# STEP 1\n\n## Create Qdrant Collection\nChange:\n- QDRANTURL\n- COLLECTION"
          },
          "typeVersion": 1
        },
        {
          "id": "75d45205-087b-433f-b049-71dcb96ea750",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            928,
            1392
          ],
          "parameters": {
            "width": 520,
            "height": 420,
            "content": "Set as metadata:\n- FILE_ID from Google Drive\n- FILE_NAME from Google Drive\n\n```\n{\n  \"source\": \"blob\",\n  \"blobType\": \"text/plain\",\n  \"loc\": {\n    \"lines\": {\n      \"from\": 1,\n      \"to\": 15\n    }\n  },\n  \"file_id\": \"xxxxxxxxxxxxxxxxxxxxxxxxxx\",\n  \"file_name\": \"FAQ\"\n}\n```\n\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "6fa1eb40-51ec-41c2-aa67-620152e0ba6f",
          "name": "Update?",
          "type": "n8n-nodes-base.googleDriveTrigger",
          "position": [
            -416,
            880
          ],
          "parameters": {
            "event": "fileUpdated",
            "options": {
              "fileType": "all"
            },
            "pollTimes": {
              "item": [
                {
                  "mode": "everyHour"
                }
              ]
            },
            "triggerOn": "specificFolder",
            "folderToWatch": {
              "__rl": true,
              "mode": "list",
              "value": "1RO5ByPhq2yvYLmbapTNC_kKdU5lZd4W5",
              "cachedResultUrl": "https://drive.google.com/drive/folders/1RO5ByPhq2yvYLmbapTNC_kKdU5lZd4W5",
              "cachedResultName": "Test Negozio"
            }
          },
          "credentials": {
            "googleDriveOAuth2Api": {
              "id": "credential-id",
              "name": "googleDriveOAuth2Api Credential"
            }
          },
          "typeVersion": 1
        },
        {
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            "name": "AI"
          },
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            "id": 26,
            "name": "Langchain"
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            ],
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              "Vector Stores": [
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              ]
            }
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                "Root Nodes"
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              "Language Models": [
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        "id": 48,
        "name": "AI RAG"
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        "id": 51,
        "name": "Multimodal AI"
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    "image": []
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}