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    "recentViews": 0,
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    "createdAt": "2025-07-15T08:57:36.748Z",
    "description": "This advanced Retrieval-Augmented Generation (RAG) automation template for n8n enables contextual, real-time recommendations using Slack messages as input. The workflow extracts referenced documents from Google Drive, performs semantic retrieval from Pinecone, and generates next-step advice using GPT-4o — tailored specifically for executives and knowledge workers.\n\nPerfect for AI copilots, Slack-based assistants, or CTO coaching tools, this no-code RAG implementation gives you the building blocks to combine unstructured inputs with memory-augmented intelligence.\n\n**What This Template Does**\n\n✅ Triggers from a Slack Message or Mention\nMonitors a Slack channel using a bot, capturing user input in real-time.\n🔍 Extracts Key Info from Message\nGPT-4o parses the message to identify the subject person and Google Drive link (if present).\n📥 Downloads File from Google Drive\nAutomatically fetches and extracts PDF content using the built-in extractor.\n📇 Retrieves Metadata from Google Sheets & Pinecone\n\nLooks up user ID from Google Sheets and retrieves context from Pinecone based on embeddings and reranking.\n\n🧠 Contextual Response via GPT-4o (RAG)\nCombines user data and document context to generate a single, actionable next step using a tightly scoped GPT-4o prompt.\n\n🛠️ Auto-Fixes & Structures Output\nEnsures formatted response with recommended_action, rationale, and optional risk_note.\n\n📨 Sends Final Output Back to Slack\nPosts the recommendation directly to the channel as a reply.\n\n**Required Integrations**\n\n- Slack Bot with channels:history & app_mentions:read\n- Google Drive OAuth for file fetching\n- Google Sheets for ID mapping\n- Pinecone for vector document retrieval\n- Azure OpenAI or OpenAI GPT-4o for language processing\n- (Optional) Cohere for reranking results\n\n**Ideal Use Cases**\n\n🧑‍💼 Executive coaching bots (e.g., for CTOs or founders)\n🧠 Slack-based internal AI assistants\n📄 AI-powered document summarization with memory\n💬 Actionable recommendations based on real Slack conversations\n📊 Enterprise knowledge augmentation from vector DBs\n\n**Why This Template Stands Out**\n\n1. Combines live Slack interaction, file ingestion, and Pinecone retrieval into a fully RAG-powered response system.\n2. AI prompts are carefully scoped for actionable, context-aware, and time-bound responses.\n3. No-code setup with modular components for scaling or adapting to new use cases (e.g., different roles or goals).\n",
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              "Excel",
              "xls",
              "xlsx",
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              "decoding",
              "Move Binary Data",
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              "PDF",
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              "HTML",
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              "iCal",
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              "RTF",
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              "Base64",
              "Convert"
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            "resources": {
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        ]
      },
      {
        "id": 1251,
        "icon": "file:azure.svg",
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            "subcategories": {
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            "name": "AI"
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            "name": "Langchain"
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        "icon": "file:azure.svg",
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                "Root Nodes"
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              "Language Models": [
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            }
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        "defaults": {
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            "name": "Langchain"
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        "id": 1264,
        "icon": "file:slack.svg",
        "name": "n8n-nodes-base.slackTrigger",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/trigger-nodes/n8n-nodes-base.slacktrigger/"
                }
              ],
              "credentialDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/credentials/slack/"
                }
              ]
            },
            "categories": [
              "Communication"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "Slack Trigger"
        },
        "iconData": {
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          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Slack Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 6,
            "name": "Communication"
          }
        ]
      },
      {
        "id": 1305,
        "icon": "file:cohere.svg",
        "name": "@n8n/n8n-nodes-langchain.rerankerCohere",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.rerankercohere/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Rerankers"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Reranker Cohere"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Reranker Cohere",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 42,
        "name": "Internal Wiki"
      },
      {
        "id": 48,
        "name": "AI RAG"
      }
    ],
    "image": []
  }
}