Agente de actualizaciones de proyectos Slack con RAG

• •Bot Token de Slack o URL de Webhook
• •Clave de API de OpenAI
• •Clave de API de Pinecone

{
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  "meta": {
    "instanceId": "1c7b08fed4406d546caf4a44e8b942ca317e7e207bb9a5701955a1a6e1ce1843"
  },
  "name": "Slack Project Update RAG Agent",
  "tags": [],
  "nodes": [
    {
      "id": "44bc7fc6-9736-48e9-90dc-3098047abdc7",
      "name": "Slack Disparador",
      "type": "n8n-nodes-base.slackTrigger",
      "position": [
        880,
        160
      ],
      "parameters": {
        "options": {
          "userIds": "==[\"User_ID\"]"
        },
        "trigger": [
          "any_event",
          "app_mention"
        ],
        "watchWorkspace": true
      },
      "typeVersion": 1
    },
    {
      "id": "aabbb277-80f5-4316-8845-f34bce33261b",
      "name": "OpenAI Modelo de Chat",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1100,
        380
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-5",
          "cachedResultName": "gpt-5"
        },
        "options": {}
      },
      "typeVersion": 1.2
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      "name": "Memoria Simple",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
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      ],
      "parameters": {
        "sessionKey": "={{ $json.channel }}",
        "sessionIdType": "customKey"
      },
      "typeVersion": 1.3
    },
    {
      "id": "92db15e1-3228-476f-a3da-1736e8f34d53",
      "name": "Enviar un mensaje",
      "type": "n8n-nodes-base.slack",
      "position": [
        1840,
        160
      ],
      "parameters": {
        "text": "={{ $json.output }}",
        "select": "channel",
        "channelId": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $('Slack Trigger').item.json.channel }}"
        },
        "otherOptions": {
          "sendAsUser": "Jacob",
          "includeLinkToWorkflow": false
        }
      },
      "typeVersion": 2.3
    },
    {
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      "name": "Nota Adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "color": 3,
        "width": 304,
        "height": 624,
        "content": "Slack Respond as a User"
      },
      "typeVersion": 1
    },
    {
      "id": "387b6478-c255-42ba-b456-8b90d889e261",
      "name": "Nota Adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "color": 4,
        "width": 704,
        "height": 624,
        "content": "GPT-5 Agent"
      },
      "typeVersion": 1
    },
    {
      "id": "d4e0c080-fdcc-45b9-89ac-da6ff9d1de4e",
      "name": "GPT 5 Slack Agentee",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1200,
        160
      ],
      "parameters": {
        "text": "={{ $json.text }}",
        "options": {
          "systemMessage": "You are Jacob, an Engineer at Purple Unicorn IT Solutions. Respond to your members' message on Jacob's behalf on Slack. Sound friendly and natural in a typical tech working environment. \n\n##Tool\nUse the Pinecone Vector Store Tool when asked about Project Updates"
        },
        "promptType": "define"
      },
      "typeVersion": 2
    },
    {
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      "name": "Nota Adhesiva2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "color": 5,
        "height": 624,
        "content": "Slack Trigger"
      },
      "typeVersion": 1
    },
    {
      "id": "d8e65fda-3927-4404-accf-300c30ebef8e",
      "name": "Pinecone Almacén de vectores",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        1440,
        340
      ],
      "parameters": {
        "mode": "retrieve-as-tool",
        "options": {},
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "test",
          "cachedResultName": "test"
        },
        "toolDescription": "Refer to Database for Work Related Information"
      },
      "typeVersion": 1.3
    },
    {
      "id": "fe5ef41c-9496-461a-b44a-5bb34aca4967",
      "name": "Incrustaciones OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
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      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.2
    },
    {
      "id": "c11871c8-557c-42f6-ab82-f287b1178798",
      "name": "Nota Adhesiva3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        0
      ],
      "parameters": {
        "color": 2,
        "width": 752,
        "height": 1008,
        "content": "🛠 GPT-5 + Pinecone-Powered Slack Auto-Responder — Real-Time, Context-Aware Replies for IT & Engineering Teams\n\nDescription\nCut down on context-switching and keep your Slack threads moving with an AI agent that responds on your behalf, pulling real-time knowledge from a Pinecone vector database. Built for IT, DevOps, and engineering environments, this n8n workflow ensures every reply is accurate, context-aware, and instantly available—without you lifting a finger.\n\nCheck out step-by-step video build of workflows like these here:\nhttps://www.youtube.com/@automatewithmarc\n\nHow It Works\n\nSlack Listener: Triggers when you’re mentioned or messaged in relevant channels.\n\nPinecone RAG Retrieval: Pulls the most relevant technical details from your indexed documents, architecture notes, or runbooks.\n\nGPT-5 Processing: Formats the retrieved data into a clear, concise, and technically accurate reply.\n\nThread-Aware Memory: Maintains the conversation state to avoid repeating answers.\n\nSlack Send-as-User: Posts the message under your identity for seamless integration into team workflows.\n\nWhy IT Teams Will Love It\n\n📚 Always up-to-date — If your Pinecone index is refreshed with system docs, runbooks, or KB articles, the bot will always deliver the latest info.\n\n🏗 Technical context retention — Perfect for answering ongoing infrastructure or incident threads.\n\n⏱ Reduced interruption time — No more breaking focus to answer “quick questions.”\n\n🔐 Controlled outputs — Tune GPT-5 to deliver fact-based, low-fluff responses for critical environments.\n\nCommon Use Cases\n\nDevOps: Automated responses to common CI/CD, deployment, or incident queries.\n\nSupport Engineering: Pulling troubleshooting steps directly from KB entries.\n\nProject Coordination: Instant status updates pulled from sprint or release notes.\n\nPro Tips for Deployment\n\nKeep your Pinecone vector DB updated with the latest architecture diagrams, release notes, and SOPs.\n\nUse embeddings tuned for technical documentation to improve retrieval accuracy.\n\nAdd channel-specific prompts if different teams require different response styles (e.g., #devops vs #product)."
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "5a498f5f-a962-44c6-ada3-7426d2cb62c3",
  "connections": {
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            "node": "GPT 5 Slack Agente",
            "type": "ai_memory",
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        ]
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    },
    "Embeddings OpenAI": {
      "ai_embedding": [
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          {
            "node": "Pinecone Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
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    "GPT 5 Slack Agente": {
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    "Pinecone Vector Store": {
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}