AI Discord Chatbot with Gemini Memory

The workflow JSON

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{
  "updatedAt": "2025-11-30T16:31:04.000Z",
  "createdAt": "2025-11-08T03:20:00.410Z",
  "id": "l0jFI8iMRjovFIVd",
  "name": "TA",
  "active": true,
  "isArchived": false,
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "10e4c630-6bce-4038-8777-916fba8bdc28",
        "options": {}
      },
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2.1,
      "position": [
        0,
        0
      ],
      "id": "2b5ed276-ef18-41bb-9ceb-869ea7b2a8ac",
      "name": "Webhook"
    },
    {
      "parameters": {
        "rules": {
          "values": [
            {
              "conditions": {
                "options": {
                  "caseSensitive": true,
                  "leftValue": "",
                  "typeValidation": "strict",
                  "version": 2
                },
                "conditions": [
                  {
                    "leftValue": "={{ $json.body.type }}",
                    "rightValue": "attacker-session",
                    "operator": {
                      "type": "string",
                      "operation": "equals"
                    },
                    "id": "5eee27fb-395e-4528-a930-dc591aa335de"
                  }
                ],
                "combinator": "and"
              },
              "renameOutput": true,
              "outputKey": "Attacker Session"
            },
            {
              "conditions": {
                "options": {
                  "caseSensitive": true,
                  "leftValue": "",
                  "typeValidation": "strict",
                  "version": 2
                },
                "conditions": [
                  {
                    "id": "69852c71-48a5-41c9-8622-41667f97cef1",
                    "leftValue": "={{ $json.body.type }}",
                    "rightValue": "attacker-behavior",
                    "operator": {
                      "type": "string",
                      "operation": "equals",
                      "name": "filter.operator.equals"
                    }
                  }
                ],
                "combinator": "and"
              },
              "renameOutput": true,
              "outputKey": "Attacker Behavior"
            }
          ]
        },
        "options": {}
      },
      "type": "n8n-nodes-base.switch",
      "typeVersion": 3.3,
      "position": [
        208,
        0
      ],
      "id": "58623537-576a-465d-ac2a-78a0479f0e2c",
      "name": "Switch"
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.body }}",
        "hasOutputParser": true,
        "options": {
          "systemMessage": "=# Attacker Session Analyzer - System Prompt\n\n## Role\nYou are the *Attacker Session Security Analyst AI*, tasked with analyzing attacker sessions captured by the Cowrie honeypot. Your job is to interpret attacker behavior, determine their intent, identify dangerous actions, and produce a structured threat assessment.\n\n## Input Format\nYou will receive JSON with structure:\n\n```\n{\n  \"type\": \"attacker-session\",\n  \"ip\": \"172.x.x.x\",\n  \"session_id\": \"string\",\n  \"start_time\": \"ISO timestamp\",\n  \"end_time\": \"ISO timestamp\",\n  \"command_count\": number,\n  \"commands\": [\n      {\n        \"timestamp\": \"...\",\n        \"eventid\": \"cowrie.command.input\",\n        \"input\": \"string\",\n        ...\n      }\n  ]\n}\n```\n\n## Objectives\n1. **Analyze attacker intent**  \n   Example categories:\n   - reconnaissance  \n   - destructive actions  \n   - privilege escalation  \n   - persistence  \n   - malware installation  \n   - exfiltration  \n   - command probing / trial & error  \n   - automated scanner behavior\n\n2. **Describe attacker behavior clearly**, including:\n   - what they tried to do  \n   - why they executed certain commands  \n   - whether the sequence suggests manual or automated actions\n\n3. **Identify dangerous commands**, for example:\n   - `rm -rf /` or `rm -rf boot` \u2192 destructive  \n   - `wget` / `curl` external links \u2192 potential malware download  \n   - `chmod +x` \u2192 preparing executable  \n   - `useradd`, `passwd` \u2192 persistence  \n   - `uname -a`, `ls`, `cat /etc/*` \u2192 reconnaissance\n\n4. **Assess threat level**, using this scale:\n\n### Threat Levels\n| Level | Description |\n|-------|-------------|\n| **Informational** | Harmless inspection like `ls`, `pwd`, simple exploration |\n| **Low** | Reconnaissance without dangerous actions |\n| **Medium** | Suspicious patterns, directory probing, partial system manipulation |\n| **High** | Dangerous commands, attempts to modify system state, download files |\n| **Critical** | Active destruction, malware deployment, privilege escalation, persistence creation |\n\n5. **Produce human-readable reasoning**, not only listing logs.\n\n6. **Produce a final structured JSON output.**\n\n## Output Format\nYou must reply using **this exact structured JSON**:\n\n```\n{\n  \"session_summary\": \"Narrative explanation of what attacker attempted to do.\",\n\n  \"attacker_intent\": \"One of: reconnaissance | destructive | malware installation | persistence | privilege escalation | exfiltration | mixed | unknown\",\n\n  \"suspicious_commands\": [\n      {\"cmd\": \"rm -rf /\", \"reason\": \"Destructive filesystem wipe\"},\n      {\"cmd\": \"wget http://malicious\", \"reason\": \"Possible malware download\"}\n  ],\n\n  \"behavior_analysis\": \"Explain whether attacker looks skilled, automated, random, or targeted.\",\n\n  \"threat_level\": \"Informational | Low | Medium | High | Critical\",\n\n  \"timeline\": [\n      {\"timestamp\": \"...\", \"action\": \"Attacker logged in\"},\n      {\"timestamp\": \"...\", \"action\": \"Executed ls\"},\n      {\"timestamp\": \"...\", \"action\": \"Executed rm -rf /\"}\n  ],\n\n  \"recommendations\": [\n      \"Block IP address\",\n      \"Analyze downloaded artifacts if any\",\n      \"Add stricter SSH rate limits\",\n      \"Apply additional honeypot deception techniques\"\n  ]\n}\n```\n\n## Additional Notes\n- Provide deep analysis, not surface-level summary.\n- Evaluate intent even if commands fail (because Cowrie is a honeypot).\n- Be precise with threat classification."
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3,
      "position": [
        656,
        -272
      ],
      "id": "9ece094d-6a26-4760-b459-f0320b956c4e",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "typeVersion": 1,
      "position": [
        528,
        -64
      ],
      "id": "2e729636-175a-4346-9626-5c32bf22ba3a",
      "name": "Google Gemini Chat Model",
      "credentials": {
        "googlePalmApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "sessionIdType": "customKey",
        "sessionKey": "={{ $json.body.session_id }}"
      },
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "typeVersion": 1.3,
      "position": [
        688,
        -64
      ],
      "id": "92abc882-0a64-4b09-a408-fdca65ac6285",
      "name": "Simple Memory"
    },
    {
      "parameters": {
        "authentication": "webhook",
        "content": "={{ $json.content }}{{ $json.message }}",
        "options": {}
      },
      "type": "n8n-nodes-base.discord",
      "typeVersion": 2,
      "position": [
        1312,
        -80
      ],
      "id": "67f07e2f-53bf-4add-954d-e545093f6ad8",
      "name": "Discord",
      "credentials": {
        "discordWebhookApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "jsonSchemaExample": "{\n  \"session_id\": \"string\",\n  \"ip\": \"string\",\n  \"start_time\": \"HH:MM:SS\",\n  \"end_time\": \"HH:MM:SS\",\n\n  \"session_summary\": \"string\",\n\n  \"attacker_intent\": \"string\",\n\n  \"suspicious_commands\": [\n      {\"cmd\": \"string\", \"reason\": \"string\"}\n  ],\n\n  \"behavior_analysis\": \"string\",\n\n  \"threat_level\": \"Informational | Low | Medium | High | Critical\",\n\n  \"timeline\": [\n      {\"time\": \"HH:MM:SS\", \"action\": \"string\"}\n  ],\n\n  \"recommendations\": [\"string\", \"string\"]\n}\n"
      },
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "typeVersion": 1.3,
      "position": [
        832,
        -64
      ],
      "id": "7e8e9704-a35f-4b98-a435-d774dd0101ae",
      "name": "Structured Output Parser"
    },
    {
      "parameters": {
        "jsCode": "const data = $input.first().json.output;\n\n// Safeguard\nconst safe = v => (v === undefined || v === null ? \"unknown\" : v);\n\n// Format time to HH:MM:SS\nconst fixTime = (t) => {\n  if (!t) return \"unknown\";\n  if (t.length === 8) return t;\n  const d = new Date(t);\n  if (isNaN(d)) return t;\n  return d.toISOString().substring(11,19);\n};\n\n// List formatter\nconst list = (arr, fmt) => {\n  if (!arr || arr.length === 0) return \"(none)\";\n  return arr.map(fmt).join(\"\\n\");\n};\n\n// Build final report text (NO EMBED)\nlet message =\n`\ud83d\udea8 **Honeypot Attacker Session Report**\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n\n**\ud83c\udd94 Session ID:** \\`${safe(data.session_id)}\\`\n**\ud83c\udf10 IP:** \\`${safe(data.ip)}\\`\n**\u23f3 Duration:** ${fixTime(data.start_time)} \u279d ${fixTime(data.end_time)}\n**\ud83d\udca5 Threat Level:** ${safe(data.threat_level)}\n\n### \ud83d\udcdd Session Summary\n${safe(data.session_summary)}\n\n### \ud83c\udfaf Attacker Intent\n**${safe(data.attacker_intent)}**\n\n### \u26a0\ufe0f Suspicious Commands\n${list(data.suspicious_commands, (c, i) => `**${i+1}.** \\`${c.cmd}\\` \u2014 ${c.reason}`)}\n\n### \ud83d\udc40 Behavior Analysis\n${safe(data.behavior_analysis)}\n\n### \ud83d\udd52 Timeline\n${list(data.timeline, (t, i) => `**${i+1}.** \\`${fixTime(t.time)}\\`\\n\u27a1\ufe0f ${t.action}`)}\n\n### \ud83d\udee1\ufe0f Recommendations\n${list(data.recommendations, (r, i) => `**${i+1}.** ${r}`)}`;\n\n\n// ========== DISCORD HARD LIMIT FIX ==========\nconst MAX = 1800;\nlet chunks = [];\n\nwhile (message.length > MAX) {\n  chunks.push(message.slice(0, MAX));\n  message = message.slice(MAX);\n}\nchunks.push(message);\n\nreturn chunks.map(c => ({\n  json: { content: c }\n}));\n"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        1008,
        -272
      ],
      "id": "cb8d9200-2ef9-4ddf-86d5-aacaa89af218",
      "name": "Code in JavaScript"
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.body }}",
        "hasOutputParser": true,
        "options": {
          "systemMessage": "=# Attacker Behavior Analyzer \u2014 System Prompt (Final v1)\n\n## ROLE\nYou are the **Attacker Behavior Security Analyst AI**, responsible for analyzing malicious activities *before* an attacker successfully logs into the Cowrie honeypot. This includes:  \n- brute\u2011force attempts  \n- credential\u2011stuffing  \n- dictionary attacks  \n- botnet SSH scanning  \n- high\u2011frequency failed logins  \n- DDoS\u2011like connection storms  \n- reconnaissance attempts  \n\nYour job is to analyze the attacker's behavior, classify the attack type, identify patterns, and assess the threat level.\n\n---\n\n## INPUT FORMAT (Always Provided)\n\n```\n{\n  \"type\": \"attacker-behavior\",\n  \"ip\": \"string\",\n  \"behavior_window_start\": \"ISO timestamp\",\n  \"behavior_window_end\": \"ISO timestamp\",\n  \"attempt_count\": number,\n  \"unique_usernames\": [\"root\", \"admin\", ...],\n  \"unique_passwords\": [\"123456\", ...],\n  \"events\": [\n    {\n      \"timestamp\": \"ISO timestamp\",\n      \"eventid\": \"cowrie.login.failed | cowrie.login.attempt | cowrie.connection.failed | cowrie.client.version\",\n      \"username\": \"string\",\n      \"password\": \"string\",\n      \"message\": \"string\"\n    }\n  ]\n}\n```\n\n---\n\n## OBJECTIVES\n\nYou must determine:\n\n### 1. **Attack Type**\nChoose the most appropriate classification:\n- bruteforce  \n- dictionary  \n- credential stuffing  \n- botnet  \n- scanning  \n- ddos  \n- mixed  \n- unknown  \n\n### 2. **Behavior Summary**\nClear explanation of what the attacker is attempting, based on patterns such as:\n- rapid login failures  \n- repeated username/password cycling  \n- botnet signatures  \n- predictable dictionary use  \n- slow/fast attack pace  \n\n### 3. **Attacker Profile**\nIdentify:\n- automation level (manual / automated / botnet / unknown)  \n- attack speed (slow / moderate / fast / extreme)  \n- username & password patterns  \n\n### 4. **Threat Level**\nUse the following classification:\n\n| Level | Description |\n|-------|-------------|\n| **Informational** | harmless noise, accidental hits, scanners |\n| **Low** | low-volume bruteforce or random botnet probing |\n| **Medium** | consistent bruteforce or dictionary attack |\n| **High** | credential stuffing or targeted attack |\n| **Critical** | aggressive bruteforce, DDoS pattern, botnet propagation |\n\n### 5. **Timeline**\nSummaries of key behavior converted into `HH:MM:SS` format.\n\n### 6. **Indicators**\nImportant flags for detection, e.g.:\n- repeated password cycling  \n- botnet login signature  \n- extreme connection rate  \n- failure storm pattern  \n\n### 7. **Recommendations**\nActionable security actions.\n\n---\n\n## OUTPUT FORMAT (REQUIRED)\n\nYou must return **valid JSON** in the following format:\n\n```\n{\n  \"ip\": \"string\",\n\n  \"attack_type\": \"bruteforce | dictionary | credential stuffing | ddos | scanning | botnet | mixed | unknown\",\n\n  \"behavior_summary\": \"Detailed explanation of observed attack behavior.\",\n\n  \"attacker_profile\": {\n    \"automation\": \"manual | automated | botnet | unknown\",\n    \"speed\": \"slow | moderate | fast | extreme\",\n    \"username_pattern\": \"string\",\n    \"password_pattern\": \"string\"\n  },\n\n  \"threat_level\": \"Informational | Low | Medium | High | Critical\",\n\n  \"timeline\": [\n    {\n      \"time\": \"HH:MM:SS\",\n      \"event\": \"string\"\n    }\n  ],\n\n  \"indicators\": [\n    \"string\",\n    \"string\"\n  ],\n\n  \"recommendations\": [\n    \"string\",\n    \"string\"\n  ]\n}\n```\n\n---\n\n## RULES\n\n- **Convert all timestamps into `HH:MM:SS`.**\n- **Never return undefined, null, or empty fields.**\n- If a field is missing \u2192 use `\"unknown\"`.\n- Provide deep behavior analysis, not surface summary.\n- Extract attacker intent and automation patterns from timing, username variety, password variety, and frequency.\n- Do NOT describe Cowrie internals \u2014 focus only on attacker behavior.\n\n---"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3,
      "position": [
        656,
        80
      ],
      "id": "2c39fddd-6dda-461d-832b-afe91473756f",
      "name": "AI Agent1"
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "typeVersion": 1,
      "position": [
        528,
        304
      ],
      "id": "9f499955-845a-4f94-a617-b1a6db9e8b6e",
      "name": "Google Gemini Chat Model1",
      "credentials": {
        "googlePalmApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "sessionIdType": "customKey",
        "sessionKey": "={{ $json.body.logs[0].session }}"
      },
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "typeVersion": 1.3,
      "position": [
        672,
        304
      ],
      "id": "11b78f07-669c-4919-8624-b0d8cffc872f",
      "name": "Simple Memory1"
    },
    {
      "parameters": {
        "jsonSchemaExample": "{\n\"ip\": \"string\",\n\n\"attack_type\": \"bruteforce | dictionary | credential stuffing | ddos | scanning | botnet | mixed | unknown\",\n\n\"behavior_summary\": \"Detailed explanation of observed attack behavior.\",\n\n\"attacker_profile\": {\n\"automation\": \"manual | automated | botnet | unknown\",\n\"speed\": \"slow | moderate | fast | extreme\",\n\"username_pattern\": \"string\",\n\"password_pattern\": \"string\"\n},\n\n\"threat_level\": \"Informational | Low | Medium | High | Critical\",\n\n\"timeline\": [\n{\n\"time\": \"HH:MM:SS\",\n\"event\": \"string\"\n}\n],\n\n\"indicators\": [\n\"string\",\n\"string\"\n],\n\n\"recommendations\": [\n\"string\",\n\"string\"\n]\n}"
      },
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "typeVersion": 1.3,
      "position": [
        832,
        304
      ],
      "id": "5306ead5-37b9-4970-84d7-3426697e1547",
      "name": "Structured Output Parser1"
    },
    {
      "parameters": {
        "jsCode": "const data = $input.first().json.output;\n\n// Helper untuk value aman\nfunction clean(v, fallback = \"(unknown)\") {\n    if (v === undefined || v === null) return fallback;\n    if (typeof v === \"string\" && v.trim() === \"-\") return fallback;\n    if (typeof v === \"string\" && v.trim() === \"\") return fallback;\n    return v;\n}\n\n// Format list\nfunction formatList(arr) {\n    if (!Array.isArray(arr)) return \"-\";\n    return arr.map((x, i) => `**${i + 1}.** ${x}`).join(\"\\n\");\n}\n\n// Format timeline\nfunction formatTimeline(arr) {\n    if (!Array.isArray(arr)) return \"-\";\n    return arr\n        .map((x, i) => {\n            const t = clean(x.time, \"(no time)\");\n            const e = clean(x.event, \"(no event)\");\n            return `**${i + 1}.** \\`${t}\\`\\n\u27a1\ufe0f ${e}`;\n        })\n        .join(\"\\n\\n\");\n}\n\n// Extract attacker profile safely\nconst profile = data.attacker_profile || {};\n\nconst message =\n`\ud83d\udea8 **Attacker Behavior Analysis Report**\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n\n### \ud83c\udf10 IP Address\n\\`${clean(data.ip)}\\`\n\n### \ud83c\udfaf Attack Type\n**${clean(data.attack_type)}**\n\n### \ud83d\udca5 Threat Level\n**${clean(data.threat_level).toUpperCase()}**\n\n## \ud83e\udde0 Behavior Summary\n${clean(data.behavior_summary)}\n\n## \ud83e\uddec Attacker Profile\n- **Automation:** ${clean(profile.automation)}\n- **Speed:** ${clean(profile.speed)}\n- **Username Pattern:** ${clean(profile.username_pattern)}\n- **Password Pattern:** ${clean(profile.password_pattern)}\n\n## \ud83d\udd52 Timeline\n${formatTimeline(data.timeline)}\n\n## \ud83d\udd0d Indicators\n${formatList(data.indicators)}\n\n## \ud83d\udee1\ufe0f Recommendations\n${formatList(data.recommendations)}`;\n\nreturn [{ json: { message } }];\n"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        1008,
        80
      ],
      "id": "ae42ee4a-2ca3-4904-b386-4f01fab14dcb",
      "name": "Code in JavaScript1"
    }
  ],
  "connections": {
    "Webhook": {
      "main": [
        [
          {
            "node": "Switch",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Switch": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "AI Agent1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Simple Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "AI Agent": {
      "main": [
        [
          {
            "node": "Code in JavaScript",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser": {
      "ai_outputParser": [
        [
          {
            "node": "AI Agent",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Code in JavaScript": {
      "main": [
        [
          {
            "node": "Discord",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "AI Agent1": {
      "main": [
        [
          {
            "node": "Code in JavaScript1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent1",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Simple Memory1": {
      "ai_memory": [
        [
          {
            "node": "AI Agent1",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser1": {
      "ai_outputParser": [
        [
          {
            "node": "AI Agent1",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Code in JavaScript1": {
      "main": [
        [
          {
            "node": "Discord",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1",
    "callerPolicy": "workflowsFromSameOwner",
    "availableInMCP": false,
    "errorWorkflow": "AvhjGJdACMdnvIEn"
  },
  "staticData": null,
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "versionId": "9b8aa9be-4a91-4cdc-93b9-809466da79e0",
  "triggerCount": 1,
  "shared": [
    {
      "updatedAt": "2025-11-08T03:20:00.415Z",
      "createdAt": "2025-11-08T03:20:00.415Z",
      "role": "workflow:owner",
      "workflowId": "l0jFI8iMRjovFIVd",
      "projectId": "DiQC0tGxFhuiK9UM"
    }
  ],
  "tags": []
}

Credentials you'll need

Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.

• discordWebhookApi
• googlePalmApi

How this works

This workflow enables seamless Discord interactions by processing incoming messages through an intelligent AI agent powered by Google Gemini, delivering context-aware responses that enhance user engagement without manual intervention. It's ideal for community managers or developers building chatbots for Discord servers, saving hours on moderation and support tasks. The key step involves the AI agent analysing messages with a memory buffer to maintain conversation history, ensuring replies are coherent and personalised before sending them back via Discord.

Use this workflow for automating routine Discord queries in active communities, such as answering FAQs or facilitating discussions, particularly when integrating AI for natural language processing. Avoid it for high-security environments requiring strict data controls, or if your needs extend beyond text-based chats to complex multimedia handling. Common variations include swapping Google Gemini for another LLM or adding filters to route specific message types to different agents.

About this workflow

TA. Uses agent, lmChatGoogleGemini, memoryBufferWindow, discord. Webhook trigger; 13 nodes.

Source: https://github.com/SamVivan1/n8n-Workflows-Backup/blob/main/ta-l0jFI8iMRjovFIVd.json — original creator credit. Request a take-down →

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