Elastische KI-Workflows mit Auto-GPT und Gemini-Failover-Kette erstellen

Fortgeschritten

Dies ist ein AI-Bereich Automatisierungsworkflow mit 9 Nodes. Hauptsächlich werden Set, ManualTrigger, Code, Agent, LmChatOpenAi und andere Nodes verwendet, kombiniert mit KI-Technologie für intelligente Automatisierung. Elastische KI-Workflows mit Auto-GPT und Gemini-Failover-Ketten erstellen

Voraussetzungen
  • OpenAI API Key
  • Google Gemini API Key
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "meta": {
    "instanceId": "e409ea34548a2afe2dffba31130cd1cf2e98ebe2afaeed2a63caf2a0582d1da0"
  },
  "nodes": [
    {
      "id": "180a023e-a350-4315-a7f2-968d052f634d",
      "name": "KI-Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "onError": "continueErrorOutput",
      "position": [
        280,
        -20
      ],
      "parameters": {
        "text": "Only output \"test\".",
        "options": {},
        "promptType": "define"
      },
      "typeVersion": 2
    },
    {
      "id": "32f3f1ad-8e72-427b-9bcf-0686ae3c4c5c",
      "name": "Agentenvariablen",
      "type": "n8n-nodes-base.set",
      "position": [
        -40,
        -20
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "38ce3db6-ce1d-4091-9645-39e674ad1782",
              "name": "models",
              "type": "array",
              "value": "[\"gemini-2.5-flash\"]"
            },
            {
              "id": "151da1bf-a82a-40a9-bca2-a85ab48f1c5b",
              "name": "fail_count",
              "type": "number",
              "value": "={{ $('Agent Variables')?.isExecuted ? $('Agent Variables').last()?.json?.fail_count + 1 : 0 }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "2d7804a4-3744-4866-89b2-705bbec66acc",
      "name": "Fallback-Modelle",
      "type": "@n8n/n8n-nodes-langchain.code",
      "position": [
        280,
        500
      ],
      "parameters": {
        "code": {
          "supplyData": {
            "code": "let llms = await this.getInputConnectionData('ai_languageModel', 0);\nllms.reverse(); // reverse array, so the order matches the UI elements\n\nconst llm_index = $input.item.json.fail_count;\n\nif (!Number.isInteger(llm_index)) {\n  console.log(\"'llm_index' is udefined or not a valid integer\");\n  throw new Error(\"'llm_index' is udefined or not a valid integer\");\n}\n\nif(typeof llms[llm_index] === 'undefined') {\n  console.log(`No LLM found with index ${llm_index}`);\n  throw new Error(`No LLM found with index ${llm_index}`);\n}\n\nreturn llms[llm_index];"
          }
        },
        "inputs": {
          "input": [
            {
              "type": "ai_languageModel",
              "required": true
            }
          ]
        },
        "outputs": {
          "output": [
            {
              "type": "ai_languageModel"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e3d0d416-2571-4e86-b701-27aee1e5856e",
      "name": "Primäres Modell",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        300,
        700
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o",
          "cachedResultName": "gpt-4o"
        },
        "options": {}
      },
      "typeVersion": 1.2
    },
    {
      "id": "75ce0d64-dcbd-47bf-a15b-802fa979333a",
      "name": "Fallback-Modell",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        420,
        700
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemma-3-27b-it"
      },
      "typeVersion": 1
    },
    {
      "id": "10efe391-496f-45db-ae13-52324b41b4ff",
      "name": "Notiz",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        200,
        200
      ],
      "parameters": {
        "color": 6,
        "width": 420,
        "height": 640,
        "content": "### ⚙️ CONFIGURE YOUR FALLBACK CHAIN HERE ⚙️\n\nThis node selects which AI model to use based on the number of previous failures.\n\n**To set up your models:**\n1.  Add your desired AI model nodes to the canvas (OpenAI, Gemini, Anthropic, etc.).\n2.  Connect them to **THIS** node's `ai_languageModel` input.\n\n\n**IMPORTANT:** The **order** you connect them in is the order they will be tried."
      },
      "typeVersion": 1
    },
    {
      "id": "93797015-159e-4e43-bf72-47f0533e92f1",
      "name": "Notiz1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        240,
        -240
      ],
      "parameters": {
        "color": 7,
        "width": 340,
        "height": 320,
        "content": "#### 📝 DEFINE YOUR PROMPT HERE\n\nEnter the prompt or task for the AI agent in this node.\n\nIt will dynamically use the models provided one-by-one from the `Fallback Models` node. If it fails, it will automatically retry with the next model in your chain."
      },
      "typeVersion": 1
    },
    {
      "id": "4cedd679-70d3-41a2-9bf5-addf8e146c9a",
      "name": "Notiz2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -180,
        -240
      ],
      "parameters": {
        "color": 7,
        "width": 400,
        "height": 320,
        "content": "#### 🔁 Loop Controller\n\nThis node manages the retry loop.\n\nIt initializes and increments a `fail_count` variable each time the `AI Agent` fails, which tells the `Fallback Models` node to try the next model in the list.\n\nNo configuration is needed here."
      },
      "typeVersion": 1
    },
    {
      "id": "4b5e9318-16fd-4e69-add6-0edbca278d91",
      "name": "Manueller Trigger",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -320,
        -20
      ],
      "parameters": {},
      "typeVersion": 1
    }
  ],
  "pinData": {},
  "connections": {
    "180a023e-a350-4315-a7f2-968d052f634d": {
      "main": [
        [],
        [
          {
            "node": "32f3f1ad-8e72-427b-9bcf-0686ae3c4c5c",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "e3d0d416-2571-4e86-b701-27aee1e5856e": {
      "ai_languageModel": [
        [
          {
            "node": "2d7804a4-3744-4866-89b2-705bbec66acc",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "75ce0d64-dcbd-47bf-a15b-802fa979333a": {
      "ai_languageModel": [
        [
          {
            "node": "2d7804a4-3744-4866-89b2-705bbec66acc",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "4b5e9318-16fd-4e69-add6-0edbca278d91": {
      "main": [
        [
          {
            "node": "32f3f1ad-8e72-427b-9bcf-0686ae3c4c5c",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "32f3f1ad-8e72-427b-9bcf-0686ae3c4c5c": {
      "main": [
        [
          {
            "node": "180a023e-a350-4315-a7f2-968d052f634d",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "2d7804a4-3744-4866-89b2-705bbec66acc": {
      "ai_languageModel": [
        [
          {
            "node": "180a023e-a350-4315-a7f2-968d052f634d",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - Künstliche Intelligenz

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes9
Kategorie1
Node-Typen7
Schwierigkeitsbeschreibung

Für erfahrene Benutzer, mittelkomplexe Workflows mit 6-15 Nodes

Autor
Lucas Peyrin

Lucas Peyrin

@lucaspeyrin

Innovative builder with a passion for crafting automation solutions that solve real-world challenges. From streamlining workflows to driving efficiency, my work empowers teams and individuals to achieve more with less effort. Experienced in developing scalable tools and strategies that deliver results with n8n, supabase and cline.

Externe Links
Auf n8n.io ansehen

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Kategorien

Kategorien: 34