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Multi-Agent Pipeline

Multi-Agent Pipeline. Uses scheduleTrigger, agent, lmChatAnthropic, executeWorkflow. Scheduled trigger; 6 nodes.

Cron / scheduled trigger★★☆☆☆ complexityAI-powered6 nodesAgentLm Chat AnthropicChain SummarizationLm Chat Google Gemini
AI & RAG Trigger: Cron / scheduled Nodes: 6 Complexity: ★★☆☆☆ AI nodes: yes

The workflow JSON

Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →

Download .json
{
  "name": "Multi-Agent Pipeline",
  "id": "wf-003",
  "nodes": [
    {
      "name": "Schedule Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "hours",
              "hoursInterval": 1
            }
          ]
        }
      },
      "position": [
        200,
        300
      ]
    },
    {
      "name": "Research Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "parameters": {
        "agentType": "toolsAgent",
        "systemMessage": "You are a research agent."
      },
      "position": [
        400,
        300
      ]
    },
    {
      "name": "Anthropic Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
      "parameters": {
        "model": "claude-3-5-sonnet-20241022",
        "maxTokens": 4096
      },
      "credentials": {
        "anthropicApi": {
          "name": "<your credential>"
        }
      },
      "position": [
        400,
        500
      ]
    },
    {
      "name": "Execute Sub-Workflow",
      "type": "n8n-nodes-base.executeWorkflow",
      "parameters": {
        "workflowId": "wf-001"
      },
      "position": [
        600,
        300
      ]
    },
    {
      "name": "Summarization Chain",
      "type": "@n8n/n8n-nodes-langchain.chainSummarization",
      "parameters": {},
      "position": [
        800,
        300
      ]
    },
    {
      "name": "Google Gemini",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "parameters": {
        "model": "gemini-1.5-pro"
      },
      "credentials": {
        "googleGeminiApi": {
          "name": "<your credential>"
        }
      },
      "position": [
        800,
        500
      ]
    }
  ],
  "connections": {
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "Research Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Research Agent": {
      "main": [
        [
          {
            "node": "Execute Sub-Workflow",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Anthropic Model": {
      "ai_languageModel": [
        [
          {
            "node": "Research Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Execute Sub-Workflow": {
      "main": [
        [
          {
            "node": "Summarization Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini": {
      "ai_languageModel": [
        [
          {
            "node": "Summarization Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}

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.

About this workflow

Multi-Agent Pipeline. Uses scheduleTrigger, agent, lmChatAnthropic, executeWorkflow. Scheduled trigger; 6 nodes.

Source: https://github.com/Trusera/ai-bom/blob/main/examples/demo-project/workflows/multi-agent-pipeline.json — original creator credit. Request a take-down →

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