AutomationFlowsAI & RAG › AI Health Expert Chat

AI Health Expert Chat

Original n8n title: Health Expert

Health Expert. Uses agent, executeWorkflowTrigger, lmChatOpenAi. Event-driven trigger; 3 nodes.

Event trigger★☆☆☆☆ complexityAI-powered3 nodesAgentExecute Workflow TriggerOpenAI Chat
AI & RAG Trigger: Event Nodes: 3 Complexity: ★☆☆☆☆ AI nodes: yes Added:

This workflow follows the Agent → Execute Workflow Trigger recipe pattern — see all workflows that pair these two integrations.

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": "Health Expert",
  "nodes": [
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.query }}",
        "options": {
          "systemMessage": "\n## ROLE  \nYou are **Medical\u202fExpert**, a board\u2011certified clinical specialist summoned by Health\u202fAssistant whenever clinical context or guideline clarity is needed.  \nYou do **not** query databases or write SQL. Instead, you supply authoritative medical definitions, guideline thresholds, and the **minimal set of biometrics / labs** required to answer the Assistant\u2019s question.\n\n## TASK FLOW  \n1. Read the Assistant\u2019s question carefully.  \n2. If the term is well\u2011defined (e.g., \u201coverweight\u201d, \u201cStage\u202f2 hypertension\u201d), provide:  \n   * a one\u2011sentence definition,  \n   * the numeric threshold(s) and units,  \n   * the minimum data fields or lab tests needed.  \n3. If no consensus definition exists, describe the most accepted options and note the uncertainty.  \n4. Keep answers **brief and precise**; no empathetic counseling (the Assistant will handle bedside manner). With every response, always include the minimum data needed to accomplish the task.\n\n## STYLE GUIDE  \n* **Definitive &\u00a0Evidence\u2011Based** \u2013 cite guideline authorship (e.g., \u201cWHO, 2020\u201d).  \n* **Bullet points over paragraphs** unless a paragraph is clearer.  \n* **No SQL or implementation details.** Provide only medical facts.\n\n## FEW\u2011SHOT EXAMPLES  \n\n### Example\u00a01  \n**Assistant asks:**  \n> \u201cFor \u2018overweight\u2019, which metric and cutoff should I use? What data do I minimally need?\u201d  \n**Medical\u202fExpert replies:**  \n* **Metric:** Body\u2011Mass Index (BMI)  \n* **Threshold:** BMI\u202f\u2265\u202f25\u202fkg/m\u00b2 (WHO, 2020)  \n* **Required data:** Weight (kg), Height (cm)\n\n### Example\u00a02  \n**Assistant asks:**  \n> \u201cWhat defines Stage\u202f2 hypertension in adults, and which vitals are required?\u201d  \n**Medical\u202fExpert replies:**  \n* **Definition:** SBP\u202f\u2265\u202f140\u202fmmHg **or** DBP\u202f\u2265\u202f90\u202fmmHg (ACC/AHA\u00a02017)  \n* **Required data:** Systolic BP, Diastolic BP (latest seated, resting measurement)"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 1.8,
      "position": [
        240,
        0
      ],
      "id": "42485eae-d14e-43e3-b8da-22a33317b17c",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "inputSource": "passthrough"
      },
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "typeVersion": 1.1,
      "position": [
        0,
        0
      ],
      "id": "26ae1a7a-fa06-4f11-ad96-210ed9b65a70",
      "name": "When Executed by Another Workflow"
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "value": "qwen2.5-32-ctx:latest",
          "mode": "list",
          "cachedResultName": "qwen2.5-32-ctx:latest"
        },
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.2,
      "position": [
        240,
        220
      ],
      "id": "5e75dde4-451f-4065-942e-42895655291a",
      "name": "Ollama",
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    }
  ],
  "connections": {
    "When Executed by Another Workflow": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Ollama": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "192995c8-946e-40a6-ae42-df727fdf9df8",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "id": "uKnN7Mmi5OAMIgbL",
  "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.

Pro

For the full experience including quality scoring and batch install features for each workflow upgrade to Pro

About this workflow

Health Expert. Uses agent, executeWorkflowTrigger, lmChatOpenAi. Event-driven trigger; 3 nodes.

Source: https://github.com/DaveBben/apple-health-ai-agent/blob/036f691adbb1eb28201db877de2b90a8028660b0/n8n/Health_Expert.json — original creator credit. Request a take-down →

More AI & RAG workflows → · Browse all categories →

Related workflows

Workflows that share integrations, category, or trigger type with this one. All free to copy and import.

AI & RAG

🤖Contact Agent. Uses lmChatOpenAi, airtableTool, agent, executeWorkflowTrigger. Event-driven trigger; 7 nodes.

OpenAI Chat, Airtable Tool, Agent +1
AI & RAG

Calendar Agent Demo. Uses executeWorkflowTrigger, lmChatOpenAi, googleCalendarTool, agent. Event-driven trigger; 7 nodes.

Execute Workflow Trigger, OpenAI Chat, Google Calendar Tool +1
AI & RAG

Financeiro. Uses executeWorkflowTrigger, agent, memoryBufferWindow, googleSheetsTool. Event-driven trigger; 6 nodes.

Execute Workflow Trigger, Agent, Memory Buffer Window +2
AI & RAG

AI Blog Post Generator with Web Search. Uses toolHttpRequest, executeWorkflowTrigger, lmChatOpenAi, agent. Event-driven trigger; 6 nodes.

Tool Http Request, Execute Workflow Trigger, OpenAI Chat +1
AI & RAG

Preguntas. Uses executeWorkflowTrigger, agent, lmChatOpenAi, dataTableTool. Event-driven trigger; 5 nodes.

Execute Workflow Trigger, Agent, OpenAI Chat +1