AutomationFlowsAI & RAG › Requesty — Full Test (chat · Tool · Structured)

Requesty — Full Test (chat · Tool · Structured)

Requesty — Full Test (Chat · Tool · Structured). Uses chainLlm, @requesty/n8n-nodes-requesty, agent, toolCalculator. Event-driven trigger; 8 nodes.

Event trigger★★★☆☆ complexityAI-powered8 nodesChain Llm@Requesty/N8N Nodes RequestyAgentTool Calculator
AI & RAG Trigger: Event Nodes: 8 Complexity: ★★★☆☆ AI nodes: yes Added:

This workflow corresponds to n8n.io template #requesty-full-test — we link there as the canonical source.

This workflow follows the Agent → Chainllm 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": "Requesty \u2014 Full Test (Chat \u00b7 Tool \u00b7 Structured)",
  "nodes": [
    {
      "parameters": {},
      "id": "aaaaaaaa-0001-0001-0001-000000000001",
      "name": "When clicking Test workflow",
      "type": "n8n-nodes-base.manualTrigger",
      "typeVersion": 1,
      "position": [
        -100,
        480
      ]
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "In one short sentence, say hello and tell me which model you are."
      },
      "id": "bbbbbbbb-0002-0002-0002-000000000002",
      "name": "1) Basic Chat",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "typeVersion": 1.6,
      "position": [
        220,
        180
      ]
    },
    {
      "parameters": {
        "model": "openai/gpt-4o-mini",
        "options": {}
      },
      "id": "cccccccc-0003-0003-0003-000000000003",
      "name": "Requesty (chat)",
      "type": "@requesty/n8n-nodes-requesty.lmChatRequesty",
      "typeVersion": 1,
      "position": [
        220,
        380
      ]
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "What is 1843 multiplied by 27, then minus 500? Use the Calculator tool and show the final number.",
        "options": {
          "systemMessage": "You are a helpful assistant. Always use the Calculator tool for any arithmetic."
        }
      },
      "id": "dddddddd-0004-0004-0004-000000000004",
      "name": "2) Tool Calling (Agent)",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3.1,
      "position": [
        640,
        180
      ]
    },
    {
      "parameters": {
        "model": "openai/gpt-4o-mini",
        "options": {}
      },
      "id": "eeeeeeee-0005-0005-0005-000000000005",
      "name": "Requesty (agent)",
      "type": "@requesty/n8n-nodes-requesty.lmChatRequesty",
      "typeVersion": 1,
      "position": [
        560,
        400
      ]
    },
    {
      "parameters": {},
      "id": "ffffffff-0006-0006-0006-000000000006",
      "name": "Calculator",
      "type": "@n8n/n8n-nodes-langchain.toolCalculator",
      "typeVersion": 1,
      "position": [
        760,
        400
      ]
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "Extract the details from this text: 'Acme Corp, founded in 1998 in Berlin, makes industrial robots and had revenue of 42 million euros last year.'"
      },
      "id": "11110007-0007-0007-0007-000000000007",
      "name": "3) Structured Output",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "typeVersion": 1.6,
      "position": [
        1080,
        180
      ]
    },
    {
      "parameters": {
        "model": "openai/gpt-4o-mini",
        "options": {
          "responseFormat": "json_schema",
          "jsonSchema": "{\n  \"name\": \"company_facts\",\n  \"strict\": true,\n  \"schema\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"company\": { \"type\": \"string\" },\n      \"foundedYear\": { \"type\": \"integer\" },\n      \"city\": { \"type\": \"string\" },\n      \"product\": { \"type\": \"string\" },\n      \"revenueMillionsEur\": { \"type\": \"number\" }\n    },\n    \"required\": [\"company\", \"foundedYear\", \"city\", \"product\", \"revenueMillionsEur\"],\n    \"additionalProperties\": false\n  }\n}"
        }
      },
      "id": "11110008-0008-0008-0008-000000000008",
      "name": "Requesty (structured)",
      "type": "@requesty/n8n-nodes-requesty.lmChatRequesty",
      "typeVersion": 1,
      "position": [
        1000,
        400
      ]
    }
  ],
  "connections": {
    "When clicking Test workflow": {
      "main": [
        [
          {
            "node": "1) Basic Chat",
            "type": "main",
            "index": 0
          },
          {
            "node": "2) Tool Calling (Agent)",
            "type": "main",
            "index": 0
          },
          {
            "node": "3) Structured Output",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Requesty (chat)": {
      "ai_languageModel": [
        [
          {
            "node": "1) Basic Chat",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Requesty (agent)": {
      "ai_languageModel": [
        [
          {
            "node": "2) Tool Calling (Agent)",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Calculator": {
      "ai_tool": [
        [
          {
            "node": "2) Tool Calling (Agent)",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Requesty (structured)": {
      "ai_languageModel": [
        [
          {
            "node": "3) Structured Output",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "meta": {
    "templateId": "requesty-full-test"
  }
}
Pro

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

About this workflow

Requesty — Full Test (Chat · Tool · Structured). Uses chainLlm, @requesty/n8n-nodes-requesty, agent, toolCalculator. Event-driven trigger; 8 nodes.

Source: https://github.com/requestyai/n8n-requesty/blob/main/test-workflow-full.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

Monthly Invoice Summarizer. Uses googleDriveTrigger, googleDrive, lmChatOpenAi, outputParserStructured. Event-driven trigger; 28 nodes.

Google Drive Trigger, Google Drive, OpenAI Chat +6
AI & RAG

telegramAssistant. Uses telegramTrigger, agent, lmChatOpenAi, memoryBufferWindow. Event-driven trigger; 17 nodes.

Telegram Trigger, Agent, OpenAI Chat +7
AI & RAG

Jarwis. Uses telegramTrigger, agent, lmChatOpenAi, memoryBufferWindow. Event-driven trigger; 17 nodes.

Telegram Trigger, Agent, OpenAI Chat +7
AI & RAG

This workflow is for users who want to turn Telegram into a personal AI-powered assistant capable of handling everyday tasks through natural language. It's ideal for solo founders, operators, or profe

Memory Buffer Window, Tool Workflow, Tool Think +9
AI & RAG

Awesome N8N Templates. Uses agent, telegramTrigger, mcpClientTool, mcpTrigger. Event-driven trigger; 33 nodes.

Agent, Telegram Trigger, Mcp Client Tool +9