Measure AI Model Carbon Footprint with Ecologits.ai Methodology

The workflow JSON

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{
  "nodes": [
    {
      "id": "e374f8b8-ff4a-4b98-af50-d609338ec38f",
      "name": "When clicking \u2018Execute workflow\u2019",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        0,
        -160
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "6cce6b66-bd1a-419b-86c1-b76aa257e96c",
      "name": "Basic LLM Chain",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        608,
        -160
      ],
      "parameters": {
        "text": "Enter here your user prompt",
        "batching": {},
        "messages": {
          "messageValues": [
            {
              "message": "Enter here the system prompt"
            }
          ]
        },
        "promptType": "define"
      },
      "typeVersion": 1.7
    },
    {
      "id": "d0ea8139-307d-4de6-9f29-11216958f362",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        672,
        64
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o",
          "cachedResultName": "gpt-4o"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "0fca2f27-8a0b-46d0-9dfc-27967afe2ae5",
      "name": "Calculate gCO\u2082e",
      "type": "n8n-nodes-base.set",
      "position": [
        960,
        -160
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "cc17f2be-ce12-488f-89c7-de200b4c4869",
              "name": "AI output",
              "type": "string",
              "value": "={{ $json.text }}"
            },
            {
              "id": "c396e3b8-f07f-4153-9892-1b499a724dbc",
              "name": "AI output gCO\u2082e",
              "type": "number",
              "value": "={{ Math.ceil($json.text.length / 4) * $('Conversion factor').item.json['Conversion factor (in gCO\u2082e/token)'] }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "5c25ded0-c24d-455b-82fb-d54d267ca591",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -624,
        -384
      ],
      "parameters": {
        "width": 560,
        "height": 672,
        "content": "# Measure Your AI's Carbon Footprint\n\nThis workflow demonstrates a technique to calculate the gCO\u2082e (grams of CO\u2082 equivalent) of an AI model's output, based on the methodology from **Ecologits.ai**.\n\n## How it works\n\nA dedicated **Conversion factor** node makes it easy to set your parameters. The **Calculate gCO\u2082e** node then uses this factor and the AI's text output to estimate the carbon footprint.\n\n## How to use this snippet\n\n1.  **Set your conversion factor (Important!):** The default factor is for **GPT-4o in the US**. You **must** visit **ecologits.ai/latest** to find the correct factor for *your model and server region* and update the value in the **\"Conversion factor\"** node.\n2.  **Connect the snippet:** Place the **\"Conversion factor\"** node before your AI node and the **\"Calculate gCO\u2082e\"** node after it.\n3.  **Update the calculation:** Modify the **\"Calculate gCO\u2082e\"** node to use the output text from *your* AI node.\n\n**Pro-Tip:** For higher accuracy, use the direct `output_tokens` value from your AI node's data if it's available."
      },
      "typeVersion": 1
    },
    {
      "id": "941043b0-01ee-4553-87ec-1246a4cb2f2b",
      "name": "Conversion factor",
      "type": "n8n-nodes-base.set",
      "position": [
        304,
        -160
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "a2c5484b-173e-4647-8dc1-23c32a899f75",
              "name": "Conversion factor (in gCO\u2082e/token)",
              "type": "number",
              "value": 0.0612
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "430fc390-50b7-4feb-8c8f-be196a342d60",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        224,
        -240
      ],
      "parameters": {
        "color": 5,
        "width": 272,
        "height": 336,
        "content": "### Adapt this value to your model & settings\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nUse the expert mode here to find the factor that fits best:\nhttps://huggingface.co/spaces/genai-impact/ecologits-calculator"
      },
      "typeVersion": 1
    }
  ],
  "connections": {
    "Basic LLM Chain": {
      "main": [
        [
          {
            "node": "Calculate gCO\u2082e",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Conversion factor": {
      "main": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "When clicking \u2018Execute workflow\u2019": {
      "main": [
        [
          {
            "node": "Conversion factor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Credentials you'll need

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• openAiApi

About this workflow

This template provides a straightforward technique to measure and raise awareness about the environmental impact of your AI automations.

Source: https://n8n.io/workflows/7716/ — original creator credit. Request a take-down →

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