{
  "nodes": [
    {
      "id": "27e5f0c0-ba88-4c28-b3be-99c973be15cb",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -480,
        -140
      ],
      "parameters": {
        "width": 1083,
        "height": 357,
        "content": "## This is an example of basic LLM Chain connected to an open-source model\n### The Chain is connected to the Mistral-7B-Instruct-v0.1 model, but you can change this\n\nPlease note the initial prompt that guides the model:\n```\nYou are a helpful assistant.\nPlease reply politely to the users.\nUse emojis and a text.\nQ: {{ $json.input }}\nA: \n```\n\nThis way the model \"knows\" that it needs to answer the question right after the `A: `.\n\nSince Hugging Face node is this is an inference mode, it does not support LangChain Agents at the moment. Please use [Ollama Chat Model](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatollama/) node for that"
      },
      "typeVersion": 1
    },
    {
      "id": "4756d5a8-7027-4942-b214-a5ff8310869a",
      "name": "When chat message received",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -200,
        280
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "20a36351-8579-4ac6-9746-526b072aeaa6",
      "name": "Basic LLM Chain",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        20,
        280
      ],
      "parameters": {
        "messages": {
          "messageValues": [
            {
              "message": "=You are a helpful assistant. Please reply politely to the users. Use emojis and a text."
            }
          ]
        }
      },
      "typeVersion": 1.5
    },
    {
      "id": "9b88e307-3ad5-4167-8c5f-e5827f7444ac",
      "name": "Hugging Face Inference Model",
      "type": "@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference",
      "position": [
        120,
        440
      ],
      "parameters": {
        "model": "mistralai/Mistral-7B-Instruct-v0.1",
        "options": {
          "maxTokens": 512,
          "temperature": 0.8,
          "frequencyPenalty": 2
        }
      },
      "typeVersion": 1
    },
    {
      "id": "a7120539-d7f9-5ebc-94cc-7b31ab8c7a40",
      "name": "Publication · Overview and setup",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        -1280,
        -140
      ],
      "parameters": {
        "content": "# The Chain is connected to the Mistral-7B-Instruct-v0.1 model, but you can change this\n\n## Purpose and structure\nThis folder contains the **The Chain is connected to the Mistral-7B-Instruct-v0.1 model, but you can change this** workflow. Its executable nodes use `chainLlm`, `chatTrigger`, `lmOpenHuggingFaceInference`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nWhen chat message received\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nhttps://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Stickynote/0332_Stickynote_Send_Triggered.json\nMIT; preserve source notices.",
        "width": 700,
        "height": 800,
        "color": 1
      }
    }
  ],
  "connections": {
    "When chat message received": {
      "main": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Hugging Face Inference Model": {
      "ai_languageModel": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false
}