Chat with Pinecone RAG

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 →

{
  "name": "Chat with Pinecone RAG",
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "bc3934df-8d10-48df-9960-f0db1e806328",
        "responseMode": "responseNode",
        "options": {}
      },
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2.1,
      "position": [
        320,
        400
      ],
      "id": "webhook-trigger",
      "name": "Webhook"
    },
    {
      "parameters": {
        "text": "={{ $json.body.message }}",
        "options": {
          "systemMessage": "Kamu adalah asisten AI yang membantu bernama Ryuma dengan akses ke knowledge base. Kamu sedang chat dengan user bernama Eja.\\n\\nPENTING:\\n- SELALU jawab dalam BAHASA INDONESIA kecuali Eja meminta bahasa lain\\n- Ketika Eja menyapa (halo, hi, hello, dll), SELALU sapa balik dengan menyebut namanya, contoh: 'Halo Eja!' atau 'Hi Eja, ada yang bisa saya bantu?'\\n- Gunakan informasi dari knowledge base jika relevan untuk menjawab pertanyaan\\n- Berikan respons yang akurat dan membantu\\n- Bersikap ramah dan profesional"
        }
      },
      "id": "ai-agent",
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        720,
        400
      ],
      "typeVersion": 1.1
    },
    {
      "parameters": {
        "options": {
          "frequencyPenalty": 0.2,
          "temperature": 0.7
        }
      },
      "id": "openai-chat-model",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        720,
        600
      ],
      "typeVersion": 1,
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "sessionKey": "={{ $json.body.chatId }}",
        "contextWindowLength": 10
      },
      "id": "window-buffer-memory",
      "name": "Window Buffer Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        920,
        600
      ],
      "typeVersion": 1
    },
    {
      "parameters": {
        "name": "knowledge_base",
        "description": "Use this tool to search the knowledge base for relevant information to answer user questions."
      },
      "id": "vector-store-tool",
      "name": "Vector Store Tool",
      "type": "@n8n/n8n-nodes-langchain.toolVectorStore",
      "position": [
        920,
        400
      ],
      "typeVersion": 1
    },
    {
      "parameters": {
        "mode": "load",
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": ""
        },
        "topK": 5
      },
      "id": "pinecone-vector-store",
      "name": "Pinecone Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        1120,
        400
      ],
      "typeVersion": 1,
      "credentials": {
        "pineconeApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "model": "text-embedding-3-small"
      },
      "id": "embeddings-openai",
      "name": "Embeddings OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        1120,
        600
      ],
      "typeVersion": 1,
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "respondWith": "text",
        "responseBody": "={{ $json.output }}",
        "options": {}
      },
      "type": "n8n-nodes-base.respondToWebhook",
      "typeVersion": 1.4,
      "position": [
        920,
        400
      ],
      "id": "respond-to-webhook",
      "name": "Respond to Webhook"
    }
  ],
  "connections": {
    "Webhook": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "AI Agent": {
      "main": [
        [
          {
            "node": "Respond to Webhook",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Window Buffer Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Vector Store Tool": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Pinecone Vector Store": {
      "ai_vectorStore": [
        [
          {
            "node": "Vector Store Tool",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings OpenAI": {
      "ai_embedding": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "executionOrder": "v1"
  }
}

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.

• openAiApi
• pineconeApi

About this workflow

Chat with Pinecone RAG. Uses agent, lmChatOpenAi, memoryBufferWindow, toolVectorStore. Webhook trigger; 8 nodes.

Source: https://github.com/Fachryza713/n8n-ngrok/blob/eff235e51742ba57d614f37c88db1ecb45d77ec3/chat-with-pinecone-rag.json — original creator credit. Request a take-down →

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