AutomationFlowsAI & RAG › PDF Q&A Agent with Mistral & PGVector

PDF Q&A Agent with Mistral & PGVector

Original n8n title: PDF Agent

PDF agent. Uses chainRetrievalQa, lmChatMistralCloud, retrieverVectorStore, vectorStorePGVector. Event-driven trigger; 6 nodes.

Event trigger★★☆☆☆ complexityAI-powered6 nodesChain Retrieval QaLm Chat Mistral CloudRetriever Vector StoreVector Store PgvectorEmbeddings Mistral CloudExecute Workflow Trigger
AI & RAG Trigger: Event Nodes: 6 Complexity: ★★☆☆☆ AI nodes: yes Added:

This workflow follows the Chainretrievalqa → Retrievervectorstore 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": "PDF agent",
  "nodes": [
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.query }}",
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
      "typeVersion": 1.4,
      "position": [
        40,
        -20
      ],
      "id": "9869c11d-fe33-4dd5-9d95-e496a624ca0b",
      "name": "Question and Answer Chain"
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatMistralCloud",
      "typeVersion": 1,
      "position": [
        -40,
        200
      ],
      "id": "96015485-d78a-4dfb-a9b6-7ce623817444",
      "name": "Mistral Cloud Chat Model",
      "credentials": {
        "mistralCloudApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {},
      "type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
      "typeVersion": 1,
      "position": [
        100,
        140
      ],
      "id": "810b63ab-7fc4-469c-bd8a-602027b075a2",
      "name": "Vector Store Retriever"
    },
    {
      "parameters": {
        "tableName": "pdf_vectors",
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.vectorStorePGVector",
      "typeVersion": 1,
      "position": [
        200,
        320
      ],
      "id": "cf8bf3a7-ffcd-41f9-8785-9bc3efd8e0c0",
      "name": "Postgres PGVector Store",
      "credentials": {
        "postgres": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.embeddingsMistralCloud",
      "typeVersion": 1,
      "position": [
        220,
        460
      ],
      "id": "1a52e246-51a3-4d51-93f0-fc8a973db232",
      "name": "Embeddings Mistral Cloud",
      "credentials": {
        "mistralCloudApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "inputSource": "passthrough"
      },
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "typeVersion": 1.1,
      "position": [
        -140,
        -20
      ],
      "id": "54c59716-72d9-42c4-9a91-19bd1045f0cd",
      "name": "When Executed by Another Workflow"
    }
  ],
  "connections": {
    "Mistral Cloud Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Question and Answer Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Vector Store Retriever": {
      "ai_retriever": [
        [
          {
            "node": "Question and Answer Chain",
            "type": "ai_retriever",
            "index": 0
          }
        ]
      ]
    },
    "Postgres PGVector Store": {
      "ai_vectorStore": [
        [
          {
            "node": "Vector Store Retriever",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings Mistral Cloud": {
      "ai_embedding": [
        [
          {
            "node": "Postgres PGVector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "When Executed by Another Workflow": {
      "main": [
        [
          {
            "node": "Question and Answer Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "85668b53-a70d-4c1d-9967-d56cd0854059",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "id": "vHlLtuL530UbpaFe",
  "tags": []
}

Credentials you'll need

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About this workflow

PDF agent. Uses chainRetrievalQa, lmChatMistralCloud, retrieverVectorStore, vectorStorePGVector. Event-driven trigger; 6 nodes.

Source: https://github.com/Karlerikkanal/GenomeAnalysisTool/blob/af76a30a7848e2f08b257e4f559d31641c3d9d86/workflows/PDF_agent.json — original creator credit. Request a take-down →

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