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使用 Qdrant 和 n8n 的混合搜索，法律 AI：检索

高级

这是一个自动化工作流，包含 17 个节点。主要使用 Set、Merge、Filter、SplitOut、Qdrant 等节点。 基于 Qdrant 和 n8n 的混合搜索，法律 AI：检索

前置要求
  • •Qdrant 服务器连接信息
  • •可能需要目标 API 的认证凭证

使用的节点 (17 个)

Set
Merge
Filter
SplitOut
Qdrant
Aggregate
StickyNote
HttpRequest
ManualTrigger
SplitInBatches

分类

未分类
工作流预览
可视化展示节点连接关系，支持缩放和平移
React Flow
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
  "id": "h81ddl7uooV3eLBq",
  "meta": {
    "instanceId": "d975180a7308eb9e1d0eb6c8833136580b02ced551ba46ad477d3b76dff98527",
    "templateCredsSetupCompleted": true
  },
  "name": "使用 Qdrant 和 n8n 的混合搜索，法律 AI：检索",
  "tags": [],
  "nodes": [
    {
      "id": "eb8d4dd7-f40b-4524-a9de-f9ef9eef0eca",
      "name": "从 HuggingFace 索引数据集",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -256,
        400
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "78030f66-5331-463f-ad22-9d09f477e3f9",
      "name": "全部分割",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        176,
        400
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "splits"
      },
      "typeVersion": 1
    },
    {
      "id": "e6d1e789-1293-480b-a163-992b0c7a2ae8",
      "name": "获取数据集分割",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -32,
        400
      ],
      "parameters": {
        "url": "https://datasets-server.huggingface.co/splits",
        "options": {},
        "sendQuery": true,
        "queryParameters": {
          "parameters": [
            {
              "name": "dataset",
              "value": "={{ $json.dataset }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "cb58241e-4579-4c5b-bd65-4a20f6cf3698",
      "name": "逐行划分",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        816,
        400
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "rows"
      },
      "typeVersion": 1
    },
    {
      "id": "2ee71c28-71fd-4cba-87c7-c9886fb403c7",
      "name": "保留测试分割",
      "type": "n8n-nodes-base.filter",
      "position": [
        384,
        400
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "52e3d8e2-825f-4e43-9d5f-e275d196b442",
              "operator": {
                "name": "filter.operator.equals",
                "type": "string",
                "operation": "equals"
              },
              "leftValue": "={{ $json.split }}",
              "rightValue": "test"
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "484a82fe-93d8-439b-bbb5-e96a4b5d7861",
      "name": "获取测试查询",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        592,
        400
      ],
      "parameters": {
        "url": "=https://datasets-server.huggingface.co/rows",
        "options": {},
        "sendQuery": true,
        "queryParameters": {
          "parameters": [
            {
              "name": "dataset",
              "value": "={{ $json.dataset }}"
            },
            {
              "name": "config",
              "value": "={{ $json.config }}"
            },
            {
              "name": "split",
              "value": "={{ $json.split }}"
            },
            {
              "name": "length",
              "value": "=100"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "20f67ae7-6631-4602-aa20-42a382db12ae",
      "name": "查询点",
      "type": "n8n-nodes-qdrant.qdrant",
      "position": [
        2144,
        416
      ],
      "parameters": {
        "limit": 1,
        "query": "{\n  \"fusion\": \"rrf\"\n}",
        "prefetch": "=[\n  {\n    \"query\": {\n      \"text\": \"{{ $json.question }}\",\n      \"model\": \"mixedbread-ai/mxbai-embed-large-v1\"\n    },\n    \"using\": \"mxbai_large\",\n    \"limit\": 25\n  },\n  {\n    \"query\": {\n      \"text\": \"{{ $json.question }}\",\n      \"model\": \"qdrant/bm25\"\n    },\n    \"using\": \"bm25\",\n    \"limit\": 25\n  }\n]",
        "resource": "search",
        "operation": "queryPoints",
        "collectionName": {
          "__rl": true,
          "mode": "list",
          "value": "legalQA_test",
          "cachedResultName": "legalQA_test"
        },
        "requestOptions": {}
      },
      "credentials": {
        "qdrantApi": {
          "id": "LVjhdCt8pAJjLyt5",
          "name": "Qdrant account 2"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "445ace25-f900-4bcf-9f7d-9bc1db662867",
      "name": "合并",
      "type": "n8n-nodes-base.merge",
      "position": [
        2320,
        608
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineAll"
      },
      "typeVersion": 3.2
    },
    {
      "id": "c631ce99-a672-499f-bbf3-e740ef431884",
      "name": "遍历项目",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        1776,
        400
      ],
      "parameters": {
        "options": {
          "reset": false
        }
      },
      "typeVersion": 3
    },
    {
      "id": "c075a745-ed50-459f-87dd-101a559e4523",
      "name": "保留数据集中有答案的问题",
      "type": "n8n-nodes-base.filter",
      "position": [
        1056,
        400
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "d1120153-1852-42c0-8b0a-084e8c3190d3",
              "operator": {
                "type": "number",
                "operation": "gt"
              },
              "leftValue": "={{ $json.row.answers.length }}",
              "rightValue": 0
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "94f78e9b-f9eb-4179-9844-d6e23bc79751",
      "name": "保留问题和 ID",
      "type": "n8n-nodes-base.set",
      "position": [
        1280,
        400
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "961c95d9-c803-404b-b4b6-cb66a8a33928",
              "name": "id_qa",
              "type": "string",
              "value": "={{ $json.row.id }}"
            },
            {
              "id": "0fefba06-4567-479c-9eb5-efbb3e13e743",
              "name": "question",
              "type": "string",
              "value": "={{ $json.row.question }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "08f67e31-ba8f-47fd-bc78-f352a160d4fd",
      "name": "聚合评估",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        2032,
        224
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData",
        "destinationFieldName": "eval"
      },
      "typeVersion": 1
    },
    {
      "id": "413ade44-d27d-4c49-862f-afb9d4e18bf6",
      "name": "评估中 isHits 的百分比",
      "type": "n8n-nodes-base.set",
      "position": [
        2256,
        224
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "5bca1a50-3e41-4f50-8362-cb7b185b50f6",
              "name": "Hits percentage",
              "type": "number",
              "value": "={{ ($json.eval.filter(item => item.isHit).length * 100) / $json.eval.length}}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "c0840c22-8954-4937-80d9-f32741b81e1e",
      "name": "便签 2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -96,
        144
      ],
      "parameters": {
        "color": 5,
        "width": 1520,
        "height": 464,
        "content": "## 从 Hugging Face 数据集获取用于评估检索的问题（已索引到 Qdrant）"
      },
      "typeVersion": 1
    },
    {
      "id": "742e68ae-0013-4dda-a818-4485ff80a986",
      "name": "便签 4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1696,
        -256
      ],
      "parameters": {
        "color": 5,
        "width": 1088,
        "height": 1120,
        "content": "## 检查法律问答数据集上简单混合搜索的质量"
      },
      "typeVersion": 1
    },
    {
      "id": "d4a32298-02ef-4f9e-b22d-3f30e9b74eb2",
      "name": "便签1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1344,
        -128
      ],
      "parameters": {
        "width": 1008,
        "height": 960,
        "content": "## 评估法律数据集上的混合搜索"
      },
      "typeVersion": 1
    },
    {
      "id": "56a5efd8-ed3f-46f7-85c8-966536f24a13",
      "name": "isHit = 是否找到正确答案",
      "type": "n8n-nodes-base.set",
      "position": [
        2512,
        608
      ],
      "parameters": {
        "include": "selected",
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "80089820-cc55-4b74-966e-b50a3f4b6e36",
              "name": "isHit",
              "type": "boolean",
              "value": "={{ $json.result.points[0].payload.ids_qa.includes($json.id_qa) }}"
            }
          ]
        },
        "includeFields": "id_qa,question",
        "includeOtherFields": true
      },
      "typeVersion": 3.4
    }
  ],
  "active": false,
  "pinData": {
    "Index Dataset from HuggingFace": [
      {
        "json": {
          "dataset": "isaacus/LegalQAEval"
        }
      }
    ]
  },
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "20b38566-7985-4139-98a3-6b275e85a9cb",
  "connections": {
    "Merge": {
      "main": [
        [
          {
            "node": "isHit = If we Found the Correct Answer",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Query Points": {
      "main": [
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Divide Per Row": {
      "main": [
        [
          {
            "node": "Keep Questions with Answers in the Dataset",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Aggregate Evals": {
      "main": [
        [
          {
            "node": "Percentage of isHits in Evals",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Keep Test Split": {
      "main": [
        [
          {
            "node": "Get Test Queries",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Loop Over Items": {
      "main": [
        [
          {
            "node": "Aggregate Evals",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 1
          },
          {
            "node": "Query Points",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get Test Queries": {
      "main": [
        [
          {
            "node": "Divide Per Row",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get Dataset Splits": {
      "main": [
        [
          {
            "node": "Split Them All Out",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Split Them All Out": {
      "main": [
        [
          {
            "node": "Keep Test Split",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Keep Questions & IDs": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Index Dataset from HuggingFace": {
      "main": [
        [
          {
            "node": "Get Dataset Splits",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "isHit = If we Found the Correct Answer": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Keep Questions with Answers in the Dataset": {
      "main": [
        [
          {
            "node": "Keep Questions & IDs",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
常见问题

如何使用这个工作流？

复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。

这个工作流适合什么场景？

这是一个高级难度的通用自动化工作流。适合高级用户，包含 16+ 个节点的复杂工作流

需要付费吗？

本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。

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节点数量17
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难度说明

适合高级用户，包含 16+ 个节点的复杂工作流

作者
Jenny

Qdrant DevRel, ML/NLP/math nerd with yapping skills

外部链接
在 n8n.io 上查看 →

分享此工作流