学习排序

学习排序是一种机器学习技术，允许您训练一个模型来对搜索结果进行排序。该模型使用一组特征和一组相关性判断进行训练。然后，该模型用于对搜索结果进行排序。

在本指南中，您将学习如何将学习排序与 Metarank 和 Searchkit 集成。您可以在 Metarank 文档 (在新标签页中打开) 中了解有关 Metarank 的学习排序的更多信息。

在本指南中，我们假设您已

安装 Metarank 和 Searchkit
使用 Metarank 训练了一个模型
为您的模型设置了特征和相关性判断

Searchkit UI 的更改

Metarank 要求在每次搜索请求中发送会话 ID 和用户 ID。一种方法是在 @searchkit/instantsearch-client 中，并通过标头提供会话 ID 和用户 ID

const searchClient = Client({
  url: "/api/search",
  headers: {
    "x-session-id": "my-session-id",
    "x-user-id": "my-user-id",
  },
});

Searchkit API 的更改

为了将学习排序与 Searchkit 集成，我们将使用 beforeSearch 和 afterSearch 的钩子。这些钩子允许我们在查询和结果发送到 Elasticsearch 并返回到 UI 之前修改它们。

我们将使用 afterSearch 钩子将结果发送到 Metarank API 并使用新顺序更新结果。

export default async function handler(req: NextApiRequest, res: NextApiResponse) {
 
  const headers = req.headers
  
  const results = await client.handleRequest(req.body, {
    hooks: {
      afterSearch: async (searchRequests, searchResponses) => {
        // Get the first search request
        const [uiRequest, otherRequests] = searchRequests;
        // Get the first search response
        const [uiResponse, otherResponses] = searchResponses;
 
        // Get the session id and user id from the headers
        const sessionId = headers["x-session-id"];
        const userId = headers["x-user-id"];
 
        // Get the query from the first search request
        const query = uiRequest.body.query;
 
        // Get the results from the first search response
        const results = uiResponse.body.hits.hits;
 
 
        // Send the request to the Metarank API
        const response = await fetch("https://127.0.0.1:8080/rank/xgboost", {
          method: "POST",
          headers: {
            "Content-Type": "application/json",
          },
          body: JSON.stringify({
            session: sessionId,
            user: userId,
            fields: [ 
              { name: "query", value: query }
            ],
            timestamp: (new Date()).getTime(),
            items: results.map((item) => {
              return {
                id: item._id,
                // an optional array of extra fields that you can use in your model
                fields: [
                  { name: "title", value: item._source.title },
                  { name: "description", value: item._source.description },
                  { name: "url", value: item._source.url },
                ],
              };
            }})
          }),
        });
 
        // Get the response from the Metarank API
        const metarankResponse = await response.json();
 
        // Get the items order from the response
        const items = metarankResponse.items;
 
        // Update the order of the results for the first 20 results
        const updatedResults = items.map((item) => {
          const result = results.find((result) => result._id === item.id);
          return result
        });
 
        // Update the results in the first search response
        const updatedUiResponse = {
          ...uiResponse,
          body: {
            ...uiResponse.body,
            hits: {
              ...uiResponse.body.hits,
              hits: updatedResults,
            },
          },
        };
 
        return [
          updatedUiResponse,
          ...otherResponses
        ];
      }
    }
  });
 
}

用户限制的数据访问从 Algolia 迁移到 Elasticsearch