Google scholar 集成

使用 LangChain JavaScript 集成 Google scholar tool。

This notebook provides a quick overview for getting started with SERPGoogleScholarTool. For detailed documentation of all SERPGoogleScholarAPITool features and configurations, head to the API reference.

概述

集成详情

Class	Package	PY support	Version
GoogleScholarTool	@langchain/community	✅

Tool features

• Retrieve academic publications by topic, author, or query.
• Fetch metadata such as title, author, and publication year.
• Advanced search filters, including citation count and journal name.

设置

The integration lives in the @langchain/community package.

npm install @langchain/community

凭证

Ensure you have the appropriate API key to access Google Scholar. Set it in your environment variables:

SERPAPI_API_KEY="your-serp-api-key"

It’s also helpful to set up LangSmith for best-in-class observability:

process.env.LANGSMITH_TRACING="true"
process.env.LANGSMITH_API_KEY="your-langchain-api-key"

实例化

You can import and instantiate an instance of the SERPGoogleScholarAPITool tool like this:

import { SERPGoogleScholarAPITool } from "@langchain/community/tools/google_scholar";

const tool = new SERPGoogleScholarAPITool({
  apiKey: process.env.SERPAPI_API_KEY,
});

调用

Invoke directly with args

You can invoke the tool directly with query arguments:

const results = await tool.invoke({
  query: "neural networks",
  maxResults: 5,
});

console.log(results);

Invoke with ToolCall

We can also invoke the tool with a model-generated ToolCall:

const modelGeneratedToolCall = {
  args: { query: "machine learning" },
  id: "1",
  name: tool.name,
  type: "tool_call",
};
await tool.invoke(modelGeneratedToolCall);

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API 参考

有关所有 SERPGoogleScholarAPITool features and configurations, 的详细文档，请前往 API 参考。

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