Skip to main content

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.

Overview​

Integration details​

ClassPackagePY supportPackage latest
GoogleScholarTool@langchain/community✅NPM - Version

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.

Setup​

The integration lives in the @langchain/community package.

npm install @langchain/community

Credentials​

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

process.env.GOOGLE_SCHOLAR_API_KEY = "your-serp-api-key";

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

process.env.LANGCHAIN_TRACING_V2 = "true";
process.env.LANGCHAIN_API_KEY = "your-langchain-api-key";

Instantiation​

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,
});

Invocation​

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);

API reference​

For detailed documentation of all SERPGoogleScholarAPITool features and configurations, head to the API reference.

Was this page helpful?


You can also leave detailed feedback on GitHub.