llamaindex/tools/dist/index.js

<p align="center"> <img height="100" width="100" alt="LlamaIndex logo" src="https://ts.llamaindex.ai/square.svg" /> </p> <h1 align="center">LlamaIndex.TS</h1> <h3 align="center"> Data framework for your LLM application. </h3>

export * from '@llamaindex/core/tools';

const DEFAULT_NAME = "query_engine_tool";
const DEFAULT_DESCRIPTION = "Useful for running a natural language query against a knowledge base and get back a natural language response.";
const DEFAULT_PARAMETERS = {
    type: "object",
    properties: {
        query: {
            type: "string",
            description: "The query to search for"
        }
    },
    required: [
        "query"
    ]
};
class QueryEngineTool {
    constructor({ queryEngine, metadata, includeSourceNodes }){
        this.queryEngine = queryEngine;
        this.metadata = {
            name: metadata?.name ?? DEFAULT_NAME,
            description: metadata?.description ?? DEFAULT_DESCRIPTION,
            parameters: metadata?.parameters ?? DEFAULT_PARAMETERS
        };
        this.includeSourceNodes = includeSourceNodes ?? false;
    }
    async call({ query }) {
        const response = await this.queryEngine.query({
            query
        });
        if (!this.includeSourceNodes) {
            return {
                content: response.message.content
            };
        }
        // Use JSON.parse(JSON.stringify()) to remove undefined values from sourceNodes
        // since undefined is not a valid JSONValue
        return {
            content: response.message.content,
            sourceNodes: JSON.parse(JSON.stringify(response.sourceNodes ?? []))
        };
    }
}

export { QueryEngineTool };