adk-typescript
Version:
TypeScript port of Google's Agent Development Kit (ADK)
56 lines (55 loc) • 2.13 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.FilesRetrieval = void 0;
const LlamaIndexRetrieval_1 = require("./LlamaIndexRetrieval");
/**
* Retrieval tool that uses LlamaIndex to retrieve information from files
*/
class FilesRetrieval extends LlamaIndexRetrieval_1.LlamaIndexRetrieval {
/**
* Create a new Files retrieval tool
*
* @param options Options for the Files retrieval tool
*/
constructor(options) {
console.log(`Loading data from ${options.inputDir}`);
// In the Python implementation, this uses SimpleDirectoryReader and VectorStoreIndex
// Since we don't have direct LlamaIndex bindings in TypeScript, we create a placeholder
// retriever object that would be replaced with actual implementation when available
const retriever = createVectorIndexFromDirectory(options.inputDir);
super({
...options,
retriever
});
this.inputDir = options.inputDir;
}
}
exports.FilesRetrieval = FilesRetrieval;
/**
* Create a vector index from a directory
*
* This is a placeholder function that would be replaced with actual LlamaIndex
* implementation when TypeScript bindings are available
*
* @param inputDir Directory containing files to index
* @returns A retriever object
*/
function createVectorIndexFromDirectory(inputDir) {
// This is a placeholder implementation
// In a real implementation, this would:
// 1. Use SimpleDirectoryReader to load documents from the directory
// 2. Create a VectorStoreIndex from those documents
// 3. Return the index as a retriever
console.log(`Creating vector index from directory: ${inputDir}`);
return {
retrieve: async (query) => {
console.log(`Querying vector index for: ${query}`);
return [
{
text: `This is a placeholder response for "${query}". In a real implementation, ` +
`this would search documents in "${inputDir}" using LlamaIndex.`
}
];
}
};
}