Embeddings & Vector Store

Come vengono generati e utilizzati gli embeddings, e come interagiamo con Qdrant.

Generazione embeddings (via Worker)

/main/src/agentTools/qdrantService.ts

export async function generateEmbeddings(text: string): Promise<number[]> {
	const response = await addToQueue({ taskType: 'query:embedding', payload: { query: text } })
	return response.data.taskResult
}

Client Qdrant

/main/src/index.ts

export const qdrantClient = new QdrantClient({ url: process.env.QDRANT_URL, apiKey: process.env.QDRANT_API_KEY, port: 6333 })

Ricerca vettoriale

/main/src/agentTools/qdrantService.ts

const searchResult = await qdrantClient.search(collectionName, { vector: queryEmbedding.flat(), limit, filter })