Agentset

TypeScript SDK for Agentset, an agentic RAG-as-a-service.

Installation

using npm:

npm install agentset

using yarn:

yarn add agentset

using pnpm:

pnpm add agentset

Getting Started

import { Agentset } from "agentset";

// Initialize the client
const agentset = new Agentset({
  apiKey: "your_api_key_here",
});

// Create a namespace
const namespace = await agentset.namespaces.create({
  name: "My Knowledge Base",
  // Optional: provide custom embedding model
  embeddingConfig: {
    provider: "OPENAI",
    model: "text-embedding-3-small",
    apiKey: "your_openai_api_key_here",
  },
});

// Get a namespace by ID or slug
const ns = agentset.namespace("my-knowledge-base");

// Ingest content
await ns.ingestion.create({
  payload: {
    type: "TEXT",
    text: "This is some content to ingest into the knowledge base.",
    name: "Introduction",
  },
});

// List all ingestion jobs
const { jobs, pagination } = await ns.ingestion.all();

// Get a specific ingestion job
const job = await ns.ingestion.get("job_id");

// List all documents
const { documents } = await ns.documents.all();

// Search the knowledge base
const results = await ns.search("What is Agentset?");

API Reference

Visit the full documentation for more details.

Custom Fetch Implementation

You can provide a custom fetch implementation:

import { Agentset } from "agentset";
import nodeFetch from "node-fetch";

const agentset = new Agentset({
  apiKey: "your_api_key_here",
  fetcher: nodeFetch,
});

Error Handling

The SDK provides typed errors that you can catch and handle:

import { Agentset, NotFoundError, UnauthorizedError } from "agentset";

try {
  const namespace = await agentset.namespaces.get("non-existent-id");
} catch (error) {
  if (error instanceof NotFoundError) {
    console.error("Namespace not found");
  } else if (error instanceof UnauthorizedError) {
    console.error("Invalid API key");
  } else {
    console.error("Unexpected error", error);
  }
}