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iris-sdk

Developer-friendly & type-safe Typescript SDK specifically catered to leverage iris-sdk API.



Important

This SDK is not yet ready for production use. To complete setup please follow the steps outlined in your workspace. Delete this section before > publishing to a package manager.

Summary

Zenobia Intelligent Automation Platform API: Zenobia is an intelligent automation platform that learns from demonstrations and transforms them into robust workflows.

Key Features

  • Demonstration-Based Learning: Create automation by showing how tasks are performed
  • Video Analysis: Convert screen recordings into precise automation instructions
  • Task Recording & Replay: Record workflows and replay them with the same or different parameters
  • RPA Process Generation: Automatically convert recordings into parameterized workflows
  • Action Caching: Efficiently reuse automation steps across different tasks
  • Multi-operator Support: Control browsers or native desktop applications

The API enables developers to create automation that can handle complex real-world tasks through a combination of visual analysis, session recording, and parameterized execution.

Table of Contents

SDK Installation

Tip

To finish publishing your SDK to npm and others you must run your first generation action.

The SDK can be installed with either npm, pnpm, bun or yarn package managers.

NPM

npm add https://github.com/iris-networks/iris-sdk

PNPM

pnpm add https://github.com/iris-networks/iris-sdk

Bun

bun add https://github.com/iris-networks/iris-sdk

Yarn

yarn add https://github.com/iris-networks/iris-sdk zod

# Note that Yarn does not install peer dependencies automatically. You will need
# to install zod as shown above.

Model Context Protocol (MCP) Server

This SDK is also an installable MCP server where the various SDK methods are exposed as tools that can be invoked by AI applications.

Node.js v20 or greater is required to run the MCP server from npm.

Claude installation steps

Add the following server definition to your claude_desktop_config.json file:

{
  "mcpServers": {
    "IrisSDK": {
      "command": "npx",
      "args": [
        "-y", "--package", "iris-sdk",
        "--",
        "mcp", "start"
      ]
    }
  }
}
Cursor installation steps

Create a .cursor/mcp.json file in your project root with the following content:

{
  "mcpServers": {
    "IrisSDK": {
      "command": "npx",
      "args": [
        "-y", "--package", "iris-sdk",
        "--",
        "mcp", "start"
      ]
    }
  }
}

You can also run MCP servers as a standalone binary with no additional dependencies. You must pull these binaries from available Github releases:

curl -L -o mcp-server \
    https://github.com/{org}/{repo}/releases/download/{tag}/mcp-server-bun-darwin-arm64 && \
chmod +x mcp-server

If the repo is a private repo you must add your Github PAT to download a release -H "Authorization: Bearer {GITHUB_PAT}".

{
  "mcpServers": {
    "Todos": {
      "command": "./DOWNLOAD/PATH/mcp-server",
      "args": [
        "start"
      ]
    }
  }
}

For a full list of server arguments, run:

npx -y --package iris-sdk -- mcp start --help

Requirements

For supported JavaScript runtimes, please consult RUNTIMES.md.

SDK Example Usage

Example

import { IrisSDK } from "iris-sdk";

const irisSDK = new IrisSDK();

async function run() {
  const result = await irisSDK.config.get();

  // Handle the result
  console.log(result);
}

run();

Available Resources and Operations

Available methods

config

  • get - Get current configuration
  • update - Update configuration

files

humanLayer

  • getRequests - Get all pending human layer requests
  • approve - Approve a pending human layer request

irisArtifacts

  • list - List artifacts in a directory within the .iris folder
  • downloadFile - Download a file artifact from the .iris folder
  • downloadFolder - Download a directory of artifacts as a zip file

operators

  • getTypes - Get available operator types

rpa

video

videoEditing

videos

Standalone functions

All the methods listed above are available as standalone functions. These functions are ideal for use in applications running in the browser, serverless runtimes or other environments where application bundle size is a primary concern. When using a bundler to build your application, all unused functionality will be either excluded from the final bundle or tree-shaken away.

To read more about standalone functions, check FUNCTIONS.md.

Available standalone functions

File uploads

Certain SDK methods accept files as part of a multi-part request. It is possible and typically recommended to upload files as a stream rather than reading the entire contents into memory. This avoids excessive memory consumption and potentially crashing with out-of-memory errors when working with very large files. The following example demonstrates how to attach a file stream to a request.

Tip

Depending on your JavaScript runtime, there are convenient utilities that return a handle to a file without reading the entire contents into memory:

  • Node.js v20+: Since v20, Node.js comes with a native openAsBlob function in node:fs.
  • Bun: The native Bun.file function produces a file handle that can be used for streaming file uploads.
  • Browsers: All supported browsers return an instance to a File when reading the value from an <input type="file"> element.
  • Node.js v18: A file stream can be created using the fileFrom helper from fetch-blob/from.js.
import { IrisSDK } from "iris-sdk";
import { openAsBlob } from "node:fs";

const irisSDK = new IrisSDK();

async function run() {
  const result = await irisSDK.video.upload({
    file: await openAsBlob("example.file"),
  });

  // Handle the result
  console.log(result);
}

run();

Retries

Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.

To change the default retry strategy for a single API call, simply provide a retryConfig object to the call:

import { IrisSDK } from "iris-sdk";

const irisSDK = new IrisSDK();

async function run() {
  const result = await irisSDK.config.get({
    retries: {
      strategy: "backoff",
      backoff: {
        initialInterval: 1,
        maxInterval: 50,
        exponent: 1.1,
        maxElapsedTime: 100,
      },
      retryConnectionErrors: false,
    },
  });

  // Handle the result
  console.log(result);
}

run();

If you'd like to override the default retry strategy for all operations that support retries, you can provide a retryConfig at SDK initialization:

import { IrisSDK } from "iris-sdk";

const irisSDK = new IrisSDK({
  retryConfig: {
    strategy: "backoff",
    backoff: {
      initialInterval: 1,
      maxInterval: 50,
      exponent: 1.1,
      maxElapsedTime: 100,
    },
    retryConnectionErrors: false,
  },
});

async function run() {
  const result = await irisSDK.config.get();

  // Handle the result
  console.log(result);
}

run();

Error Handling

If the request fails due to, for example 4XX or 5XX status codes, it will throw a APIError.

Error Type Status Code Content Type
errors.APIError 4XX, 5XX */* 
import { IrisSDK } from "iris-sdk";
import { SDKValidationError } from "iris-sdk/models/errors";

const irisSDK = new IrisSDK();

async function run() {
  let result;
  try {
    result = await irisSDK.config.get();

    // Handle the result
    console.log(result);
  } catch (err) {
    switch (true) {
      // The server response does not match the expected SDK schema
      case (err instanceof SDKValidationError):
        {
          // Pretty-print will provide a human-readable multi-line error message
          console.error(err.pretty());
          // Raw value may also be inspected
          console.error(err.rawValue);
          return;
        }
        apierror.js;
      // Server returned an error status code or an unknown content type
      case (err instanceof APIError): {
        console.error(err.statusCode);
        console.error(err.rawResponse.body);
        return;
      }
      default: {
        // Other errors such as network errors, see HTTPClientErrors for more details
        throw err;
      }
    }
  }
}

run();

Validation errors can also occur when either method arguments or data returned from the server do not match the expected format. The SDKValidationError that is thrown as a result will capture the raw value that failed validation in an attribute called rawValue. Additionally, a pretty() method is available on this error that can be used to log a nicely formatted multi-line string since validation errors can list many issues and the plain error string may be difficult read when debugging.

In some rare cases, the SDK can fail to get a response from the server or even make the request due to unexpected circumstances such as network conditions. These types of errors are captured in the models/errors/httpclienterrors.ts module:

HTTP Client Error Description
RequestAbortedError HTTP request was aborted by the client
RequestTimeoutError HTTP request timed out due to an AbortSignal signal
ConnectionError HTTP client was unable to make a request to a server
InvalidRequestError Any input used to create a request is invalid
UnexpectedClientError Unrecognised or unexpected error

Server Selection

Override Server URL Per-Client

The default server can be overridden globally by passing a URL to the serverURL: string optional parameter when initializing the SDK client instance. For example:

import { IrisSDK } from "iris-sdk";

const irisSDK = new IrisSDK({
  serverURL: "http://0.0.0.0:3000",
});

async function run() {
  const result = await irisSDK.config.get();

  // Handle the result
  console.log(result);
}

run();

Custom HTTP Client

The TypeScript SDK makes API calls using an HTTPClient that wraps the native Fetch API. This client is a thin wrapper around fetch and provides the ability to attach hooks around the request lifecycle that can be used to modify the request or handle errors and response.

The HTTPClient constructor takes an optional fetcher argument that can be used to integrate a third-party HTTP client or when writing tests to mock out the HTTP client and feed in fixtures.

The following example shows how to use the "beforeRequest" hook to to add a custom header and a timeout to requests and how to use the "requestError" hook to log errors:

import { IrisSDK } from "iris-sdk";
import { HTTPClient } from "iris-sdk/lib/http";

const httpClient = new HTTPClient({
  // fetcher takes a function that has the same signature as native `fetch`.
  fetcher: (request) => {
    return fetch(request);
  }
});

httpClient.addHook("beforeRequest", (request) => {
  const nextRequest = new Request(request, {
    signal: request.signal || AbortSignal.timeout(5000)
  });

  nextRequest.headers.set("x-custom-header", "custom value");

  return nextRequest;
});

httpClient.addHook("requestError", (error, request) => {
  console.group("Request Error");
  console.log("Reason:", `${error}`);
  console.log("Endpoint:", `${request.method} ${request.url}`);
  console.groupEnd();
});

const sdk = new IrisSDK({ httpClient });

Debugging

You can setup your SDK to emit debug logs for SDK requests and responses.

You can pass a logger that matches console's interface as an SDK option.

Warning

Beware that debug logging will reveal secrets, like API tokens in headers, in log messages printed to a console or files. It's recommended to use this feature only during local development and not in production.

import { IrisSDK } from "iris-sdk";

const sdk = new IrisSDK({ debugLogger: console });

You can also enable a default debug logger by setting an environment variable IRISSDK_DEBUG to true.

Development

Maturity

This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version.

Contributions

While we value open-source contributions to this SDK, this library is generated programmatically. Any manual changes added to internal files will be overwritten on the next generation. We look forward to hearing your feedback. Feel free to open a PR or an issue with a proof of concept and we'll do our best to include it in a future release.

SDK Created by Speakeasy

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SDK for all things IRIS

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