StartGPT Node API Library

This library provides convenient access to the StartGPT REST API from TypeScript or JavaScript.

It is generated from our OpenAPI specification with Stainless.

To learn how to use the StartGPT API, check out our API Reference and Documentation.

Installation

npm install --save startgpt
# or
yarn add startgpt

You can import in Deno via:

import StartGPT from 'https://deno.land/x/[email protected]/mod.ts';

Usage

The full API of this library can be found in api.md file along with many code examples. The code below shows how to get started using the chat completions API.

import StartGPT from 'startgpt';

const startgpt = new StartGPT({
  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
});

async function main() {
  const chatCompletion = await startgpt.chat.completions.create({
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'gpt-3.5-turbo',
  });
}

main();

Streaming Responses

We provide support for streaming responses using Server Sent Events (SSE).

import StartGPT from 'startgpt';

const startgpt = new StartGPT();

async function main() {
  const stream = await startgpt.chat.completions.create({
    model: 'gpt-4',
    messages: [{ role: 'user', content: 'Say this is a test' }],
    stream: true,
  });
  for await (const chunk of stream) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
  }
}

main();

If you need to cancel a stream, you can break from the loop or call stream.controller.abort().

Request & Response types

This library includes TypeScript definitions for all request params and response fields. You may import and use them like so:

import StartGPT from 'startgpt';

const startgpt = new StartGPT({
  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
});

async function main() {
  const params: StartGPT.Chat.ChatCompletionCreateParams = {
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'gpt-3.5-turbo',
  };
  const chatCompletion: StartGPT.Chat.ChatCompletion = await startgpt.chat.completions.create(params);
}

main();

Documentation for each method, request param, and response field are available in docstrings and will appear on hover in most modern editors.

[!IMPORTANT] Previous versions of this SDK used a Configuration class. See the v3 to v4 migration guide.

Streaming responses

This library provides several conveniences for streaming chat completions, for example:

import StartGPT from 'startgpt';

const startgpt = new StartGPT();

async function main() {
  const stream = await startgpt.beta.chat.completions.stream({
    model: 'gpt-4',
    messages: [{ role: 'user', content: 'Say this is a test' }],
    stream: true,
  });

  stream.on('content', (delta, snapshot) => {
    process.stdout.write(delta);
  });

  // or, equivalently:
  for await (const chunk of stream) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
  }

  const chatCompletion = await stream.finalChatCompletion();
  console.log(chatCompletion); // {id: "…", choices: […], …}
}

main();

Streaming with startgpt.beta.chat.completions.stream({…}) exposes various helpers for your convenience including event handlers and promises.

Alternatively, you can use startgpt.chat.completions.create({ stream: true, … }) which only returns an async iterable of the chunks in the stream and thus uses less memory (it does not build up a final chat completion object for you).

If you need to cancel a stream, you can break from a for await loop or call stream.abort().

Automated function calls

We provide the startgpt.beta.chat.completions.runTools({…}) convenience helper for using function tool calls with the /chat/completions endpoint which automatically call the JavaScript functions you provide and sends their results back to the /chat/completions endpoint, looping as long as the model requests tool calls.

If you pass a parse function, it will automatically parse the arguments for you and returns any parsing errors to the model to attempt auto-recovery. Otherwise, the args will be passed to the function you provide as a string.

If you pass tool_choice: {function: {name: …}} instead of auto, it returns immediately after calling that function (and only loops to auto-recover parsing errors).

import StartGPT from 'startgpt';

const client = new StartGPT();

async function main() {
  const runner = client.beta.chat.completions
    .runTools({
      model: 'gpt-3.5-turbo',
      messages: [{ role: 'user', content: 'How is the weather this week?' }],
      tools: [
        {
          type: 'function',
          function: {
            function: getCurrentLocation,
            parameters: { type: 'object', properties: {} },
          },
        },
        {
          type: 'function',
          function: {
            function: getWeather,
            parse: JSON.parse, // or use a validation library like zod for typesafe parsing.
            parameters: {
              type: 'object',
              properties: {
                location: { type: 'string' },
              },
            },
          },
        },
      ],
    })
    .on('message', (message) => console.log(message));

  const finalContent = await runner.finalContent();
  console.log();
  console.log('Final content:', finalContent);
}

async function getCurrentLocation() {
  return 'Boston'; // Simulate lookup
}

async function getWeather(args: { location: string }) {
  const { location } = args;
  // … do lookup …
  return { temperature, precipitation };
}

main();

// {role: "user",      content: "How's the weather this week?"}
// {role: "assistant", tool_calls: [{type: "function", function: {name: "getCurrentLocation", arguments: "{}"}, id: "123"}
// {role: "tool",      name: "getCurrentLocation", content: "Boston", tool_call_id: "123"}
// {role: "assistant", tool_calls: [{type: "function", function: {name: "getWeather", arguments: '{"location": "Boston"}'}, id: "1234"}]}
// {role: "tool",      name: "getWeather", content: '{"temperature": "50degF", "preciptation": "high"}', tool_call_id: "1234"}
// {role: "assistant", content: "It's looking cold and rainy - you might want to wear a jacket!"}
//
// Final content: "It's looking cold and rainy - you might want to wear a jacket!"

Like with .stream(), we provide a variety of helpers and events.

Note that runFunctions was previously available as well, but has been deprecated in favor of runTools.

Read more about various examples such as with integrating with zod, next.js, and proxying a stream to the browser.

File Uploads

Request parameters that correspond to file uploads can be passed in many different forms:

• File (or an object with the same structure)
• a fetch Response (or an object with the same structure)
• an fs.ReadStream
• the return value of our toFile helper

import fs from 'fs';
import fetch from 'node-fetch';
import StartGPT, { toFile } from 'startgpt';

const startgpt = new StartGPT();

// If you have access to Node `fs` we recommend using `fs.createReadStream()`:
await startgpt.files.create({ file: fs.createReadStream('input.jsonl'), purpose: 'fine-tune' });

// Or if you have the web `File` API you can pass a `File` instance:
await startgpt.files.create({ file: new File(['my bytes'], 'input.jsonl'), purpose: 'fine-tune' });

// You can also pass a `fetch` `Response`:
await startgpt.files.create({ file: await fetch('https://somesite/input.jsonl'), purpose: 'fine-tune' });

// Finally, if none of the above are convenient, you can use our `toFile` helper:
await startgpt.files.create({
  file: await toFile(Buffer.from('my bytes'), 'input.jsonl'),
  purpose: 'fine-tune',
});
await startgpt.files.create({
  file: await toFile(new Uint8Array([0, 1, 2]), 'input.jsonl'),
  purpose: 'fine-tune',
});

Handling errors

When the library is unable to connect to the API, or if the API returns a non-success status code (i.e., 4xx or 5xx response), a subclass of APIError will be thrown:

async function main() {
  const job = await startgpt.fineTuning.jobs
    .create({ model: 'gpt-3.5-turbo', training_file: 'file-abc123' })
    .catch((err) => {
      if (err instanceof StartGPT.APIError) {
        console.log(err.status); // 400
        console.log(err.name); // BadRequestError
        console.log(err.headers); // {server: 'nginx', ...}
      } else {
        throw err;
      }
    });
}

main();

Error codes are as followed:

| Status Code | Error Type | | ----------- | -------------------------- | | 400 | BadRequestError | | 401 | AuthenticationError | | 403 | PermissionDeniedError | | 404 | NotFoundError | | 422 | UnprocessableEntityError | | 429 | RateLimitError | | >=500 | InternalServerError | | N/A | APIConnectionError |

Azure StartGPT

An example of using this library with Azure StartGPT can be found here.

Please note there are subtle differences in API shape & behavior between the Azure StartGPT API and the StartGPT API, so using this library with Azure StartGPT may result in incorrect types, which can lead to bugs.

See @azure/startgpt for an Azure-specific SDK provided by Microsoft.

Retries

Certain errors will be automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors will all be retried by default.

You can use the maxRetries option to configure or disable this:

// Configure the default for all requests:
const startgpt = new StartGPT({
  maxRetries: 0, // default is 2
});

// Or, configure per-request:
await startgpt.chat.completions.create({ messages: [{ role: 'user', content: 'How can I get the name of the current day in Node.js?' }], model: 'gpt-3.5-turbo' }, {
  maxRetries: 5,
});

Timeouts

Requests time out after 10 minutes by default. You can configure this with a timeout option:

// Configure the default for all requests:
const startgpt = new StartGPT({
  timeout: 20 * 1000, // 20 seconds (default is 10 minutes)
});

// Override per-request:
await startgpt.chat.completions.create({ messages: [{ role: 'user', content: 'How can I list all files in a directory using Python?' }], model: 'gpt-3.5-turbo' }, {
  timeout: 5 * 1000,
});

On timeout, an APIConnectionTimeoutError is thrown.

Note that requests which time out will be retried twice by default.

Auto-pagination

List methods in the StartGPT API are paginated. You can use for await … of syntax to iterate through items across all pages:

async function fetchAllFineTuningJobs(params) {
  const allFineTuningJobs = [];
  // Automatically fetches more pages as needed.
  for await (const fineTuningJob of startgpt.fineTuning.jobs.list({ limit: 20 })) {
    allFineTuningJobs.push(fineTuningJob);
  }
  return allFineTuningJobs;
}

Alternatively, you can make request a single page at a time:

let page = await startgpt.fineTuning.jobs.list({ limit: 20 });
for (const fineTuningJob of page.data) {
  console.log(fineTuningJob);
}

// Convenience methods are provided for manually paginating:
while (page.hasNextPage()) {
  page = page.getNextPage();
  // ...
}

Advanced Usage

Accessing raw Response data (e.g., headers)

The "raw" Response returned by fetch() can be accessed through the .asResponse() method on the APIPromise type that all methods return.

You can also use the .withResponse() method to get the raw Response along with the parsed data.

const startgpt = new StartGPT();

const response = await startgpt.chat.completions
  .create({ messages: [{ role: 'user', content: 'Say this is a test' }], model: 'gpt-3.5-turbo' })
  .asResponse();
console.log(response.headers.get('X-My-Header'));
console.log(response.statusText); // access the underlying Response object

const { data: chatCompletion, response: raw } = await startgpt.chat.completions
  .create({ messages: [{ role: 'user', content: 'Say this is a test' }], model: 'gpt-3.5-turbo' })
  .withResponse();
console.log(raw.headers.get('X-My-Header'));
console.log(chatCompletion);

Customizing the fetch client

By default, this library uses node-fetch in Node, and expects a global fetch function in other environments.

If you would prefer to use a global, web-standards-compliant fetch function even in a Node environment, (for example, if you are running Node with --experimental-fetch or using NextJS which polyfills with undici), add the following import before your first import from "StartGPT":

// Tell TypeScript and the package to use the global web fetch instead of node-fetch.
// Note, despite the name, this does not add any polyfills, but expects them to be provided if needed.
import 'startgpt/shims/web';
import StartGPT from 'startgpt';

To do the inverse, add import "startgpt/shims/node" (which does import polyfills). This can also be useful if you are getting the wrong TypeScript types for Response - more details here.

You may also provide a custom fetch function when instantiating the client, which can be used to inspect or alter the Request or Response before/after each request:

import { fetch } from 'undici'; // as one example
import StartGPT from 'startgpt';

const client = new StartGPT({
  fetch: async (url: RequestInfo, init?: RequestInfo): Promise<Response> => {
    console.log('About to make a request', url, init);
    const response = await fetch(url, init);
    console.log('Got response', response);
    return response;
  },
});

Note that if given a DEBUG=true environment variable, this library will log all requests and responses automatically. This is intended for debugging purposes only and may change in the future without notice.

Configuring an HTTP(S) Agent (e.g., for proxies)

By default, this library uses a stable agent for all http/https requests to reuse TCP connections, eliminating many TCP & TLS handshakes and shaving around 100ms off most requests.

If you would like to disable or customize this behavior, for example to use the API behind a proxy, you can pass an httpAgent which is used for all requests (be they http or https), for example:

import http from 'http';
import HttpsProxyAgent from 'https-proxy-agent';

// Configure the default for all requests:
const startgpt = new StartGPT({
  httpAgent: new HttpsProxyAgent(process.env.PROXY_URL),
});

// Override per-request:
await startgpt.models.list({
  baseURL: 'http://localhost:8080/test-api',
  httpAgent: new http.Agent({ keepAlive: false }),
})

Semantic Versioning

This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:

1. Changes that only affect static types, without breaking runtime behavior.
2. Changes to library internals which are technically public but not intended or documented for external use. (Please open a GitHub issue to let us know if you are relying on such internals).
3. Changes that we do not expect to impact the vast majority of users in practice.

We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.

We are keen for your feedback; please open an issue with questions, bugs, or suggestions.

Requirements

TypeScript >= 4.5 is supported.

The following runtimes are supported:

• Node.js 18 LTS or later (non-EOL) versions.
• Deno v1.28.0 or higher, using import StartGPT from "npm:startgpt".
• Bun 1.0 or later.
• Cloudflare Workers.
• Vercel Edge Runtime.
• Jest 28 or greater with the "node" environment ("jsdom" is not supported at this time).
• Nitro v2.6 or greater.

Note that React Native is not supported at this time.

If you are interested in other runtime environments, please open or upvote an issue on GitHub.