Scale GP TypeScript API Library

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This library provides convenient access to the Scale GP REST API from server-side TypeScript or JavaScript.

The REST API documentation can be found on docs.gp.scale.com. The full API of this library can be found in api.md.

It is generated with Stainless.

Installation

npm install scale-gp

Usage

The full API of this library can be found in api.md.

import SGPClient from 'scale-gp';

const client = new SGPClient({
  accountID: 'My Account ID',
  apiKey: process.env['SGP_API_KEY'], // This is the default and can be omitted
  environment: 'development', // defaults to 'production'
});

const completion = await client.chat.completions.create({
  messages: [{ foo: 'bar' }],
  model: 'model',
  top_k: 2,
});

Streaming responses

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

import SGPClient from 'scale-gp';

const client = new SGPClient();

const stream = await client.chat.completions.create({
  messages: [{ foo: 'bar' }],
  model: 'model',
  stream: true,
});
for await (const chatCompletionChunk of stream) {
  console.log(chatCompletionChunk);
}

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 SGPClient from 'scale-gp';

const client = new SGPClient({
  accountID: 'My Account ID',
  apiKey: process.env['SGP_API_KEY'], // This is the default and can be omitted
  environment: 'development', // defaults to 'production'
});

const params: SGPClient.Chat.CompletionCreateParams = { messages: [{ foo: 'bar' }], model: 'model' };
const completion: SGPClient.Chat.CompletionCreateResponse = await client.chat.completions.create(params);

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

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 SGPClient, { toFile } from 'scale-gp';

const client = new SGPClient();

// If you have access to Node `fs` we recommend using `fs.createReadStream()`:
await client.files.create({ file: fs.createReadStream('/path/to/file') });

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

// You can also pass a `fetch` `Response`:
await client.files.create({ file: await fetch('https://somesite/file') });

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

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:

const completion = await client.chat.completions
  .create({ messages: [{ foo: 'bar' }], model: 'model' })
  .catch(async (err) => {
    if (err instanceof SGPClient.APIError) {
      console.log(err.status); // 400
      console.log(err.name); // BadRequestError
      console.log(err.headers); // {server: 'nginx', ...}
    } else {
      throw err;
    }
  });

Error codes are as follows:

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

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 client = new SGPClient({
  accountID: 'My Account ID',
  maxRetries: 0, // default is 2
});

// Or, configure per-request:
await client.chat.completions.create({ messages: [{ foo: 'bar' }], model: 'model' }, {
  maxRetries: 5,
});

Timeouts

Requests time out after 1 minute by default. You can configure this with a timeout option:

// Configure the default for all requests:
const client = new SGPClient({
  accountID: 'My Account ID',
  timeout: 20 * 1000, // 20 seconds (default is 1 minute)
});

// Override per-request:
await client.chat.completions.create({ messages: [{ foo: 'bar' }], model: 'model' }, {
  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 SGPClient API are paginated. You can use the for await … of syntax to iterate through items across all pages:

async function fetchAllInferenceModels(params) {
  const allInferenceModels = [];
  // Automatically fetches more pages as needed.
  for await (const inferenceModel of client.models.list({ limit: 10 })) {
    allInferenceModels.push(inferenceModel);
  }
  return allInferenceModels;
}

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

let page = await client.models.list({ limit: 10 });
for (const inferenceModel of page.items) {
  console.log(inferenceModel);
}

// Convenience methods are provided for manually paginating:
while (page.hasNextPage()) {
  page = await 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. This method returns as soon as the headers for a successful response are received and does not consume the response body, so you are free to write custom parsing or streaming logic.

You can also use the .withResponse() method to get the raw Response along with the parsed data. Unlike .asResponse() this method consumes the body, returning once it is parsed.

const client = new SGPClient();

const response = await client.chat.completions
  .create({ messages: [{ foo: 'bar' }], model: 'model' })
  .asResponse();
console.log(response.headers.get('X-My-Header'));
console.log(response.statusText); // access the underlying Response object

const { data: completion, response: raw } = await client.chat.completions
  .create({ messages: [{ foo: 'bar' }], model: 'model' })
  .withResponse();
console.log(raw.headers.get('X-My-Header'));
console.log(completion);

Logging

Important

All log messages are intended for debugging only. The format and content of log messages may change between releases.

Log levels

The log level can be configured in two ways:

Via the SGP_CLIENT_LOG environment variable
Using the logLevel client option (overrides the environment variable if set)

import SGPClient from 'scale-gp';

const client = new SGPClient({
  logLevel: 'debug', // Show all log messages
});

Available log levels, from most to least verbose:

'debug' - Show debug messages, info, warnings, and errors
'info' - Show info messages, warnings, and errors
'warn' - Show warnings and errors (default)
'error' - Show only errors
'off' - Disable all logging

At the 'debug' level, all HTTP requests and responses are logged, including headers and bodies. Some authentication-related headers are redacted, but sensitive data in request and response bodies may still be visible.

Custom logger

By default, this library logs to globalThis.console. You can also provide a custom logger. Most logging libraries are supported, including pino, winston, bunyan, consola, signale, and @std/log. If your logger doesn't work, please open an issue.

When providing a custom logger, the logLevel option still controls which messages are emitted, messages below the configured level will not be sent to your logger.

import SGPClient from 'scale-gp';
import pino from 'pino';

const logger = pino();

const client = new SGPClient({
  logger: logger.child({ name: 'SGPClient' }),
  logLevel: 'debug', // Send all messages to pino, allowing it to filter
});

Making custom/undocumented requests

This library is typed for convenient access to the documented API. If you need to access undocumented endpoints, params, or response properties, the library can still be used.

Undocumented endpoints

To make requests to undocumented endpoints, you can use client.get, client.post, and other HTTP verbs. Options on the client, such as retries, will be respected when making these requests.

await client.post('/some/path', {
  body: { some_prop: 'foo' },
  query: { some_query_arg: 'bar' },
});

Undocumented request params

To make requests using undocumented parameters, you may use // @ts-expect-error on the undocumented parameter. This library doesn't validate at runtime that the request matches the type, so any extra values you send will be sent as-is.

client.chat.completions.create({
  // ...
  // @ts-expect-error baz is not yet public
  baz: 'undocumented option',
});

For requests with the GET verb, any extra params will be in the query, all other requests will send the extra param in the body.

If you want to explicitly send an extra argument, you can do so with the query, body, and headers request options.

Undocumented response properties

To access undocumented response properties, you may access the response object with // @ts-expect-error on the response object, or cast the response object to the requisite type. Like the request params, we do not validate or strip extra properties from the response from the API.

Customizing the fetch client

By default, this library expects a global fetch function is defined.

If you want to use a different fetch function, you can either polyfill the global:

import fetch from 'my-fetch';

globalThis.fetch = fetch;

Or pass it to the client:

import SGPClient from 'scale-gp';
import fetch from 'my-fetch';

const client = new SGPClient({ fetch });

Fetch options

If you want to set custom fetch options without overriding the fetch function, you can provide a fetchOptions object when instantiating the client or making a request. (Request-specific options override client options.)

import SGPClient from 'scale-gp';

const client = new SGPClient({
  fetchOptions: {
    // `RequestInit` options
  },
});

Configuring proxies

To modify proxy behavior, you can provide custom fetchOptions that add runtime-specific proxy options to requests:

Node ^[docs]

import SGPClient from 'scale-gp';
import * as undici from 'undici';

const proxyAgent = new undici.ProxyAgent('http://localhost:8888');
const client = new SGPClient({
  fetchOptions: {
    dispatcher: proxyAgent,
  },
});

Bun ^[docs]

import SGPClient from 'scale-gp';

const client = new SGPClient({
  fetchOptions: {
    proxy: 'http://localhost:8888',
  },
});

Deno ^[docs]

import SGPClient from 'npm:scale-gp';

const httpClient = Deno.createHttpClient({ proxy: { url: 'http://localhost:8888' } });
const client = new SGPClient({
  fetchOptions: {
    client: httpClient,
  },
});

Frequently Asked Questions

Semantic versioning

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

Changes that only affect static types, without breaking runtime behavior.
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.)
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 >= 4.9 is supported.

The following runtimes are supported:

Web browsers (Up-to-date Chrome, Firefox, Safari, Edge, and more)
Node.js 20 LTS or later (non-EOL) versions.
Deno v1.28.0 or higher.
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.

Contributing

See the contributing documentation.

Responses