Anjing Webshells

Website : rimsha.abasa.com
: / var / www / talha_silentcontent / node_modules / openai /
Filename : README.md
back
# OpenAI Node API Library

[![NPM version](https://img.shields.io/npm/v/openai.svg)](https://npmjs.org/package/openai)

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

It is generated from our [OpenAPI specification](https://github.com/openai/openai-openapi) with [Stainless](https://stainlessapi.com/).

To learn how to use the OpenAI API, check out our [API Reference](https://platform.openai.com/docs/api-reference) and [Documentation](https://platform.openai.com/docs).

## Installation

```sh
npm install --save openai
# or
yarn add openai
```

## Usage

The full API of this library can be found in [api.md file](https://github.com/openai/openai-node/blob/master/api.md). The code below shows how to get started using the chat completions API.

```js
import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'my api key', // defaults to process.env["OPENAI_API_KEY"]
});

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

  console.log(chatCompletion.choices);
}

main();
```

## Streaming Responses

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

```ts
import OpenAI from 'openai';

const openai = new OpenAI();

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

```ts
import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'my api key', // defaults to process.env["OPENAI_API_KEY"]
});

async function main() {
  const params: OpenAI.Chat.ChatCompletionCreateParams = {
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'gpt-3.5-turbo',
  };
  const chatCompletion: OpenAI.Chat.ChatCompletion = await openai.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](https://github.com/openai/openai-node/discussions/217).

## 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

```ts
import fs from 'fs';
import fetch from 'node-fetch';
import OpenAI, { toFile } from 'openai';

const openai = new OpenAI();

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

// You can also pass a `fetch` `Response`:
await openai.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 openai.files.create({
  file: await toFile(Buffer.from('my bytes'), 'input.jsonl'),
  purpose: 'fine-tune',
});
await openai.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:

```ts
async function main() {
  const fineTune = await openai.fineTunes
    .create({ training_file: 'file-XGinujblHPwGLSztz8cPS8XY' })
    .catch((err) => {
      if (err instanceof OpenAI.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 OpenAI

An example of using this library with Azure OpenAI can be found [here](https://github.com/openai/openai-node/blob/master/examples/azure.ts).

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

See [`@azure/openai`](https://www.npmjs.com/package/@azure/openai) 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:

<!-- prettier-ignore -->
```js
// Configure the default for all requests:
const openai = new OpenAI({
  maxRetries: 0, // default is 2
});

// Or, configure per-request:
await openai.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:

<!-- prettier-ignore -->
```ts
// Configure the default for all requests:
const openai = new OpenAI({
  timeout: 20 * 1000, // 20 seconds (default is 10 minutes)
});

// Override per-request:
await openai.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](#retries).

## Auto-pagination

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

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

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

```ts
let page = await openai.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.

```ts
const openai = new OpenAI();

const response = await openai.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 openai.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.choices);
```

## 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:

<!-- prettier-ignore -->
```ts
import http from 'http';
import HttpsProxyAgent from 'https-proxy-agent';

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

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

## Semantic Versioning

This package generally attempts to follow [SemVer](https://semver.org/spec/v2.0.0.html) 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](https://www.github.com/openai/openai-node/issues) with questions, bugs, or suggestions.

## Requirements

TypeScript >= 4.5 is supported.

The following runtimes are supported:

- Node.js 16 LTS or later ([non-EOL](https://endoflife.date/nodejs)) versions.
- Deno v1.28.0 or higher, using `import OpenAI from "npm:openai"`.
- 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.