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official TypeScript library for the Cerebras API","maintainers":[{"name":"cerebras-it","email":"it-team@cerebras.net"},{"name":"henrytu","email":"henry@henrytu.me"}],"readme":"# Cerebras Node API Library\n\n[![NPM version](https://img.shields.io/npm/v/@cerebras/cerebras_cloud_sdk.svg)](https://npmjs.org/package/@cerebras/cerebras_cloud_sdk) ![npm bundle size](https://img.shields.io/bundlephobia/minzip/@cerebras/cerebras_cloud_sdk)\n\nThis library provides convenient access to the Cerebras REST API from server-side TypeScript or JavaScript.\n\nThe REST API documentation can be found on [inference-docs.cerebras.ai](https://inference-docs.cerebras.ai). The full API of this library can be found in [api.md](api.md).\n\nIt is generated with [Stainless](https://www.stainless.com/).\n\n> [!NOTE]  \n> This SDK has a mechanism that sends a few requests to `/v1/tcp_warming` upon construction to reduce the TTFT. If this behaviour is not desired, set `warmTCPConnection=false` in the constructor.\n>\n> If you are repeatedly reconstructing the SDK instance it will lead to poor performance. It is recommended that you construct the SDK once and reuse the instance if possible.\n\n## About Cerebras\n\nAt Cerebras, we've developed the world's largest and fastest AI processor, the Wafer-Scale Engine-3 (WSE-3). The Cerebras CS-3 system, powered by the WSE-3, represents a new class of AI supercomputer that sets the standard for generative AI training and inference with unparalleled performance and scalability.\n\nWith Cerebras as your inference provider, you can:\n- Achieve unprecedented speed for AI inference workloads\n- Build commercially with high throughput\n- Effortlessly scale your AI workloads with our seamless clustering technology\n\nOur CS-3 systems can be quickly and easily clustered to create the largest AI supercomputers in the world, making it simple to place and run the largest models. Leading corporations, research institutions, and governments are already using Cerebras solutions to develop proprietary models and train popular open-source models.\n\nWant to experience the power of Cerebras? Check out our [website](https://cerebras.net) for more resources and explore options for accessing our technology through the Cerebras Cloud or on-premise deployments!\n\n## Installation\n```\nnpm install @cerebras/cerebras_cloud_sdk\n```\n\n## API Key\nGet an API Key from [cloud.cerebras.ai](https://cloud.cerebras.ai/) and add it to your environment variables:\n```\nexport CEREBRAS_API_KEY=\"your-api-key-here\"\n```\n\n## Usage\n\nThe full API of this library can be found in [api.md](api.md).\n\n### Chat Completion\n<!-- RUN TEST: ChatStandard -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  apiKey: process.env['CEREBRAS_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n  const chatCompletion = await client.chat.completions.create({\n    model: 'llama3.1-8b',\n    messages: [{ role: 'user', content: 'Why is fast inference important?' }],\n  });\n\n  console.log(chatCompletion?.choices[0]?.message);\n}\n\nmain();\n```\n\n### Text Completion\n<!-- RUN TEST: TextStandard -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  apiKey: process.env['CEREBRAS_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n  const completion = await client.completions.create({\n    prompt: \"It was a dark and stormy \",\n    model: 'llama3.1-8b',\n  });\n\n  console.log(completion?.choices[0]?.text);\n}\n\nmain();\n```\n\n## Streaming responses\n\nWe provide support for streaming responses using Server Sent Events (SSE).\n\nNote that when streaming, `usage` and `time_info` will be information will only be included in the final chunk.\n\n### Chat Completion\n<!-- RUN TEST: ChatStreaming -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  apiKey: process.env['CEREBRAS_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n  const stream = await client.chat.completions.create({\n    messages: [{ role: 'user', content: 'Why is fast inference important?' }],\n    model: 'llama3.1-8b',\n    stream: true,\n  });\n  for await (const chunk of stream) {\n    process.stdout.write(chunk.choices[0]?.delta?.content || '');\n  }\n}\n\nmain();\n```\n\n### Text Completion\n<!-- RUN TEST: TextStreaming -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  apiKey: process.env['CEREBRAS_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n  const stream = await client.completions.create({\n    prompt: \"It was a dark and stormy \",\n    model: 'llama3.1-8b',\n    max_tokens: 10,\n    stream: true,\n  });\n  for await (const chunk of stream) {\n    process.stdout.write(chunk.choices[0]?.text || '');\n  }\n}\n\nmain();\n```\n\nIf you need to cancel a stream, you can `break` from the loop\nor call `stream.controller.abort()`.\n\n### Request & Response types\n\nThis library includes TypeScript definitions for all request params and response fields. You may import and use them like so:\n\n<!-- RUN TEST: Types -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  apiKey: process.env['CEREBRAS_API_KEY'], // This is the default and can be omitted\n});\n\nconst params: Cerebras.Chat.ChatCompletionCreateParams = {\n  model: 'llama3.1-8b',\n  messages: [{ role: 'user', content: 'Why is fast inference important?' }],\n};\nconst chatCompletion: Cerebras.Chat.ChatCompletion = await client.chat.completions.create(params);\n```\n\nDocumentation for each method, request param, and response field are available in docstrings and will appear on hover in most modern editors.\n\n## Handling errors\n\nWhen the library is unable to connect to the API,\nor if the API returns a non-success status code (i.e., 4xx or 5xx response),\na subclass of `APIError` will be thrown:\n\n<!-- RUN TEST: Error -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  apiKey: process.env['CEREBRAS_API_KEY'], // This is the default and can be omitted\n});\n\nasync function main() {\n  const chatCompletion = await client.chat.completions\n    .create({\n      model: 'some-model-that-doesnt-exist' as any,\n      messages: [{ role: 'user', content: 'This should cause an error!' }], // Ask TS to ignore the obviously invalid model name... Do not do this!\n    })\n    .catch(async (err) => {\n      if (err instanceof Cerebras.APIError) {\n        console.log(err.status); // 400\n        console.log(err.name); // BadRequestError\n        console.log(err.headers); // {server: 'nginx', ...}\n        console.log(err); // Full exception\n      } else {\n        throw err;\n      }\n    });\n}\n\nmain();\n```\n\nError codes are as follows:\n\n| Status Code | Error Type                 |\n| ----------- | -------------------------- |\n| 400         | `BadRequestError`          |\n| 401         | `AuthenticationError`      |\n| 403         | `PermissionDeniedError`    |\n| 404         | `NotFoundError`            |\n| 422         | `UnprocessableEntityError` |\n| 429         | `RateLimitError`           |\n| >=500       | `InternalServerError`      |\n| N/A         | `APIConnectionError`       |\n\n### Retries\n\nCertain errors will be automatically retried 2 times by default, with a short exponential backoff.\nConnection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict,\n429 Rate Limit, and >=500 Internal errors will all be retried by default.\n\nYou can use the `maxRetries` option to configure or disable this:\n\n<!-- RUN TEST: Retries -->\n```js\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\n// Configure the default for all requests:\nconst client = new Cerebras({\n  maxRetries: 0, // default is 2\n});\n\n// Or, configure per-request:\nawait client.chat.completions.create({ model: 'llama3.1-8b', messages: [{ role: 'user', content: 'Why is fast inference important?' }] }, {\n  maxRetries: 5,\n});\n```\n\n### Timeouts\n\nRequests time out after 1 minute by default. You can configure this with a `timeout` option:\n\n<!-- RUN TEST: Timeout -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\n// Configure the default for all requests:\nconst client = new Cerebras({\n  timeout: 20 * 1000, // 20 seconds (default is 1 minute)\n});\n\n// Override per-request:\nawait client.chat.completions.create({ model: 'llama3.1-8b', messages: [{ role: 'user', content: 'Why is fast inference important?' }] }, {\n  timeout: 5 * 1000,\n});\n```\n\nOn timeout, an `APIConnectionTimeoutError` is thrown.\n\nNote that requests which time out will be [retried twice by default](#retries).\n\n## Advanced Usage\n\n### Accessing raw Response data (e.g., headers)\n\nThe \"raw\" `Response` returned by `fetch()` can be accessed through the `.asResponse()` method on the `APIPromise` type that all methods return.\n\nYou can also use the `.withResponse()` method to get the raw `Response` along with the parsed data.\n\n<!-- RUN TEST: Advanced -->\n```ts\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras();\n\nconst response = await client.chat.completions\n  .create({ model: 'llama3.1-8b', messages: [{ role: 'user', content: 'Why is fast inference important?' }] })\n  .asResponse();\nconsole.log(response.headers.get('X-My-Header'));\nconsole.log(response.statusText); // access the underlying Response object\n\nconst { data: chatCompletion, response: raw } = await client.chat.completions\n  .create({ model: 'llama3.1-8b', messages: [{ role: 'user', content: 'Why is fast inference important?' }] })\n  .withResponse();\nconsole.log(raw.headers.get('X-My-Header'));\nconsole.log(chatCompletion);\n```\n\n### Making custom/undocumented requests\n\nThis library is typed for convenient access to the documented API. If you need to access undocumented\nendpoints, params, or response properties, the library can still be used.\n\n#### Undocumented endpoints\n\nTo make requests to undocumented endpoints, you can use `client.get`, `client.post`, and other HTTP verbs.\nOptions on the client, such as retries, will be respected when making these requests.\n\n```ts\nawait client.post('/some/path', {\n  body: { some_prop: 'foo' },\n  query: { some_query_arg: 'bar' },\n});\n```\n\n#### Undocumented request params\n\nTo make requests using undocumented parameters, you may use `// @ts-expect-error` on the undocumented\nparameter. This library doesn't validate at runtime that the request matches the type, so any extra values you\nsend will be sent as-is.\n\n```ts\nclient.foo.create({\n  foo: 'my_param',\n  bar: 12,\n  // @ts-expect-error baz is not yet public\n  baz: 'undocumented option',\n});\n```\n\nFor requests with the `GET` verb, any extra params will be in the query, all other requests will send the\nextra param in the body.\n\nIf you want to explicitly send an extra argument, you can do so with the `query`, `body`, and `headers` request\noptions.\n\n#### Undocumented response properties\n\nTo access undocumented response properties, you may access the response object with `// @ts-expect-error` on\nthe response object, or cast the response object to the requisite type. Like the request params, we do not\nvalidate or strip extra properties from the response from the API.\n\n### Customizing the fetch client\n\nBy default, this library uses `node-fetch` in Node, and expects a global `fetch` function in other environments.\n\nIf you would prefer to use a global, web-standards-compliant `fetch` function even in a Node environment,\n(for example, if you are running Node with `--experimental-fetch` or using NextJS which polyfills with `undici`),\nadd the following import before your first import `from \"Cerebras\"`:\n\n```ts\n// Tell TypeScript and the package to use the global web fetch instead of node-fetch.\n// Note, despite the name, this does not add any polyfills, but expects them to be provided if needed.\nimport '@cerebras/cerebras_cloud_sdk/shims/web';\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n```\n\nTo do the inverse, add `import \"@cerebras/cerebras_cloud_sdk/shims/node\"` (which does import polyfills).\nThis can also be useful if you are getting the wrong TypeScript types for `Response` ([more details](https://github.com/Cerebras/cerebras-cloud-sdk-node/tree/main/src/_shims#readme)).\n\n### Logging and middleware\n\nYou may also provide a custom `fetch` function when instantiating the client,\nwhich can be used to inspect or alter the `Request` or `Response` before/after each request:\n\n```ts\nimport { fetch } from 'undici'; // as one example\nimport Cerebras from '@cerebras/cerebras_cloud_sdk';\n\nconst client = new Cerebras({\n  fetch: async (url: RequestInfo, init?: RequestInit): Promise<Response> => {\n    console.log('About to make a request', url, init);\n    const response = await fetch(url, init);\n    console.log('Got response', response);\n    return response;\n  },\n});\n```\n\nNote that if given a `DEBUG=true` environment variable, this library will log all requests and responses automatically.\nThis is intended for debugging purposes only and may change in the future without notice.\n\n### Configuring an HTTP(S) Agent (e.g., for proxies)\n\nBy 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.\n\nIf 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:\n\n<!-- prettier-ignore -->\n```ts\nimport http from 'http';\nimport { HttpsProxyAgent } from 'https-proxy-agent';\n\n// Configure the default for all requests:\nconst client = new Cerebras({\n  httpAgent: new HttpsProxyAgent(process.env.PROXY_URL),\n});\n\n// Override per-request:\nawait client.chat.completions.create(\n  { model: 'llama3.1-8b', messages: [{ role: 'user', content: 'Why is fast inference important?' }] },\n  {\n    httpAgent: new http.Agent({ keepAlive: false }),\n  },\n);\n```\n\n## Semantic versioning\n\nThis package generally follows [SemVer](https://semver.org/spec/v2.0.0.html) conventions, though certain backwards-incompatible changes may be released as minor versions:\n\n1. Changes that only affect static types, without breaking runtime behavior.\n2. 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.)_\n3. Changes that we do not expect to impact the vast majority of users in practice.\n\nWe take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.\n\nWe are keen for your feedback; please open an [issue](https://www.github.com/Cerebras/cerebras-cloud-sdk-node/issues) with questions, bugs, or suggestions.\n\n## Requirements\n\nTypeScript >= 4.5 is supported.\n\nThe following runtimes are supported:\n\n- Web browsers (Up-to-date Chrome, Firefox, Safari, Edge, and more)\n- Node.js 18 LTS or later ([non-EOL](https://endoflife.date/nodejs)) versions.\n- Deno v1.28.0 or higher.\n- Bun 1.0 or later.\n- Cloudflare Workers.\n- Vercel Edge Runtime.\n- Jest 28 or greater with the `\"node\"` environment (`\"jsdom\"` is not supported at this time).\n- Nitro v2.6 or greater.\n\nNote that React Native is not supported at this time.\n\nIf you are interested in other runtime environments, please open or upvote an issue on GitHub.\n\n## Contributing\n\nSee [the contributing documentation](./CONTRIBUTING.md).\n\n","readmeFilename":"README.md"}