The Official TypeScript SDK for the SpaceXAI API

XAI released the official TypeScript SDK for its SpaceXAI API, published as the npm package @xai-official/sdk and requiring Node.js 22.13 or later. The SDK is experimental, covers the Responses API plus image and video generation, Files, Batch, Voice, tokenization, and model and account lookup, and its interfaces may change before version 1.0, so xAI advises pinning an exact version. The client reads the XAI_API_KEY environment variable, has no runtime dependencies, and blocks browser and Worker use by default to keep API keys server-side.

Use Grok from TypeScript with a typed, ESM client built on the SpaceXAI REST API. The SDK has no runtime dependencies and includes streaming, structured output, function tools, image input, image and video generation, file uploads, batch processing, text to speech and transcription, multi-turn conversations, and access to usage and HTTP metadata. Experimental. This SDK is in early development. It currently covers the Responses API, image and video generation, the Files, Batch, and Voice APIs, tokenization, and model and account lookup, and its interfaces may change between releases before 1.0. Pin an exact version and read the changelog https://github.com/xai-org/xai-sdk-ts/blob/main/CHANGELOG.md when upgrading. Feedback and bug reports are welcome in issues https://github.com/xai-org/xai-sdk-ts/issues . - Node.js 22.13 or later - A SpaceXAI API key https://console.x.ai - An ESM project Install the package with your preferred package manager: npm install @xai-official/sdk pnpm add @xai-official/sdk Set your API key in the environment. The client reads XAI API KEY automatically. export XAI API KEY="your-api-key" js import { SpaceXAI } from "@xai-official/sdk"; const client = new SpaceXAI ; const response = await client.responses.create { model: "grok-4.7", input: "Explain why the sky is blue in one sentence.", } ; console.log response.toText ; Keep API keys on the server. The SDK blocks browser and Worker use by default because shipping a secret key to client-side code exposes it to users. Set stream: true to receive output as it's generated. Listen for answer text with on "text" , then await stream.done for the final response: js const stream = await client.responses.create { model: "grok-4.7", input: "Write a short story about a curious robot.", stream: true, } ; const response = await stream .on "text", text = process.stdout.write text .done ; console.log \n${response.usage.total tokens} tokens ; done resolves to the same response object a non-streamed request returns. It rejects if the stream fails or closes before the response completes. Besides "text" , on has helper events for the rest of a response: - "reasoning" for each chunk of reasoning text or reasoning summary - "tool call" for each tool call once its arguments are complete, whether your code or SpaceXAI runs it. Check call.type to tell them apart - "client tool call" for each call that your code runs: your function tools and shell commands - "server tool call" for each call to a tool that SpaceXAI runs, such as web search or code execution - "image" for each finished image generation call, with the base64 image in result - "citation" for each URL citation in the answer Each tool call fires once, when its arguments are complete. For your function tools, that's when to run the function, since nothing has run it yet. To show that a call has started before its arguments arrive, listen for "response.output item.added" . js const response = await stream .on "reasoning", text = process.stderr.write text .on "text", text = process.stdout.write text .on "tool call", call = console.error \n${call.type} ${call.status} .done ; on also takes any server-sent event type, such as "response.completed" , and passes the listener the typed event. Events the SDK doesn't recognize arrive as "unknown" , with the original payload in event.raw . You can also iterate over the stream to handle events in a loop. After the loop, done resolves right away with the final response: js for await const event of stream { if event.type === "response.function call arguments.delta" { process.stdout.write event.delta ; } } const response = await stream.done ; console.log response.toText ; stream.http has the HTTP status, headers, and request IDs as soon as create returns. If you stop consuming a stream early, call await stream.close to cancel its response body. Responses are not stored by default. Use toInput to carry the model output, including encrypted reasoning content, into the next turn. Reuse one prompt cache key across the conversation to improve prompt cache routing: js import { randomUUID } from "node:crypto"; import { type InputItem, SpaceXAI } from "@xai-official/sdk"; const client = new SpaceXAI ; const promptCacheKey = conversation:${randomUUID } ; const input: Array<InputItem = { role: "user", content: "My name is Ada. Remember it." }, ; const first = await client.responses.create { model: "grok-4.7", input, prompt cache key: promptCacheKey, } ; const second = await client.responses.create { model: "grok-4.7", input: ...input, ...first.toInput , { role: "user", content: "What is my name?" }, , prompt cache key: promptCacheKey, } ; console.log second.toText ; Use a different cache key for each unrelated conversation. To continue a stored response by ID, opt in to storage: js const first = await client.responses.create { model: "grok-4.7", input: "My name is Ada. Remember it.", store: true, } ; const second = await client.responses.create { model: "grok-4.7", input: "What is my name?", previous response id: first.id, store: true, } ; Every turn resends the whole conversation, so input tokens grow as it gets longer. Compact the conversation into a single encrypted item with responses.compact , then start the next input with the compacted output . Continuing the toInput example: js const compacted = await client.responses.compact { model: "grok-4.7", input: ...input, ...first.toInput , { role: "user", content: "What is my name?" }, ...second.toInput , , } ; const third = await client.responses.create { model: "grok-4.7", input: ...compacted.output, { role: "user", content: "Spell my name backwards." }, , prompt cache key: promptCacheKey, } ; console.log third.toText ; Pass compacted.output unchanged and add new turns after it. The conversation must still fit in the model's context window when you compact it. compacted.usage reports the tokens the compaction used and dropped message count , the number of messages it replaced. Pass an image URL alongside text: js const response = await client.responses.create { model: "grok-4.7", input: { role: "user", content: { type: "input text", text: "Describe this image." }, { type: "input image", image url: "https://example.com/image.jpg", detail: "high", }, , }, , } ; console.log response.toText ; For a local image, pass a Blob or File as image . The SDK converts it to a data URL before sending the request, and detects JPEG, PNG, or WebP from the bytes when the Blob has no MIME type. js import { readFile } from "node:fs/promises"; const bytes = new Uint8Array await readFile "./image.png" ; const image = new Blob bytes , { type: "image/png" } ; const response = await client.responses.create { model: "grok-4.7", input: { role: "user", content: { type: "input text", text: "What is in this image?" }, { type: "input image", image }, , }, , } ; Provide a JSON Schema through text.format . Call toJson to parse the completed text output. js const response = await client.responses.create { model: "grok-4.7", input: "Give me a city to visit in Japan.", text: { format: { type: "json schema", name: "travel suggestion", schema: { type: "object", properties: { city: { type: "string" }, reason: { type: "string" }, }, required: "city", "reason" , additionalProperties: false, }, }, }, } ; const suggestion = response.toJson ; console.log suggestion ; toJson returns unknown . Validate the result before using it at a trust boundary. The non-throwing response.parsed getter returns null when the output is incomplete or is not valid JSON. Describe functions with JSON Schema, run the requested function in your application, then return its output to the model: js import { type InputItem, type Tool, isFunctionCall, SpaceXAI } from "@xai-official/sdk"; const client = new SpaceXAI ; const prompt = "What is the weather in San Francisco?"; const input: Array<InputItem = { role: "user", content: prompt } ; const getWeatherTool: Tool = { type: "function", name: "get weather", description: "Get the current weather for a location.", parameters: { type: "object", properties: { location: { type: "string" }, }, required: "location" , additionalProperties: false, }, }; async function getWeather args: unknown { if typeof args == "object" || args === null || "location" in args || typeof args.location == "string" { throw new Error "get weather expects a location string" ; } return { location: args.location, temperatureC: 18, conditions: "sunny" }; } const response = await client.responses.create { model: "grok-4.7", input, parallel tool calls: false, tools: getWeatherTool , } ; const call = response.output.find isFunctionCall ; if call throw new Error "The model did not call get weather" ; const result = await getWeather JSON.parse call.arguments ; const answer = await client.responses.create { model: "grok-4.7", input: ...input, ...response.toInput , { type: "function call output", call id: call.call id, output: JSON.stringify result }, , } ; console.log answer.toText ; parallel tool calls: false limits the model to one function call per turn, so this example only has to handle one. By default the model can ask for several at once, which the tool call loop tool-call-loop handles. Treat function names and arguments as untrusted input. Only dispatch functions you have explicitly allowed, and validate arguments before executing them, as getWeather does. To let the model call tools until it has an answer, run a loop. Stream a turn, run each function call as soon as it finishes streaming, then send the outputs back along with the model's output. Stop when a turn makes no function calls, and cap the number of turns so a model that keeps calling tools can't loop forever. This reuses getWeatherTool and getWeather from the example above: js import { type FunctionToolCall, type InputItem, type Tool, SpaceXAI } from "@xai-official/sdk"; const client = new SpaceXAI ; const tools: Array<Tool = getWeatherTool ; const handlers: Record<string, args: unknown = Promise<unknown = { get weather: getWeather, }; async function runTool call: FunctionToolCall : Promise<InputItem { let output: unknown; try { const handler = handlers call.name ; if handler throw new Error Unknown tool: ${call.name} ; output = await handler JSON.parse call.arguments ; } catch err { output = { error: err instanceof Error ? err.message : String err }; } return { type: "function call output", call id: call.call id, output: JSON.stringify output , }; } const input: Array<InputItem = { role: "user", content: "Compare the weather in Paris and Tokyo." }, ; for let turn = 0; turn < 10; turn++ { const toolRuns: Array<Promise<InputItem = ; const stream = await client.responses.create { model: "grok-4.7", input, tools, stream: true, } ; const response = await stream .on "text", text = process.stdout.write text .on "client tool call", call = { if call.type === "function call" toolRuns.push runTool call ; } .done ; if toolRuns.length === 0 break; const toolOutputs = await Promise.all toolRuns ; input.push ...response.toInput , ...toolOutputs ; } The handlers map is the list of functions the model may call. runTool returns errors to the model instead of throwing, so the model can recover, and a failing tool can't crash the loop while the stream is still running. With the shell tool, the model writes shell commands and your application runs them. Use it for agents that work on your machine, such as exploring a repository, running tests, or checking disk space. Each call arrives through the client tool call listener as a shell call , with the commands in action.commands . The model writes these commands, so run them in a sandbox or container, or check each one before running it: js import { exec } from "node:child process"; import { SpaceXAI } from "@xai-official/sdk"; const client = new SpaceXAI ; const stream = await client.responses.create { model: "grok-4.7", input: "How much free disk space does this machine have?", tools: { type: "shell", environment: { type: "local" } } , stream: true, } ; await stream .on "client tool call", call = { if call.type === "shell call" { for const command of call.action.commands { exec command, error, stdout, stderr = console.log stdout || stderr ; } } } .done ; To let the model use the results, send them back in the next request, like the function outputs in the tool call loop tool-call-loop : { type: "shell call output", call id: call.call id, output: { stdout, stderr, outcome: { type: "exit", exit code: 0 } } } . To give the model skills, list them in the tool's environment . A skill is a directory with a SKILL.md file of instructions. The model sees each skill's name and description, and when a task matches one, it reads the SKILL.md through your shell tool and follows it. If you only allow certain commands, allow reading the skill's directory: js const shell: Tool = { type: "shell", environment: { type: "local", skills: { name: "release-notes", description: "Write release notes from this repo's git log in our house style.", path: "./skills/release-notes", }, , }, }; Asked to write release notes, the model reads ./skills/release-notes/SKILL.md , runs the git log command it describes, and writes the notes in the format it specifies. Besides your own functions, the API has built-in tools. Create them with the helpers from @xai-official/sdk/tools , which check each tool's options as you type. SpaceXAI runs these tools and includes their results in the response: - webSearch web search searches the web. Options include allowed domains , excluded domains , user location , and search context size . - xSearch x search searches posts on X. Options include allowed x handles , excluded x handles , from date , and to date . - codeExecution code interpreter writes and runs Python code to answer the prompt. - collectionsSearch file search searches the collections https://docs.x.ai/developers/files/collections listed in vector store ids . - imageGeneration image generation creates or edits images. - mcp mcp calls tools on the remote MCP server at server url , identified by server label . - toolSearch tool search loads the definitions of tools marked defer loading: true when the model needs them, instead of putting every definition in the prompt. Two kinds of tools run in your application instead: function for your own functions, as shown in Tools tools , and shell , where the model writes shell commands for your application to run, as shown in Shell commands shell-commands . When you stream, calls to both arrive through the client tool call listener. The helpers return plain tool objects, so you can also write { type: "web search" } yourself. Tool autocompletes the known types and accepts any other type , such as a tool released after this SDK version, but it doesn't check options the way the helpers do. See the SpaceXAI documentation https://docs.x.ai for each tool's options. Add the web search tool when a prompt needs current information: js import { SpaceXAI } from "@xai-official/sdk"; import { webSearch } from "@xai-official/sdk/tools"; const client = new SpaceXAI ; const response = await client.responses.create { model: "grok-4.7", input: "What are the latest developments in commercial spaceflight?", tools: webSearch , } ; console.log response.toText ; console.log response.usage.num server side tools used ; Search posts on X, optionally limited to certain accounts and dates: js import { xSearch } from "@xai-official/sdk/tools"; const response = await client.responses.create { model: "grok-4.7", input: "What has SpaceXAI announced on X this month?", tools: xSearch { allowed x handles: "xai" , from date: "2026-09-01" } , } ; allowed x handles and excluded x handles each take up to 20 handles and can't be used together. Set enable image understanding or enable video understanding to let the model look at media in posts. When you stream, each finished search reaches the server tool call listener as a custom tool call . Its name is the search that ran, such as x keyword search , and input holds the search arguments as a JSON string: js await stream .on "server tool call", call = { if call.type === "custom tool call" console.log call.name, call.input ; } .done ; Let the model write and run Python for calculations and data analysis: js import { codeExecution } from "@xai-official/sdk/tools"; const response = await client.responses.create { model: "grok-4.7", input: "What is the standard deviation of 12, 15, 19, 22, and 31?", tools: codeExecution , } ; The code runs in a sandbox with common libraries installed. The tool takes no options. Search documents you've added to collections https://docs.x.ai/developers/files/collections : js import { collectionsSearch } from "@xai-official/sdk/tools"; const response = await client.responses.create { model: "grok-4.7", input: "What does our refund policy say about digital purchases?", tools: collectionsSearch { vector store ids: "your-collection-id" , max num results: 10 } , } ; Give the model the tools of a remote MCP server. SpaceXAI connects to the server and calls its tools during the response: js import { mcp } from "@xai-official/sdk/tools"; const response = await client.responses.create { model: "grok-4.7", input: "What is the modelcontextprotocol/typescript-sdk repository for?", tools: mcp { server url: "https://mcp.deepwiki.com/mcp", server label: "deepwiki" } , } ; The server must use the Streaming HTTP or SSE transport. Limit the model to some of the server's tools with allowed tools , and pass credentials with authorization or headers . require approval and connector id aren't supported yet. For a server with many tools, set defer loading: true on it and add toolSearch , so the model loads only the tool definitions it needs. Add the image generation tool to let the model create or edit images as one step of a response. Each image arrives as an image generation call output item whose result holds base64 image data: js import { writeFile } from "node:fs/promises"; import { isImageGenerationCall, SpaceXAI } from "@xai-official/sdk"; import { imageGeneration } from "@xai-official/sdk/tools"; const client = new SpaceXAI ; const response = await client.responses.create { model: "grok-4.7", input: "Generate an image of a corgi surfing a big wave, in the style of a Japanese woodblock print.", tools: imageGeneration , } ; console.log response.toText ; const call = response.output.find isImageGenerationCall ; if call?.result { await writeFile "corgi.jpg", Buffer.from call.result, "base64" ; } Pass action: "generate" or action: "edit" to imageGeneration to allow only one of those capabilities. When streaming, each call emits response.image generation call.in progress , response.image generation call.generating , and response.image generation call.completed events, then a response.output item.done event carries the finished item. To generate or edit an image directly with full control over its size and format, use the image generation image-generation and image editing image-editing methods instead. Every completed response provides: - response.toText to concatenate output text - response.toInput to carry all output items into a later request - response.toJson to parse completed JSON output - response.parsed for non-throwing JSON parsing - response.output for typed output items - response.usage for token counts, server-side tool use, and cost when available - response.http for the HTTP status, headers, SpaceXAI request ID, and client request ID - response.raw for the response object as the API sent it, including fields this SDK doesn't know yet Use the exported type guards when inspecting output items: js import { isFunctionCall, isMessage, isReasoning, } from "@xai-official/sdk"; for const item of response.output { if isMessage item { console.log "message", item.content ; } else if isFunctionCall item { console.log "function", item.name, item.arguments ; } else if isReasoning item { console.log "reasoning item", item.id ; } } Generate images from a text prompt with a Grok Imagine model. Images are returned as temporary URLs by default, so download or process them promptly: js const result = await client.images.generate { model: "grok-imagine-image-2.0", prompt: "A collage of London landmarks in a stenciled street-art style", } ; console.log result.data 0 ?.url ; console.log result.usage?.cost usd ; Request up to 10 images with n , and shape the output with aspect ratio , resolution , and quality . Only grok-imagine-image-2.0 supports quality . Set response format: "b64 json" to receive base64 data instead of URLs: js import { writeFile } from "node:fs/promises"; const result = await client.images.generate { model: "grok-imagine-image-2.0", prompt: "A futuristic city skyline at night", n: 4, aspect ratio: "16:9", resolution: "2k", response format: "b64 json", } ; for const index, image of result.data.entries { if image.b64 json { await writeFile skyline-${index}.jpg , Buffer.from image.b64 json, "base64" ; } } Base64 output is about a third larger than the image file, so large batches of high-resolution images can approach the default 32 MiB response size limit. Raise maxResponseBodyBytes for those requests: js const result = await client.images.generate { model: "grok-imagine-image-2.0", prompt: "A futuristic city skyline at night", n: 10, resolution: "2k", response format: "b64 json", }, { maxResponseBodyBytes: 128 1024 1024 }, ; Each result provides data , usage , and http . usage.cost usd converts the reported cost in usd ticks to US dollars, and usage is null when the API omits it. Pass a source image with your prompt to edit it. image accepts a public URL, a base64 data URL, a Files API file id , or a Blob or File , which the SDK converts to a data URL before sending the request: js import { openAsBlob } from "node:fs"; const photo = await openAsBlob "./photo.png" ; const result = await client.images.edit { model: "grok-imagine-image-2.0", prompt: "Render this as a pencil sketch with detailed shading", image: photo, } ; console.log result.data 0 ?.url ; When a Blob or File has no MIME type, as with openAsBlob or new File bytes , "photo.png" , the SDK detects JPEG, PNG, or WebP from its first bytes. The API rejects image data URLs that are not typed as one of those formats. To combine up to five source images, pass images instead of image and refer to them in the prompt as <IMAGE 0 , <IMAGE 1 , and so on. The output follows the first image's aspect ratio unless you set aspect ratio : js const result = await client.images.edit { model: "grok-imagine-image-2.0", prompt: "Place the cat from <IMAGE 0 on the sofa from <IMAGE 1 ", images: { url: "https://example.com/cat.png" }, { file id: "file abc123" }, , aspect ratio: "16:9", } ; Video generation runs as a background job. generate starts the job and returns its request id , and wait polls until the job finishes: const { request id } = await client.videos.generate { model: "grok-imagine-video-1.5", prompt: "A paper boat drifting down a rain-soaked street", duration: 8, aspect ratio: "16:9", resolution: "720p", } ; const result = await client.videos.wait request id ; if result.status === "done" { console.log result.video?.url ; console.log result.usage?.cost usd ; } else { console.error result.status, result.error?.code, result.error?.message ; } wait resolves once the status is no longer pending : done , failed , or expired . A failed result includes an error with a code and message . If video.respect moderation is false , the video did not pass moderation and has no URL. Video URLs are temporary, so download the file promptly. wait polls every 5 seconds for up to 10 minutes. Pass interval and timeout in milliseconds to change this, and a signal to stop waiting. A timeout rejects with TimeoutError but does not cancel the job, so you can call wait again. To check once without waiting, call client.videos.get request id , which returns status: "pending" until the video is ready. To animate a still image, pass it as image . image , reference images , and keyframe images accept a public URL, a base64 data URL, a Files API file id , or a Blob or File , which the SDK converts to a data URL before sending the request: js import { openAsBlob } from "node:fs"; const { request id } = await client.videos.generate { model: "grok-imagine-video-1.5", prompt: "Make the water crash down and slowly pan out the camera", image: await openAsBlob "./waterfall.png" , } ; Edit a video with edit , or continue it from its last frame with extend . Both return a request id for wait . The source video must be an MP4, given as a public URL, a base64 data URL, a Files API file id , or a Blob or File , which the SDK converts to a data URL before sending the request. For extensions, duration sets the length of the new segment only: js import { openAsBlob } from "node:fs"; const edit = await client.videos.edit { model: "grok-imagine-video", prompt: "Give the woman a silver necklace", video: await openAsBlob "portrait.mp4" , } ; const extension = await client.videos.extend { model: "grok-imagine-video", prompt: "The camera slowly zooms out to reveal the city skyline", video: { file id: "file abc123" }, duration: 6, } ; A Blob or File without a MIME type is sent as video/mp4 . Because the video travels inside the request as base64, which is a third larger than the file, upload large videos with client.files.upload up to 50 MB and pass { file id } instead. List the video generation models available to your API key with client.models.video.list , or look one up by ID with client.models.video.get . Upload a document, image, or video once and refer to it by ID. A file ID works wherever the API accepts a file id , such as an input file part in the Responses API or an image or video input: js import { openAsBlob } from "node:fs"; const file = await client.files.upload { file: await openAsBlob "./report.pdf" , filename: "report.pdf", } ; const response = await client.responses.create { model: "grok-4.7", input: { role: "user", content: { type: "input text", text: "Summarize the key findings in this report." }, { type: "input file", file id: file.id }, , }, , } ; console.log response.toText ; The API records the upload's filename as the file's filename . A File uses its own name, and a plain Blob , such as one from openAsBlob , needs filename . Files are kept until you delete them; set expires after to between 3,600 and 2,592,000 seconds 1 hour to 30 days to have one deleted automatically. List, download, share, and delete stored files: js import { writeFile } from "node:fs/promises"; for await const stored of client.files.list { console.log stored.id, stored.filename, stored.bytes ; } const content = await client.files.content file.id ; await writeFile "report-copy.pdf", await content.bytes ; const { public url } = await client.files.createPublicUrl file.id, { expires after: 86 400, } ; console.log public url ; await client.files.revokePublicUrl file.id ; await client.files.delete file.id ; list returns the newest files first and fetches further pages as the loop needs them. content returns an BinaryResponse : stream its body or read it with bytes , text , or blob . Anyone with a public URL can download the file without an API key. Only images, videos, and PDFs up to 50 MiB can be made public. A file has at most one public URL, so calling createPublicUrl again returns the existing URL and updates its expiry if you pass a new expires after . Without expires after , the URL lasts as long as the file unless you revoke it. After revoking, copies already cached by the CDN can still be served briefly. The Batch API processes large volumes of requests asynchronously at a reduced price. Most requests complete within 24 hours. Create a batch, then add requests to it: js const batch = await client.batches.create { name: "feedback sentiment" } ; const feedback = { id: "feedback 001", text: "The product exceeded my expectations " }, { id: "feedback 002", text: "Shipping took way too long." }, ; await client.batches.requests.add batch.batch id, { batch requests: feedback.map item = { batch request id: item.id, batch request: { responses: { model: "grok-4.7", input: { role: "system", content: "Classify the sentiment as positive, negative, or neutral." }, { role: "user", content: item.text }, , }, }, } , } ; Each batch request holds one request. responses takes the same CreateParams as client.responses.create , including the store: false default, and its result comes back as a chat get completion response. image generation , image edit , video generation , and video extension take the request body of the matching REST endpoint. Results can come back in any order, so give each request a batch request id that is unique within the batch. Not every model accepts batch requests; each model page https://docs.x.ai/developers/models lists its Batch API support. Wait until no requests are pending, then read the results: await client.batches.wait batch.batch id ; for await const { batch request id, batch result } of client.batches.results batch.batch id { if "error" in batch result { console.error batch request id, batch result.error ; } else { console.log batch request id, batch result.response ; } } wait polls every 5 seconds and rejects with TimeoutError after 24 hours. Pass interval , timeout , or signal to change that. Results are available as soon as each request finishes, so you can read them before the whole batch completes. Use client.batches.requests.list to check the state of individual requests, client.batches.list to list your team's batches, and client.batches.cancel to stop the remaining requests. Finished results stay available after cancelling. Convert text to speech with client.voice.speak . The audio comes back as an BinaryResponse , encoded as MP3 unless you set output format : js import { writeFile } from "node:fs/promises"; const speech = await client.voice.speak { text: "Welcome to SpaceX. pause How can I help you today?", language: "en", voice id: "eve", } ; await writeFile "welcome.mp3", await speech.bytes ; Shape the delivery with speech tags https://docs.x.ai/developers/model-capabilities/audio/text-to-speech speech-tags in the text. Inline tags such as pause , long-pause , and laugh go where the sound should happen, and wrapping tags such as <whisper It's a secret.</whisper change how the enclosed text is spoken. The API doesn't report mistakes in tags, so TypeScript checks string literals as you type: it flags unknown tags such as laff and suggests the closest one, and it catches wrapping tags that are never closed, closed without being opened, or closed in the wrong order. To use a tag released after this SDK version, add as UnsafeSpeechText to the text, which skips the check. Searching for UnsafeSpeechText then finds every tag to clean up once the SDK knows it: js import { type UnsafeSpeechText } from "@xai-official/sdk"; await client.voice.speak { text: "Hello new-tag there." as UnsafeSpeechText, language: "en", } ; voice id autocompletes the built-in voices and accepts any other string, such as a custom voice ID or a voice added after this SDK version. List the built-in voices with client.voice.list . To start playback before synthesis finishes, read speech.body as a stream. Set with timestamps: true to receive JSON with base64 audio and per-character audio timestamps instead of audio bytes. Transcribe a recording with client.voice.transcribe . Pass the audio as a Blob or File , or pass url to have the API download it: js import { openAsBlob } from "node:fs"; const transcript = await client.voice.transcribe { file: await openAsBlob "./meeting.mp3" , language: "en", format: true, } ; console.log transcript.text ; format: true writes spoken numbers, currencies, and units in written form, and requires language . Word-level timings are in transcript.words . Clone a voice from a reference clip of up to 120 seconds with client.voice.custom.create . Creating custom voices through the API requires an Enterprise plan: js import { openAsBlob } from "node:fs"; const voice = await client.voice.custom.create { file: await openAsBlob "./reference.wav" , name: "Friendly Narrator", language: "en", } ; console.log voice.voice id ; Pass the returned voice id to speak or a realtime session like a built-in voice. client.voice.custom also provides list , get , update , delete , and getAudio , which downloads the reference clip. Realtime voice sessions in a browser should authenticate with a short-lived client secret instead of your API key. Create one on your server: js const secret = await client.voice.clientSecrets.create { expires after: { seconds: 300 }, } ; Send secret.value to the browser, which passes xai-client-secret.<value as the WebSocket subprotocol when it connects to wss://api.x.ai/v1/realtime . Secrets expire after 10 minutes by default, and expires after.seconds can be at most 3600. Encode text with a language model's tokenizer to count its tokens or see how it is split: const { token ids } = await client.tokenizer.encode { model: "grok-4.7", text: "Hello world ", } ; console.log token ids.length ; for const token of token ids { console.log token.token id, token.string token ; } Inference requests add tokens of their own, so usage.input tokens for a prompt can be higher than this count. The API has no decode endpoint, but each token carries its bytes, so you can turn encoded tokens back into text. Decode token bytes rather than joining string token , because a token can hold part of a multi-byte character: js const text = new TextDecoder .decode new Uint8Array token ids.flatMap token = token.token bytes , ; Use model IDs directly. ModelId suggests known string literals while still accepting models released after the installed SDK version: js import { type KnownModelId } from "@xai-official/sdk"; const model: KnownModelId = "grok-4.7"; const available = await client.models.list ; for const availableModel of available.data { console.log availableModel.id ; } const modelInfo = await client.models.get model ; console.log modelInfo ; KnownModelId is generated from the SpaceXAI model documentation https://docs.x.ai/developers/models . Use it when you want strict validation against the models known to this SDK release. Image generation models have their own catalog, which includes modalities, aliases, and pricing. ImageModelId and KnownImageModelId work the same way as the text model types: js import { type KnownImageModelId } from "@xai-official/sdk"; const imageModel: KnownImageModelId = "grok-imagine-image-2.0"; const imageModels = await client.models.image.list ; for const availableImageModel of imageModels.models { console.log availableImageModel.id, availableImageModel.aliases ; } const imageModelInfo = await client.models.image.get imageModel ; console.log imageModelInfo ; Chat and image understanding models have their own catalog, which includes modalities, aliases, token pricing, and supported reasoning efforts: js const languageModels = await client.models.language.list ; for const languageModel of languageModels.models { console.log languageModel.id, languageModel.input modalities ; } const languageModelInfo = await client.models.language.get "grok-4.7" ; console.log languageModelInfo.capabilities?.reasoning effort ; Token prices such as prompt text token price are in USD cents per 100 million tokens. Divide them by 10,000 for US dollars per million tokens. client.account.apiKey returns the name, status, and permissions of the API key the client is using: js const apiKeyInfo = await client.account.apiKey ; console.log apiKeyInfo.name, apiKeyInfo.acls, apiKeyInfo.api key disabled ; The SDK sends store: false unless you opt in. This differs from the API wire default. With storage disabled, the SDK requests encrypted reasoning content so response.toInput can preserve context between turns. Pass store: true when you need to retrieve, continue, inspect, or delete a response by ID: js const stored = await client.responses.create { model: "grok-4.7", input: "Save this response.", store: true, } ; const fetched = await client.responses.get stored.id ; const inputItems = await client.responses.inputItems.list stored.id ; await client.responses.delete stored.id ; List methods that return results in pages fetch the next page for you in a for await loop: js for await const file of client.files.list { console.log file.id ; } This works for files.list , batches.list , batches.results , batches.requests.list , voice.custom.list , and responses.inputItems.list . Awaiting one of these calls instead returns a single page. Configure defaults on the client: js const client = new SpaceXAI { timeout: 60 000, idleTimeout: 30 000, maxRetries: 2, } ; Override them for one request and pass an AbortSignal when needed: js const controller = new AbortController ; const pending = client.responses.create { model: "grok-4.7", input: "Write a detailed report.", }, { signal: controller.signal, timeout: 120 000, maxRetries: 0, }, ; controller.abort ; await pending; Requests that generate content, such as responses.create , images.generate , and images.edit , retry only explicit 429 responses by default. Read-only requests may also retry transient HTTP failures. Retry delays honor Retry-After and use jittered exponential backoff. When you leave out stream , responses.create streams the response under the hood and resolves to the final response. Streamed responses send headers right away, so long reasoning requests aren't cut off by limits on waiting for headers, such as the 5 minutes that Node's built-in fetch allows whatever timeout is set to. Reasoning can also go quiet for minutes, so these requests only apply idleTimeout when you pass it on the request. Set stream: false to send a plain JSON request instead. All SDK errors extend APIError . Status-specific classes are exported for common API failures. js import { APIError, AuthenticationError, RateLimitError, } from "@xai-official/sdk"; try { await client.responses.create { model: "grok-4.7", input: "Hello", } ; } catch error { if error instanceof AuthenticationError { console.error "Check XAI API KEY" ; } else if error instanceof RateLimitError { console.error "Rate limited. Retry later." ; } else if APIError.is error { console.error error.status, error.code, error.param, error.requestId, error.message ; } else { throw error; } } The SDK exports APIConnectionError , APIProtocolError , APIStatusError , AbortError , AuthenticationError , NotFoundError , OverloadedError , PermissionDeniedError , RateLimitError , and TimeoutError . Set XAI DEBUG=1 to print each request's method, URL, and headers as a cURL command: XAI DEBUG=1 node app.js Authentication headers and common credential fields are redacted. Request bodies are always omitted because prompts and tool outputs may contain sensitive data. Structured API failures expose error.type , error.code , and error.param when the server returns them. The SpaceXAI request ID is also available at response.http.requestId and error.requestId . Include it when reporting an API problem. Every request also sends an x-client-request-id header with a UUID generated by the SDK. The ID stays the same across retries and is available at response.http.clientRequestId and error.clientRequestId , even when a request fails before the API responds. To use your own ID, set x-client-request-id in the request headers . Install dependencies and run the checks: pnpm install pnpm check pnpm pack:check pnpm pack:smoke Run every release gate, including the dependency audit: pnpm release:check Create a distributable tarball and SHA-256 checksum in artifacts/ : pnpm pack:artifact Generated API types live in src/generated/types.ts , speech tags, voice IDs, and voice model IDs in src/generated/voice.ts , and the model ID union in src/models.ts . Run pnpm generate:types for API types, pnpm generate:voice for the Voice API values, and pnpm generate:models for model IDs instead of editing those files by hand. We aren't accepting outside contributions yet, but plan to later. Please open an issue https://github.com/xai-org/xai-sdk-ts/issues for bugs and feature requests. CONTRIBUTING.md https://github.com/xai-org/xai-sdk-ts/blob/main/CONTRIBUTING.md covers local development. Report suspected vulnerabilities privately as described in SECURITY.md https://github.com/xai-org/xai-sdk-ts/blob/main/SECURITY.md . Do not include credentials, confidential data, or unredacted request bodies in public issues. Licensed under the Apache License 2.0 https://github.com/xai-org/xai-sdk-ts/blob/main/LICENSE .