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openai

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The official TypeScript library for the OpenAI API

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import * as Core from "../core"; import { OpenAIError, APIUserAbortError } from "../error"; import { Completions, type ChatCompletion, type ChatCompletionChunk, type ChatCompletionCreateParams, type ChatCompletionCreateParamsBase, } from "../resources/chat/completions"; import { AbstractChatCompletionRunner, type AbstractChatCompletionRunnerEvents, } from './AbstractChatCompletionRunner'; import { type ReadableStream } from "../_shims/index"; import { Stream } from "../streaming"; export interface ChatCompletionStreamEvents extends AbstractChatCompletionRunnerEvents { content: (contentDelta: string, contentSnapshot: string) => void; chunk: (chunk: ChatCompletionChunk, snapshot: ChatCompletionSnapshot) => void; } export type ChatCompletionStreamParams = Omit<ChatCompletionCreateParamsBase, 'stream'> & { stream?: true; }; export class ChatCompletionStream extends AbstractChatCompletionRunner<ChatCompletionStreamEvents> implements AsyncIterable<ChatCompletionChunk> { #currentChatCompletionSnapshot: ChatCompletionSnapshot | undefined; get currentChatCompletionSnapshot(): ChatCompletionSnapshot | undefined { return this.#currentChatCompletionSnapshot; } /** * Intended for use on the frontend, consuming a stream produced with * `.toReadableStream()` on the backend. * * Note that messages sent to the model do not appear in `.on('message')` * in this context. */ static fromReadableStream(stream: ReadableStream): ChatCompletionStream { const runner = new ChatCompletionStream(); runner._run(() => runner._fromReadableStream(stream)); return runner; } static createChatCompletion( completions: Completions, params: ChatCompletionStreamParams, options?: Core.RequestOptions, ): ChatCompletionStream { const runner = new ChatCompletionStream(); runner._run(() => runner._runChatCompletion( completions, { ...params, stream: true }, { ...options, headers: { ...options?.headers, 'X-Stainless-Helper-Method': 'stream' } }, ), ); return runner; } #beginRequest() { if (this.ended) return; this.#currentChatCompletionSnapshot = undefined; } #addChunk(chunk: ChatCompletionChunk) { if (this.ended) return; const completion = this.#accumulateChatCompletion(chunk); this._emit('chunk', chunk, completion); const delta = chunk.choices[0]?.delta?.content; const snapshot = completion.choices[0]?.message; if (delta != null && snapshot?.role === 'assistant' && snapshot?.content) { this._emit('content', delta, snapshot.content); } } #endRequest(): ChatCompletion { if (this.ended) { throw new OpenAIError(`stream has ended, this shouldn't happen`); } const snapshot = this.#currentChatCompletionSnapshot; if (!snapshot) { throw new OpenAIError(`request ended without sending any chunks`); } this.#currentChatCompletionSnapshot = undefined; return finalizeChatCompletion(snapshot); } protected override async _createChatCompletion( completions: Completions, params: ChatCompletionCreateParams, options?: Core.RequestOptions, ): Promise<ChatCompletion> { const signal = options?.signal; if (signal) { if (signal.aborted) this.controller.abort(); signal.addEventListener('abort', () => this.controller.abort()); } this.#beginRequest(); const stream = await completions.create( { ...params, stream: true }, { ...options, signal: this.controller.signal }, ); this._connected(); for await (const chunk of stream) { this.#addChunk(chunk); } if (stream.controller.signal?.aborted) { throw new APIUserAbortError(); } return this._addChatCompletion(this.#endRequest()); } protected async _fromReadableStream( readableStream: ReadableStream, options?: Core.RequestOptions, ): Promise<ChatCompletion> { const signal = options?.signal; if (signal) { if (signal.aborted) this.controller.abort(); signal.addEventListener('abort', () => this.controller.abort()); } this.#beginRequest(); this._connected(); const stream = Stream.fromReadableStream<ChatCompletionChunk>(readableStream, this.controller); let chatId; for await (const chunk of stream) { if (chatId && chatId !== chunk.id) { // A new request has been made. this._addChatCompletion(this.#endRequest()); } this.#addChunk(chunk); chatId = chunk.id; } if (stream.controller.signal?.aborted) { throw new APIUserAbortError(); } return this._addChatCompletion(this.#endRequest()); } #accumulateChatCompletion(chunk: ChatCompletionChunk): ChatCompletionSnapshot { let snapshot = this.#currentChatCompletionSnapshot; const { choices, ...rest } = chunk; if (!snapshot) { snapshot = this.#currentChatCompletionSnapshot = { ...rest, choices: [], }; } else { Object.assign(snapshot, rest); } for (const { delta, finish_reason, index, logprobs = null, ...other } of chunk.choices) { let choice = snapshot.choices[index]; if (!choice) { choice = snapshot.choices[index] = { finish_reason, index, message: {}, logprobs, ...other }; } if (logprobs) { if (!choice.logprobs) { choice.logprobs = Object.assign({}, logprobs); } else { const { content, ...rest } = logprobs; Object.assign(choice.logprobs, rest); if (content) { choice.logprobs.content ??= []; choice.logprobs.content.push(...content); } } } if (finish_reason) choice.finish_reason = finish_reason; Object.assign(choice, other); if (!delta) continue; // Shouldn't happen; just in case. const { content, function_call, role, tool_calls, ...rest } = delta; Object.assign(choice.message, rest); if (content) choice.message.content = (choice.message.content || '') + content; if (role) choice.message.role = role; if (function_call) { if (!choice.message.function_call) { choice.message.function_call = function_call; } else { if (function_call.name) choice.message.function_call.name = function_call.name; if (function_call.arguments) { choice.message.function_call.arguments ??= ''; choice.message.function_call.arguments += function_call.arguments; } } } if (tool_calls) { if (!choice.message.tool_calls) choice.message.tool_calls = []; for (const { index, id, type, function: fn, ...rest } of tool_calls) { const tool_call = (choice.message.tool_calls[index] ??= {}); Object.assign(tool_call, rest); if (id) tool_call.id = id; if (type) tool_call.type = type; if (fn) tool_call.function ??= { arguments: '' }; if (fn?.name) tool_call.function!.name = fn.name; if (fn?.arguments) tool_call.function!.arguments += fn.arguments; } } } return snapshot; } [Symbol.asyncIterator](): AsyncIterator<ChatCompletionChunk> { const pushQueue: ChatCompletionChunk[] = []; const readQueue: { resolve: (chunk: ChatCompletionChunk | undefined) => void; reject: (err: unknown) => void; }[] = []; let done = false; this.on('chunk', (chunk) => { const reader = readQueue.shift(); if (reader) { reader.resolve(chunk); } else { pushQueue.push(chunk); } }); this.on('end', () => { done = true; for (const reader of readQueue) { reader.resolve(undefined); } readQueue.length = 0; }); this.on('abort', (err) => { done = true; for (const reader of readQueue) { reader.reject(err); } readQueue.length = 0; }); this.on('error', (err) => { done = true; for (const reader of readQueue) { reader.reject(err); } readQueue.length = 0; }); return { next: async (): Promise<IteratorResult<ChatCompletionChunk>> => { if (!pushQueue.length) { if (done) { return { value: undefined, done: true }; } return new Promise<ChatCompletionChunk | undefined>((resolve, reject) => readQueue.push({ resolve, reject }), ).then((chunk) => (chunk ? { value: chunk, done: false } : { value: undefined, done: true })); } const chunk = pushQueue.shift()!; return { value: chunk, done: false }; }, return: async () => { this.abort(); return { value: undefined, done: true }; }, }; } toReadableStream(): ReadableStream { const stream = new Stream(this[Symbol.asyncIterator].bind(this), this.controller); return stream.toReadableStream(); } } function finalizeChatCompletion(snapshot: ChatCompletionSnapshot): ChatCompletion { const { id, choices, created, model, system_fingerprint, ...rest } = snapshot; return { ...rest, id, choices: choices.map( ({ message, finish_reason, index, logprobs, ...choiceRest }): ChatCompletion.Choice => { if (!finish_reason) throw new OpenAIError(`missing finish_reason for choice ${index}`); const { content = null, function_call, tool_calls, ...messageRest } = message; const role = message.role as 'assistant'; // this is what we expect; in theory it could be different which would make our types a slight lie but would be fine. if (!role) throw new OpenAIError(`missing role for choice ${index}`); if (function_call) { const { arguments: args, name } = function_call; if (args == null) throw new OpenAIError(`missing function_call.arguments for choice ${index}`); if (!name) throw new OpenAIError(`missing function_call.name for choice ${index}`); return { ...choiceRest, message: { content, function_call: { arguments: args, name }, role }, finish_reason, index, logprobs, }; } if (tool_calls) { return { ...choiceRest, index, finish_reason, logprobs, message: { ...messageRest, role, content, tool_calls: tool_calls.map((tool_call, i) => { const { function: fn, type, id, ...toolRest } = tool_call; const { arguments: args, name, ...fnRest } = fn || {}; if (id == null) throw new OpenAIError(`missing choices[${index}].tool_calls[${i}].id\n${str(snapshot)}`); if (type == null) throw new OpenAIError(`missing choices[${index}].tool_calls[${i}].type\n${str(snapshot)}`); if (name == null) throw new OpenAIError( `missing choices[${index}].tool_calls[${i}].function.name\n${str(snapshot)}`, ); if (args == null) throw new OpenAIError( `missing choices[${index}].tool_calls[${i}].function.arguments\n${str(snapshot)}`, ); return { ...toolRest, id, type, function: { ...fnRest, name, arguments: args } }; }), }, }; } return { ...choiceRest, message: { ...messageRest, content, role }, finish_reason, index, logprobs, }; }, ), created, model, object: 'chat.completion', ...(system_fingerprint ? { system_fingerprint } : {}), }; } function str(x: unknown) { return JSON.stringify(x); } /** * Represents a streamed chunk of a chat completion response returned by model, * based on the provided input. */ export interface ChatCompletionSnapshot { /** * A unique identifier for the chat completion. */ id: string; /** * A list of chat completion choices. Can be more than one if `n` is greater * than 1. */ choices: Array<ChatCompletionSnapshot.Choice>; /** * The Unix timestamp (in seconds) of when the chat completion was created. */ created: number; /** * The model to generate the completion. */ model: string; // Note we do not include an "object" type on the snapshot, // because the object is not a valid "chat.completion" until finalized. // object: 'chat.completion'; /** * This fingerprint represents the backend configuration that the model runs with. * * Can be used in conjunction with the `seed` request parameter to understand when * backend changes have been made that might impact determinism. */ system_fingerprint?: string; } export namespace ChatCompletionSnapshot { export interface Choice { /** * A chat completion delta generated by streamed model responses. */ message: Choice.Message; /** * The reason the model stopped generating tokens. This will be `stop` if the model * hit a natural stop point or a provided stop sequence, `length` if the maximum * number of tokens specified in the request was reached, `content_filter` if * content was omitted due to a flag from our content filters, or `function_call` * if the model called a function. */ finish_reason: ChatCompletion.Choice['finish_reason'] | null; /** * Log probability information for the choice. */ logprobs: ChatCompletion.Choice.Logprobs | null; /** * The index of the choice in the list of choices. */ index: number; } export namespace Choice { /** * A chat completion delta generated by streamed model responses. */ export interface Message { /** * The contents of the chunk message. */ content?: string | null; /** * The name and arguments of a function that should be called, as generated by the * model. */ function_call?: Message.FunctionCall; tool_calls?: Array<Message.ToolCall>; /** * The role of the author of this message. */ role?: 'system' | 'user' | 'assistant' | 'function' | 'tool'; } export namespace Message { export interface ToolCall { /** * The ID of the tool call. */ id?: string; function?: ToolCall.Function; /** * The type of the tool. */ type?: 'function'; } export namespace ToolCall { export interface Function { /** * The arguments to call the function with, as generated by the model in JSON * format. Note that the model does not always generate valid JSON, and may * hallucinate parameters not defined by your function schema. Validate the * arguments in your code before calling your function. */ arguments?: string; /** * The name of the function to call. */ name?: string; } } /** * The name and arguments of a function that should be called, as generated by the * model. */ export interface FunctionCall { /** * The arguments to call the function with, as generated by the model in JSON * format. Note that the model does not always generate valid JSON, and may * hallucinate parameters not defined by your function schema. Validate the * arguments in your code before calling your function. */ arguments?: string; /** * The name of the function to call. */ name?: string; } } } }