openai
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The official TypeScript library for the OpenAI API
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text/typescript
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;
}
}
}
}