forked from XiaoMo/ChatGPT-Next-Web
223 lines
6.6 KiB
TypeScript
223 lines
6.6 KiB
TypeScript
import { Google, REQUEST_TIMEOUT_MS } from "@/app/constant";
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import { ChatOptions, getHeaders, LLMApi, LLMModel, LLMUsage } from "../api";
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import { useAccessStore, useAppConfig, useChatStore } from "@/app/store";
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import {
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EventStreamContentType,
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fetchEventSource,
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} from "@fortaine/fetch-event-source";
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import { prettyObject } from "@/app/utils/format";
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import { getClientConfig } from "@/app/config/client";
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import Locale from "../../locales";
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import { getServerSideConfig } from "@/app/config/server";
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export class GeminiProApi implements LLMApi {
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extractMessage(res: any) {
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console.log("[Response] gemini-pro response: ", res);
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return (
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res?.candidates?.at(0)?.content?.parts.at(0)?.text ||
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res?.error?.message ||
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""
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);
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}
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async chat(options: ChatOptions): Promise<void> {
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const messages = options.messages.map((v) => ({
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role: v.role.replace("assistant", "model").replace("system", "user"),
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parts: [{ text: v.content }],
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}));
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// google requires that role in neighboring messages must not be the same
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for (let i = 0; i < messages.length - 1; ) {
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// Check if current and next item both have the role "model"
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if (messages[i].role === messages[i + 1].role) {
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// Concatenate the 'parts' of the current and next item
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messages[i].parts = messages[i].parts.concat(messages[i + 1].parts);
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// Remove the next item
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messages.splice(i + 1, 1);
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} else {
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// Move to the next item
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i++;
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}
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}
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const modelConfig = {
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...useAppConfig.getState().modelConfig,
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...useChatStore.getState().currentSession().mask.modelConfig,
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...{
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model: options.config.model,
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},
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};
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const requestPayload = {
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contents: messages,
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generationConfig: {
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// stopSequences: [
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// "Title"
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// ],
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temperature: modelConfig.temperature,
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maxOutputTokens: modelConfig.max_tokens,
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topP: modelConfig.top_p,
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// "topK": modelConfig.top_k,
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},
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};
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console.log("[Request] google payload: ", requestPayload);
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// todo: support stream later
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const shouldStream = false;
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const controller = new AbortController();
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options.onController?.(controller);
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try {
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const chatPath = this.path(Google.ChatPath);
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const chatPayload = {
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method: "POST",
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body: JSON.stringify(requestPayload),
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signal: controller.signal,
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headers: getHeaders(),
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};
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// make a fetch request
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const requestTimeoutId = setTimeout(
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() => controller.abort(),
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REQUEST_TIMEOUT_MS,
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);
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if (shouldStream) {
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let responseText = "";
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let remainText = "";
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let finished = false;
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// animate response to make it looks smooth
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function animateResponseText() {
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if (finished || controller.signal.aborted) {
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responseText += remainText;
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console.log("[Response Animation] finished");
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return;
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}
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if (remainText.length > 0) {
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const fetchCount = Math.max(1, Math.round(remainText.length / 60));
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const fetchText = remainText.slice(0, fetchCount);
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responseText += fetchText;
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remainText = remainText.slice(fetchCount);
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options.onUpdate?.(responseText, fetchText);
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}
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requestAnimationFrame(animateResponseText);
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}
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// start animaion
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animateResponseText();
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const finish = () => {
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if (!finished) {
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finished = true;
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options.onFinish(responseText + remainText);
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}
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};
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controller.signal.onabort = finish;
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fetchEventSource(chatPath, {
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...chatPayload,
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async onopen(res) {
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clearTimeout(requestTimeoutId);
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const contentType = res.headers.get("content-type");
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console.log(
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"[OpenAI] request response content type: ",
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contentType,
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);
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if (contentType?.startsWith("text/plain")) {
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responseText = await res.clone().text();
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return finish();
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}
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if (
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!res.ok ||
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!res.headers
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.get("content-type")
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?.startsWith(EventStreamContentType) ||
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res.status !== 200
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) {
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const responseTexts = [responseText];
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let extraInfo = await res.clone().text();
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try {
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const resJson = await res.clone().json();
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extraInfo = prettyObject(resJson);
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} catch {}
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if (res.status === 401) {
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responseTexts.push(Locale.Error.Unauthorized);
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}
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if (extraInfo) {
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responseTexts.push(extraInfo);
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}
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responseText = responseTexts.join("\n\n");
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return finish();
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}
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},
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onmessage(msg) {
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if (msg.data === "[DONE]" || finished) {
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return finish();
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}
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const text = msg.data;
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try {
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const json = JSON.parse(text) as {
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choices: Array<{
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delta: {
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content: string;
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};
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}>;
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};
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const delta = json.choices[0]?.delta?.content;
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if (delta) {
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remainText += delta;
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}
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} catch (e) {
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console.error("[Request] parse error", text);
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}
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},
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onclose() {
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finish();
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},
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onerror(e) {
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options.onError?.(e);
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throw e;
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},
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openWhenHidden: true,
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});
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} else {
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const res = await fetch(chatPath, chatPayload);
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clearTimeout(requestTimeoutId);
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const resJson = await res.json();
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if (resJson?.promptFeedback?.blockReason) {
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// being blocked
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options.onError?.(
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new Error(
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"Message is being blocked for reason: " +
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resJson.promptFeedback.blockReason,
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),
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);
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}
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const message = this.extractMessage(resJson);
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options.onFinish(message);
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}
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} catch (e) {
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console.log("[Request] failed to make a chat request", e);
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options.onError?.(e as Error);
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}
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}
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usage(): Promise<LLMUsage> {
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throw new Error("Method not implemented.");
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}
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async models(): Promise<LLMModel[]> {
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return [];
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}
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path(path: string): string {
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return "/api/google/" + path;
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}
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}
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