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Compare commits
18 Commits
Leizhenpen
...
v2.16.0
Author | SHA1 | Date | |
---|---|---|---|
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377480b448 | ||
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8bd0d6a1a7 | ||
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12863f5213 | ||
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cf140d4228 | ||
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476d946f96 | ||
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9714258322 | ||
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48cd4b11b5 | ||
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77c78b230a | ||
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b44686b887 | ||
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34bdd4b945 | ||
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b0758cccde | ||
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98a11e56d2 | ||
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86f86962fb | ||
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2137aa65bf | ||
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18fa2cc30d | ||
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0bfc648085 | ||
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9f91c2d05c | ||
|
a029b4330b |
@@ -1,6 +1,6 @@
|
||||
<div align="center">
|
||||
|
||||
<a href='https://nextchat.dev/chat'>
|
||||
<a href='https://nextchat.club'>
|
||||
<img src="https://github.com/user-attachments/assets/83bdcc07-ae5e-4954-a53a-ac151ba6ccf3" width="1000" alt="icon"/>
|
||||
</a>
|
||||
|
||||
@@ -23,9 +23,10 @@ English / [简体中文](./README_CN.md)
|
||||
[![Linux][Linux-image]][download-url]
|
||||
|
||||
[NextChatAI](https://nextchat.dev/chat?utm_source=readme) / [Web App Demo](https://app.nextchat.dev) / [Desktop App](https://github.com/Yidadaa/ChatGPT-Next-Web/releases)
|
||||
[NextChatAI](https://nextchat.club?utm_source=readme) / [Web App Demo](https://app.nextchat.dev) / [Desktop App](https://github.com/Yidadaa/ChatGPT-Next-Web/releases) / [Discord](https://discord.gg/YCkeafCafC) / [Enterprise Edition](#enterprise-edition) / [Twitter](https://twitter.com/NextChatDev)
|
||||
|
||||
|
||||
[saas-url]: https://nextchat.dev/chat?utm_source=readme
|
||||
[saas-url]: https://nextchat.club?utm_source=readme
|
||||
[saas-image]: https://img.shields.io/badge/NextChat-Saas-green?logo=microsoftedge
|
||||
[web-url]: https://app.nextchat.dev/
|
||||
[download-url]: https://github.com/Yidadaa/ChatGPT-Next-Web/releases
|
||||
|
@@ -8,7 +8,7 @@
|
||||
|
||||
一键免费部署你的私人 ChatGPT 网页应用,支持 Claude, GPT4 & Gemini Pro 模型。
|
||||
|
||||
[NextChatAI](https://nextchat.dev/chat?utm_source=readme) / [企业版](#%E4%BC%81%E4%B8%9A%E7%89%88) / [演示 Demo](https://chat-gpt-next-web.vercel.app/) / [反馈 Issues](https://github.com/Yidadaa/ChatGPT-Next-Web/issues) / [加入 Discord](https://discord.gg/zrhvHCr79N)
|
||||
[NextChatAI](https://nextchat.club?utm_source=readme) / [企业版](#%E4%BC%81%E4%B8%9A%E7%89%88) / [演示 Demo](https://chat-gpt-next-web.vercel.app/) / [反馈 Issues](https://github.com/Yidadaa/ChatGPT-Next-Web/issues) / [加入 Discord](https://discord.gg/zrhvHCr79N)
|
||||
|
||||
[<img src="https://vercel.com/button" alt="Deploy on Zeabur" height="30">](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2FChatGPTNextWeb%2FChatGPT-Next-Web&env=OPENAI_API_KEY&env=CODE&project-name=nextchat&repository-name=NextChat) [<img src="https://zeabur.com/button.svg" alt="Deploy on Zeabur" height="30">](https://zeabur.com/templates/ZBUEFA) [<img src="https://gitpod.io/button/open-in-gitpod.svg" alt="Open in Gitpod" height="30">](https://gitpod.io/#https://github.com/Yidadaa/ChatGPT-Next-Web)
|
||||
|
||||
|
@@ -5,7 +5,7 @@
|
||||
|
||||
ワンクリックで無料であなた専用の ChatGPT ウェブアプリをデプロイ。GPT3、GPT4 & Gemini Pro モデルをサポート。
|
||||
|
||||
[NextChatAI](https://nextchat.dev/chat?utm_source=readme) / [企業版](#企業版) / [デモ](https://chat-gpt-next-web.vercel.app/) / [フィードバック](https://github.com/Yidadaa/ChatGPT-Next-Web/issues) / [Discordに参加](https://discord.gg/zrhvHCr79N)
|
||||
[NextChatAI](https://nextchat.club?utm_source=readme) / [企業版](#企業版) / [デモ](https://chat-gpt-next-web.vercel.app/) / [フィードバック](https://github.com/Yidadaa/ChatGPT-Next-Web/issues) / [Discordに参加](https://discord.gg/zrhvHCr79N)
|
||||
|
||||
[<img src="https://vercel.com/button" alt="Zeaburでデプロイ" height="30">](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2FChatGPTNextWeb%2FChatGPT-Next-Web&env=OPENAI_API_KEY&env=CODE&project-name=nextchat&repository-name=NextChat) [<img src="https://zeabur.com/button.svg" alt="Zeaburでデプロイ" height="30">](https://zeabur.com/templates/ZBUEFA) [<img src="https://gitpod.io/button/open-in-gitpod.svg" alt="Gitpodで開く" height="30">](https://gitpod.io/#https://github.com/Yidadaa/ChatGPT-Next-Web)
|
||||
|
||||
|
@@ -14,8 +14,12 @@ function getModels(remoteModelRes: OpenAIListModelResponse) {
|
||||
if (config.disableGPT4) {
|
||||
remoteModelRes.data = remoteModelRes.data.filter(
|
||||
(m) =>
|
||||
!(m.id.startsWith("gpt-4") || m.id.startsWith("chatgpt-4o") || m.id.startsWith("o1") || m.id.startsWith("o3")) ||
|
||||
m.id.startsWith("gpt-4o-mini"),
|
||||
!(
|
||||
m.id.startsWith("gpt-4") ||
|
||||
m.id.startsWith("chatgpt-4o") ||
|
||||
m.id.startsWith("o1") ||
|
||||
m.id.startsWith("o3")
|
||||
) || m.id.startsWith("gpt-4o-mini"),
|
||||
);
|
||||
}
|
||||
|
||||
|
@@ -1,12 +1,13 @@
|
||||
"use client";
|
||||
import { ApiPath, Alibaba, ALIBABA_BASE_URL } from "@/app/constant";
|
||||
import {
|
||||
ApiPath,
|
||||
Alibaba,
|
||||
ALIBABA_BASE_URL,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
} from "@/app/constant";
|
||||
import { useAccessStore, useAppConfig, useChatStore } from "@/app/store";
|
||||
|
||||
useAccessStore,
|
||||
useAppConfig,
|
||||
useChatStore,
|
||||
ChatMessageTool,
|
||||
usePluginStore,
|
||||
} from "@/app/store";
|
||||
import { streamWithThink } from "@/app/utils/chat";
|
||||
import {
|
||||
ChatOptions,
|
||||
getHeaders,
|
||||
@@ -15,14 +16,12 @@ import {
|
||||
SpeechOptions,
|
||||
MultimodalContent,
|
||||
} from "../api";
|
||||
import Locale from "../../locales";
|
||||
import {
|
||||
EventStreamContentType,
|
||||
fetchEventSource,
|
||||
} from "@fortaine/fetch-event-source";
|
||||
import { prettyObject } from "@/app/utils/format";
|
||||
import { getClientConfig } from "@/app/config/client";
|
||||
import { getMessageTextContent } from "@/app/utils";
|
||||
import {
|
||||
getMessageTextContent,
|
||||
getMessageTextContentWithoutThinking,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
|
||||
export interface OpenAIListModelResponse {
|
||||
@@ -92,7 +91,10 @@ export class QwenApi implements LLMApi {
|
||||
async chat(options: ChatOptions) {
|
||||
const messages = options.messages.map((v) => ({
|
||||
role: v.role,
|
||||
content: getMessageTextContent(v),
|
||||
content:
|
||||
v.role === "assistant"
|
||||
? getMessageTextContentWithoutThinking(v)
|
||||
: getMessageTextContent(v),
|
||||
}));
|
||||
|
||||
const modelConfig = {
|
||||
@@ -122,134 +124,118 @@ export class QwenApi implements LLMApi {
|
||||
options.onController?.(controller);
|
||||
|
||||
try {
|
||||
const headers = {
|
||||
...getHeaders(),
|
||||
"X-DashScope-SSE": shouldStream ? "enable" : "disable",
|
||||
};
|
||||
|
||||
const chatPath = this.path(Alibaba.ChatPath);
|
||||
const chatPayload = {
|
||||
method: "POST",
|
||||
body: JSON.stringify(requestPayload),
|
||||
signal: controller.signal,
|
||||
headers: {
|
||||
...getHeaders(),
|
||||
"X-DashScope-SSE": shouldStream ? "enable" : "disable",
|
||||
},
|
||||
headers: headers,
|
||||
};
|
||||
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
let responseText = "";
|
||||
let remainText = "";
|
||||
let finished = false;
|
||||
let responseRes: Response;
|
||||
const [tools, funcs] = usePluginStore
|
||||
.getState()
|
||||
.getAsTools(
|
||||
useChatStore.getState().currentSession().mask?.plugin || [],
|
||||
);
|
||||
return streamWithThink(
|
||||
chatPath,
|
||||
requestPayload,
|
||||
headers,
|
||||
tools as any,
|
||||
funcs,
|
||||
controller,
|
||||
// parseSSE
|
||||
(text: string, runTools: ChatMessageTool[]) => {
|
||||
// console.log("parseSSE", text, runTools);
|
||||
const json = JSON.parse(text);
|
||||
const choices = json.output.choices as Array<{
|
||||
message: {
|
||||
content: string | null;
|
||||
tool_calls: ChatMessageTool[];
|
||||
reasoning_content: string | null;
|
||||
};
|
||||
}>;
|
||||
|
||||
// animate response to make it looks smooth
|
||||
function animateResponseText() {
|
||||
if (finished || controller.signal.aborted) {
|
||||
responseText += remainText;
|
||||
console.log("[Response Animation] finished");
|
||||
if (responseText?.length === 0) {
|
||||
options.onError?.(new Error("empty response from server"));
|
||||
}
|
||||
return;
|
||||
}
|
||||
if (!choices?.length) return { isThinking: false, content: "" };
|
||||
|
||||
if (remainText.length > 0) {
|
||||
const fetchCount = Math.max(1, Math.round(remainText.length / 60));
|
||||
const fetchText = remainText.slice(0, fetchCount);
|
||||
responseText += fetchText;
|
||||
remainText = remainText.slice(fetchCount);
|
||||
options.onUpdate?.(responseText, fetchText);
|
||||
}
|
||||
|
||||
requestAnimationFrame(animateResponseText);
|
||||
}
|
||||
|
||||
// start animaion
|
||||
animateResponseText();
|
||||
|
||||
const finish = () => {
|
||||
if (!finished) {
|
||||
finished = true;
|
||||
options.onFinish(responseText + remainText, responseRes);
|
||||
}
|
||||
};
|
||||
|
||||
controller.signal.onabort = finish;
|
||||
|
||||
fetchEventSource(chatPath, {
|
||||
fetch: fetch as any,
|
||||
...chatPayload,
|
||||
async onopen(res) {
|
||||
clearTimeout(requestTimeoutId);
|
||||
const contentType = res.headers.get("content-type");
|
||||
console.log(
|
||||
"[Alibaba] request response content type: ",
|
||||
contentType,
|
||||
);
|
||||
responseRes = res;
|
||||
|
||||
if (contentType?.startsWith("text/plain")) {
|
||||
responseText = await res.clone().text();
|
||||
return finish();
|
||||
const tool_calls = choices[0]?.message?.tool_calls;
|
||||
if (tool_calls?.length > 0) {
|
||||
const index = tool_calls[0]?.index;
|
||||
const id = tool_calls[0]?.id;
|
||||
const args = tool_calls[0]?.function?.arguments;
|
||||
if (id) {
|
||||
runTools.push({
|
||||
id,
|
||||
type: tool_calls[0]?.type,
|
||||
function: {
|
||||
name: tool_calls[0]?.function?.name as string,
|
||||
arguments: args,
|
||||
},
|
||||
});
|
||||
} else {
|
||||
// @ts-ignore
|
||||
runTools[index]["function"]["arguments"] += args;
|
||||
}
|
||||
}
|
||||
|
||||
const reasoning = choices[0]?.message?.reasoning_content;
|
||||
const content = choices[0]?.message?.content;
|
||||
|
||||
// Skip if both content and reasoning_content are empty or null
|
||||
if (
|
||||
!res.ok ||
|
||||
!res.headers
|
||||
.get("content-type")
|
||||
?.startsWith(EventStreamContentType) ||
|
||||
res.status !== 200
|
||||
(!reasoning || reasoning.length === 0) &&
|
||||
(!content || content.length === 0)
|
||||
) {
|
||||
const responseTexts = [responseText];
|
||||
let extraInfo = await res.clone().text();
|
||||
try {
|
||||
const resJson = await res.clone().json();
|
||||
extraInfo = prettyObject(resJson);
|
||||
} catch {}
|
||||
|
||||
if (res.status === 401) {
|
||||
responseTexts.push(Locale.Error.Unauthorized);
|
||||
}
|
||||
|
||||
if (extraInfo) {
|
||||
responseTexts.push(extraInfo);
|
||||
}
|
||||
|
||||
responseText = responseTexts.join("\n\n");
|
||||
|
||||
return finish();
|
||||
return {
|
||||
isThinking: false,
|
||||
content: "",
|
||||
};
|
||||
}
|
||||
},
|
||||
onmessage(msg) {
|
||||
if (msg.data === "[DONE]" || finished) {
|
||||
return finish();
|
||||
}
|
||||
const text = msg.data;
|
||||
try {
|
||||
const json = JSON.parse(text);
|
||||
const choices = json.output.choices as Array<{
|
||||
message: { content: string };
|
||||
}>;
|
||||
const delta = choices[0]?.message?.content;
|
||||
if (delta) {
|
||||
remainText += delta;
|
||||
}
|
||||
} catch (e) {
|
||||
console.error("[Request] parse error", text, msg);
|
||||
|
||||
if (reasoning && reasoning.length > 0) {
|
||||
return {
|
||||
isThinking: true,
|
||||
content: reasoning,
|
||||
};
|
||||
} else if (content && content.length > 0) {
|
||||
return {
|
||||
isThinking: false,
|
||||
content: content,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
isThinking: false,
|
||||
content: "",
|
||||
};
|
||||
},
|
||||
onclose() {
|
||||
finish();
|
||||
// processToolMessage, include tool_calls message and tool call results
|
||||
(
|
||||
requestPayload: RequestPayload,
|
||||
toolCallMessage: any,
|
||||
toolCallResult: any[],
|
||||
) => {
|
||||
requestPayload?.input?.messages?.splice(
|
||||
requestPayload?.input?.messages?.length,
|
||||
0,
|
||||
toolCallMessage,
|
||||
...toolCallResult,
|
||||
);
|
||||
},
|
||||
onerror(e) {
|
||||
options.onError?.(e);
|
||||
throw e;
|
||||
},
|
||||
openWhenHidden: true,
|
||||
});
|
||||
options,
|
||||
);
|
||||
} else {
|
||||
const res = await fetch(chatPath, chatPayload);
|
||||
clearTimeout(requestTimeoutId);
|
||||
|
@@ -1,10 +1,5 @@
|
||||
"use client";
|
||||
import {
|
||||
ApiPath,
|
||||
Baidu,
|
||||
BAIDU_BASE_URL,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
} from "@/app/constant";
|
||||
import { ApiPath, Baidu, BAIDU_BASE_URL } from "@/app/constant";
|
||||
import { useAccessStore, useAppConfig, useChatStore } from "@/app/store";
|
||||
import { getAccessToken } from "@/app/utils/baidu";
|
||||
|
||||
@@ -23,7 +18,7 @@ import {
|
||||
} from "@fortaine/fetch-event-source";
|
||||
import { prettyObject } from "@/app/utils/format";
|
||||
import { getClientConfig } from "@/app/config/client";
|
||||
import { getMessageTextContent } from "@/app/utils";
|
||||
import { getMessageTextContent, getTimeoutMSByModel } from "@/app/utils";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
|
||||
export interface OpenAIListModelResponse {
|
||||
@@ -155,7 +150,7 @@ export class ErnieApi implements LLMApi {
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
|
@@ -1,11 +1,12 @@
|
||||
"use client";
|
||||
import { ApiPath, ByteDance, BYTEDANCE_BASE_URL } from "@/app/constant";
|
||||
import {
|
||||
ApiPath,
|
||||
ByteDance,
|
||||
BYTEDANCE_BASE_URL,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
} from "@/app/constant";
|
||||
import { useAccessStore, useAppConfig, useChatStore } from "@/app/store";
|
||||
useAccessStore,
|
||||
useAppConfig,
|
||||
useChatStore,
|
||||
ChatMessageTool,
|
||||
usePluginStore,
|
||||
} from "@/app/store";
|
||||
|
||||
import {
|
||||
ChatOptions,
|
||||
@@ -15,14 +16,14 @@ import {
|
||||
MultimodalContent,
|
||||
SpeechOptions,
|
||||
} from "../api";
|
||||
import Locale from "../../locales";
|
||||
import {
|
||||
EventStreamContentType,
|
||||
fetchEventSource,
|
||||
} from "@fortaine/fetch-event-source";
|
||||
import { prettyObject } from "@/app/utils/format";
|
||||
|
||||
import { streamWithThink } from "@/app/utils/chat";
|
||||
import { getClientConfig } from "@/app/config/client";
|
||||
import { preProcessImageContent } from "@/app/utils/chat";
|
||||
import {
|
||||
getMessageTextContentWithoutThinking,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
|
||||
export interface OpenAIListModelResponse {
|
||||
@@ -34,7 +35,7 @@ export interface OpenAIListModelResponse {
|
||||
}>;
|
||||
}
|
||||
|
||||
interface RequestPayload {
|
||||
interface RequestPayloadForByteDance {
|
||||
messages: {
|
||||
role: "system" | "user" | "assistant";
|
||||
content: string | MultimodalContent[];
|
||||
@@ -86,7 +87,10 @@ export class DoubaoApi implements LLMApi {
|
||||
async chat(options: ChatOptions) {
|
||||
const messages: ChatOptions["messages"] = [];
|
||||
for (const v of options.messages) {
|
||||
const content = await preProcessImageContent(v.content);
|
||||
const content =
|
||||
v.role === "assistant"
|
||||
? getMessageTextContentWithoutThinking(v)
|
||||
: await preProcessImageContent(v.content);
|
||||
messages.push({ role: v.role, content });
|
||||
}
|
||||
|
||||
@@ -99,7 +103,7 @@ export class DoubaoApi implements LLMApi {
|
||||
};
|
||||
|
||||
const shouldStream = !!options.config.stream;
|
||||
const requestPayload: RequestPayload = {
|
||||
const requestPayload: RequestPayloadForByteDance = {
|
||||
messages,
|
||||
stream: shouldStream,
|
||||
model: modelConfig.model,
|
||||
@@ -124,119 +128,101 @@ export class DoubaoApi implements LLMApi {
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
let responseText = "";
|
||||
let remainText = "";
|
||||
let finished = false;
|
||||
let responseRes: Response;
|
||||
const [tools, funcs] = usePluginStore
|
||||
.getState()
|
||||
.getAsTools(
|
||||
useChatStore.getState().currentSession().mask?.plugin || [],
|
||||
);
|
||||
return streamWithThink(
|
||||
chatPath,
|
||||
requestPayload,
|
||||
getHeaders(),
|
||||
tools as any,
|
||||
funcs,
|
||||
controller,
|
||||
// parseSSE
|
||||
(text: string, runTools: ChatMessageTool[]) => {
|
||||
// console.log("parseSSE", text, runTools);
|
||||
const json = JSON.parse(text);
|
||||
const choices = json.choices as Array<{
|
||||
delta: {
|
||||
content: string | null;
|
||||
tool_calls: ChatMessageTool[];
|
||||
reasoning_content: string | null;
|
||||
};
|
||||
}>;
|
||||
|
||||
// animate response to make it looks smooth
|
||||
function animateResponseText() {
|
||||
if (finished || controller.signal.aborted) {
|
||||
responseText += remainText;
|
||||
console.log("[Response Animation] finished");
|
||||
if (responseText?.length === 0) {
|
||||
options.onError?.(new Error("empty response from server"));
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
if (remainText.length > 0) {
|
||||
const fetchCount = Math.max(1, Math.round(remainText.length / 60));
|
||||
const fetchText = remainText.slice(0, fetchCount);
|
||||
responseText += fetchText;
|
||||
remainText = remainText.slice(fetchCount);
|
||||
options.onUpdate?.(responseText, fetchText);
|
||||
}
|
||||
|
||||
requestAnimationFrame(animateResponseText);
|
||||
}
|
||||
|
||||
// start animaion
|
||||
animateResponseText();
|
||||
|
||||
const finish = () => {
|
||||
if (!finished) {
|
||||
finished = true;
|
||||
options.onFinish(responseText + remainText, responseRes);
|
||||
}
|
||||
};
|
||||
|
||||
controller.signal.onabort = finish;
|
||||
|
||||
fetchEventSource(chatPath, {
|
||||
fetch: fetch as any,
|
||||
...chatPayload,
|
||||
async onopen(res) {
|
||||
clearTimeout(requestTimeoutId);
|
||||
const contentType = res.headers.get("content-type");
|
||||
console.log(
|
||||
"[ByteDance] request response content type: ",
|
||||
contentType,
|
||||
);
|
||||
responseRes = res;
|
||||
if (contentType?.startsWith("text/plain")) {
|
||||
responseText = await res.clone().text();
|
||||
return finish();
|
||||
if (!choices?.length) return { isThinking: false, content: "" };
|
||||
|
||||
const tool_calls = choices[0]?.delta?.tool_calls;
|
||||
if (tool_calls?.length > 0) {
|
||||
const index = tool_calls[0]?.index;
|
||||
const id = tool_calls[0]?.id;
|
||||
const args = tool_calls[0]?.function?.arguments;
|
||||
if (id) {
|
||||
runTools.push({
|
||||
id,
|
||||
type: tool_calls[0]?.type,
|
||||
function: {
|
||||
name: tool_calls[0]?.function?.name as string,
|
||||
arguments: args,
|
||||
},
|
||||
});
|
||||
} else {
|
||||
// @ts-ignore
|
||||
runTools[index]["function"]["arguments"] += args;
|
||||
}
|
||||
}
|
||||
const reasoning = choices[0]?.delta?.reasoning_content;
|
||||
const content = choices[0]?.delta?.content;
|
||||
|
||||
// Skip if both content and reasoning_content are empty or null
|
||||
if (
|
||||
!res.ok ||
|
||||
!res.headers
|
||||
.get("content-type")
|
||||
?.startsWith(EventStreamContentType) ||
|
||||
res.status !== 200
|
||||
(!reasoning || reasoning.length === 0) &&
|
||||
(!content || content.length === 0)
|
||||
) {
|
||||
const responseTexts = [responseText];
|
||||
let extraInfo = await res.clone().text();
|
||||
try {
|
||||
const resJson = await res.clone().json();
|
||||
extraInfo = prettyObject(resJson);
|
||||
} catch {}
|
||||
|
||||
if (res.status === 401) {
|
||||
responseTexts.push(Locale.Error.Unauthorized);
|
||||
}
|
||||
|
||||
if (extraInfo) {
|
||||
responseTexts.push(extraInfo);
|
||||
}
|
||||
|
||||
responseText = responseTexts.join("\n\n");
|
||||
|
||||
return finish();
|
||||
return {
|
||||
isThinking: false,
|
||||
content: "",
|
||||
};
|
||||
}
|
||||
},
|
||||
onmessage(msg) {
|
||||
if (msg.data === "[DONE]" || finished) {
|
||||
return finish();
|
||||
}
|
||||
const text = msg.data;
|
||||
try {
|
||||
const json = JSON.parse(text);
|
||||
const choices = json.choices as Array<{
|
||||
delta: { content: string };
|
||||
}>;
|
||||
const delta = choices[0]?.delta?.content;
|
||||
if (delta) {
|
||||
remainText += delta;
|
||||
}
|
||||
} catch (e) {
|
||||
console.error("[Request] parse error", text, msg);
|
||||
|
||||
if (reasoning && reasoning.length > 0) {
|
||||
return {
|
||||
isThinking: true,
|
||||
content: reasoning,
|
||||
};
|
||||
} else if (content && content.length > 0) {
|
||||
return {
|
||||
isThinking: false,
|
||||
content: content,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
isThinking: false,
|
||||
content: "",
|
||||
};
|
||||
},
|
||||
onclose() {
|
||||
finish();
|
||||
// processToolMessage, include tool_calls message and tool call results
|
||||
(
|
||||
requestPayload: RequestPayloadForByteDance,
|
||||
toolCallMessage: any,
|
||||
toolCallResult: any[],
|
||||
) => {
|
||||
requestPayload?.messages?.splice(
|
||||
requestPayload?.messages?.length,
|
||||
0,
|
||||
toolCallMessage,
|
||||
...toolCallResult,
|
||||
);
|
||||
},
|
||||
onerror(e) {
|
||||
options.onError?.(e);
|
||||
throw e;
|
||||
},
|
||||
openWhenHidden: true,
|
||||
});
|
||||
options,
|
||||
);
|
||||
} else {
|
||||
const res = await fetch(chatPath, chatPayload);
|
||||
clearTimeout(requestTimeoutId);
|
||||
|
@@ -1,12 +1,6 @@
|
||||
"use client";
|
||||
// azure and openai, using same models. so using same LLMApi.
|
||||
import {
|
||||
ApiPath,
|
||||
DEEPSEEK_BASE_URL,
|
||||
DeepSeek,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
REQUEST_TIMEOUT_MS_FOR_THINKING,
|
||||
} from "@/app/constant";
|
||||
import { ApiPath, DEEPSEEK_BASE_URL, DeepSeek } from "@/app/constant";
|
||||
import {
|
||||
useAccessStore,
|
||||
useAppConfig,
|
||||
@@ -26,6 +20,7 @@ import { getClientConfig } from "@/app/config/client";
|
||||
import {
|
||||
getMessageTextContent,
|
||||
getMessageTextContentWithoutThinking,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { RequestPayload } from "./openai";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
@@ -116,16 +111,10 @@ export class DeepSeekApi implements LLMApi {
|
||||
headers: getHeaders(),
|
||||
};
|
||||
|
||||
// console.log(chatPayload);
|
||||
|
||||
const isR1 =
|
||||
options.config.model.endsWith("-reasoner") ||
|
||||
options.config.model.endsWith("-r1");
|
||||
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
isR1 ? REQUEST_TIMEOUT_MS_FOR_THINKING : REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
@@ -176,8 +165,8 @@ export class DeepSeekApi implements LLMApi {
|
||||
|
||||
// Skip if both content and reasoning_content are empty or null
|
||||
if (
|
||||
(!reasoning || reasoning.trim().length === 0) &&
|
||||
(!content || content.trim().length === 0)
|
||||
(!reasoning || reasoning.length === 0) &&
|
||||
(!content || content.length === 0)
|
||||
) {
|
||||
return {
|
||||
isThinking: false,
|
||||
@@ -185,12 +174,12 @@ export class DeepSeekApi implements LLMApi {
|
||||
};
|
||||
}
|
||||
|
||||
if (reasoning && reasoning.trim().length > 0) {
|
||||
if (reasoning && reasoning.length > 0) {
|
||||
return {
|
||||
isThinking: true,
|
||||
content: reasoning,
|
||||
};
|
||||
} else if (content && content.trim().length > 0) {
|
||||
} else if (content && content.length > 0) {
|
||||
return {
|
||||
isThinking: false,
|
||||
content: content,
|
||||
|
@@ -1,10 +1,5 @@
|
||||
"use client";
|
||||
import {
|
||||
ApiPath,
|
||||
CHATGLM_BASE_URL,
|
||||
ChatGLM,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
} from "@/app/constant";
|
||||
import { ApiPath, CHATGLM_BASE_URL, ChatGLM } from "@/app/constant";
|
||||
import {
|
||||
useAccessStore,
|
||||
useAppConfig,
|
||||
@@ -21,7 +16,11 @@ import {
|
||||
SpeechOptions,
|
||||
} from "../api";
|
||||
import { getClientConfig } from "@/app/config/client";
|
||||
import { getMessageTextContent, isVisionModel } from "@/app/utils";
|
||||
import {
|
||||
getMessageTextContent,
|
||||
isVisionModel,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { RequestPayload } from "./openai";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
import { preProcessImageContent } from "@/app/utils/chat";
|
||||
@@ -191,7 +190,7 @@ export class ChatGLMApi implements LLMApi {
|
||||
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (modelType === "image" || modelType === "video") {
|
||||
|
@@ -1,9 +1,4 @@
|
||||
import {
|
||||
ApiPath,
|
||||
Google,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
REQUEST_TIMEOUT_MS_FOR_THINKING,
|
||||
} from "@/app/constant";
|
||||
import { ApiPath, Google } from "@/app/constant";
|
||||
import {
|
||||
ChatOptions,
|
||||
getHeaders,
|
||||
@@ -27,6 +22,7 @@ import {
|
||||
getMessageTextContent,
|
||||
getMessageImages,
|
||||
isVisionModel,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { preProcessImageContent } from "@/app/utils/chat";
|
||||
import { nanoid } from "nanoid";
|
||||
@@ -206,7 +202,7 @@ export class GeminiProApi implements LLMApi {
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
isThinking ? REQUEST_TIMEOUT_MS_FOR_THINKING : REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
|
@@ -8,7 +8,6 @@ import {
|
||||
Azure,
|
||||
REQUEST_TIMEOUT_MS,
|
||||
ServiceProvider,
|
||||
REQUEST_TIMEOUT_MS_FOR_THINKING,
|
||||
} from "@/app/constant";
|
||||
import {
|
||||
ChatMessageTool,
|
||||
@@ -22,7 +21,7 @@ import {
|
||||
preProcessImageContent,
|
||||
uploadImage,
|
||||
base64Image2Blob,
|
||||
stream,
|
||||
streamWithThink,
|
||||
} from "@/app/utils/chat";
|
||||
import { cloudflareAIGatewayUrl } from "@/app/utils/cloudflare";
|
||||
import { ModelSize, DalleQuality, DalleStyle } from "@/app/typing";
|
||||
@@ -42,6 +41,7 @@ import {
|
||||
getMessageTextContent,
|
||||
isVisionModel,
|
||||
isDalle3 as _isDalle3,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
|
||||
@@ -294,7 +294,7 @@ export class ChatGPTApi implements LLMApi {
|
||||
useChatStore.getState().currentSession().mask?.plugin || [],
|
||||
);
|
||||
// console.log("getAsTools", tools, funcs);
|
||||
stream(
|
||||
streamWithThink(
|
||||
chatPath,
|
||||
requestPayload,
|
||||
getHeaders(),
|
||||
@@ -309,8 +309,12 @@ export class ChatGPTApi implements LLMApi {
|
||||
delta: {
|
||||
content: string;
|
||||
tool_calls: ChatMessageTool[];
|
||||
reasoning_content: string | null;
|
||||
};
|
||||
}>;
|
||||
|
||||
if (!choices?.length) return { isThinking: false, content: "" };
|
||||
|
||||
const tool_calls = choices[0]?.delta?.tool_calls;
|
||||
if (tool_calls?.length > 0) {
|
||||
const id = tool_calls[0]?.id;
|
||||
@@ -330,7 +334,37 @@ export class ChatGPTApi implements LLMApi {
|
||||
runTools[index]["function"]["arguments"] += args;
|
||||
}
|
||||
}
|
||||
return choices[0]?.delta?.content;
|
||||
|
||||
const reasoning = choices[0]?.delta?.reasoning_content;
|
||||
const content = choices[0]?.delta?.content;
|
||||
|
||||
// Skip if both content and reasoning_content are empty or null
|
||||
if (
|
||||
(!reasoning || reasoning.length === 0) &&
|
||||
(!content || content.length === 0)
|
||||
) {
|
||||
return {
|
||||
isThinking: false,
|
||||
content: "",
|
||||
};
|
||||
}
|
||||
|
||||
if (reasoning && reasoning.length > 0) {
|
||||
return {
|
||||
isThinking: true,
|
||||
content: reasoning,
|
||||
};
|
||||
} else if (content && content.length > 0) {
|
||||
return {
|
||||
isThinking: false,
|
||||
content: content,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
isThinking: false,
|
||||
content: "",
|
||||
};
|
||||
},
|
||||
// processToolMessage, include tool_calls message and tool call results
|
||||
(
|
||||
@@ -362,9 +396,7 @@ export class ChatGPTApi implements LLMApi {
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
isDalle3 || isO1OrO3
|
||||
? REQUEST_TIMEOUT_MS_FOR_THINKING
|
||||
: REQUEST_TIMEOUT_MS, // dalle3 using b64_json is slow.
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
const res = await fetch(chatPath, chatPayload);
|
||||
|
@@ -4,7 +4,7 @@ import {
|
||||
ApiPath,
|
||||
SILICONFLOW_BASE_URL,
|
||||
SiliconFlow,
|
||||
REQUEST_TIMEOUT_MS_FOR_THINKING,
|
||||
DEFAULT_MODELS,
|
||||
} from "@/app/constant";
|
||||
import {
|
||||
useAccessStore,
|
||||
@@ -13,7 +13,7 @@ import {
|
||||
ChatMessageTool,
|
||||
usePluginStore,
|
||||
} from "@/app/store";
|
||||
import { streamWithThink } from "@/app/utils/chat";
|
||||
import { preProcessImageContent, streamWithThink } from "@/app/utils/chat";
|
||||
import {
|
||||
ChatOptions,
|
||||
getHeaders,
|
||||
@@ -25,12 +25,23 @@ import { getClientConfig } from "@/app/config/client";
|
||||
import {
|
||||
getMessageTextContent,
|
||||
getMessageTextContentWithoutThinking,
|
||||
isVisionModel,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import { RequestPayload } from "./openai";
|
||||
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
export interface SiliconFlowListModelResponse {
|
||||
object: string;
|
||||
data: Array<{
|
||||
id: string;
|
||||
object: string;
|
||||
root: string;
|
||||
}>;
|
||||
}
|
||||
|
||||
export class SiliconflowApi implements LLMApi {
|
||||
private disableListModels = true;
|
||||
private disableListModels = false;
|
||||
|
||||
path(path: string): string {
|
||||
const accessStore = useAccessStore.getState();
|
||||
@@ -71,13 +82,16 @@ export class SiliconflowApi implements LLMApi {
|
||||
}
|
||||
|
||||
async chat(options: ChatOptions) {
|
||||
const visionModel = isVisionModel(options.config.model);
|
||||
const messages: ChatOptions["messages"] = [];
|
||||
for (const v of options.messages) {
|
||||
if (v.role === "assistant") {
|
||||
const content = getMessageTextContentWithoutThinking(v);
|
||||
messages.push({ role: v.role, content });
|
||||
} else {
|
||||
const content = getMessageTextContent(v);
|
||||
const content = visionModel
|
||||
? await preProcessImageContent(v.content)
|
||||
: getMessageTextContent(v);
|
||||
messages.push({ role: v.role, content });
|
||||
}
|
||||
}
|
||||
@@ -123,7 +137,7 @@ export class SiliconflowApi implements LLMApi {
|
||||
// Use extended timeout for thinking models as they typically require more processing time
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS_FOR_THINKING,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
@@ -238,6 +252,36 @@ export class SiliconflowApi implements LLMApi {
|
||||
}
|
||||
|
||||
async models(): Promise<LLMModel[]> {
|
||||
return [];
|
||||
if (this.disableListModels) {
|
||||
return DEFAULT_MODELS.slice();
|
||||
}
|
||||
|
||||
const res = await fetch(this.path(SiliconFlow.ListModelPath), {
|
||||
method: "GET",
|
||||
headers: {
|
||||
...getHeaders(),
|
||||
},
|
||||
});
|
||||
|
||||
const resJson = (await res.json()) as SiliconFlowListModelResponse;
|
||||
const chatModels = resJson.data;
|
||||
console.log("[Models]", chatModels);
|
||||
|
||||
if (!chatModels) {
|
||||
return [];
|
||||
}
|
||||
|
||||
let seq = 1000; //同 Constant.ts 中的排序保持一致
|
||||
return chatModels.map((m) => ({
|
||||
name: m.id,
|
||||
available: true,
|
||||
sorted: seq++,
|
||||
provider: {
|
||||
id: "siliconflow",
|
||||
providerName: "SiliconFlow",
|
||||
providerType: "siliconflow",
|
||||
sorted: 14,
|
||||
},
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
@@ -1,5 +1,5 @@
|
||||
"use client";
|
||||
import { ApiPath, TENCENT_BASE_URL, REQUEST_TIMEOUT_MS } from "@/app/constant";
|
||||
import { ApiPath, TENCENT_BASE_URL } from "@/app/constant";
|
||||
import { useAccessStore, useAppConfig, useChatStore } from "@/app/store";
|
||||
|
||||
import {
|
||||
@@ -17,7 +17,11 @@ import {
|
||||
} from "@fortaine/fetch-event-source";
|
||||
import { prettyObject } from "@/app/utils/format";
|
||||
import { getClientConfig } from "@/app/config/client";
|
||||
import { getMessageTextContent, isVisionModel } from "@/app/utils";
|
||||
import {
|
||||
getMessageTextContent,
|
||||
isVisionModel,
|
||||
getTimeoutMSByModel,
|
||||
} from "@/app/utils";
|
||||
import mapKeys from "lodash-es/mapKeys";
|
||||
import mapValues from "lodash-es/mapValues";
|
||||
import isArray from "lodash-es/isArray";
|
||||
@@ -135,7 +139,7 @@ export class HunyuanApi implements LLMApi {
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
|
@@ -1,6 +1,6 @@
|
||||
"use client";
|
||||
// azure and openai, using same models. so using same LLMApi.
|
||||
import { ApiPath, XAI_BASE_URL, XAI, REQUEST_TIMEOUT_MS } from "@/app/constant";
|
||||
import { ApiPath, XAI_BASE_URL, XAI } from "@/app/constant";
|
||||
import {
|
||||
useAccessStore,
|
||||
useAppConfig,
|
||||
@@ -17,6 +17,7 @@ import {
|
||||
SpeechOptions,
|
||||
} from "../api";
|
||||
import { getClientConfig } from "@/app/config/client";
|
||||
import { getTimeoutMSByModel } from "@/app/utils";
|
||||
import { preProcessImageContent } from "@/app/utils/chat";
|
||||
import { RequestPayload } from "./openai";
|
||||
import { fetch } from "@/app/utils/stream";
|
||||
@@ -103,7 +104,7 @@ export class XAIApi implements LLMApi {
|
||||
// make a fetch request
|
||||
const requestTimeoutId = setTimeout(
|
||||
() => controller.abort(),
|
||||
REQUEST_TIMEOUT_MS,
|
||||
getTimeoutMSByModel(options.config.model),
|
||||
);
|
||||
|
||||
if (shouldStream) {
|
||||
|
@@ -66,11 +66,11 @@ export function Avatar(props: { model?: ModelType; avatar?: string }) {
|
||||
LlmIcon = BotIconGemma;
|
||||
} else if (modelName.startsWith("claude")) {
|
||||
LlmIcon = BotIconClaude;
|
||||
} else if (modelName.startsWith("llama")) {
|
||||
} else if (modelName.toLowerCase().includes("llama")) {
|
||||
LlmIcon = BotIconMeta;
|
||||
} else if (modelName.startsWith("mixtral")) {
|
||||
LlmIcon = BotIconMistral;
|
||||
} else if (modelName.startsWith("deepseek")) {
|
||||
} else if (modelName.toLowerCase().includes("deepseek")) {
|
||||
LlmIcon = BotIconDeepseek;
|
||||
} else if (modelName.startsWith("moonshot")) {
|
||||
LlmIcon = BotIconMoonshot;
|
||||
@@ -85,7 +85,7 @@ export function Avatar(props: { model?: ModelType; avatar?: string }) {
|
||||
} else if (modelName.startsWith("doubao") || modelName.startsWith("ep-")) {
|
||||
LlmIcon = BotIconDoubao;
|
||||
} else if (
|
||||
modelName.startsWith("glm") ||
|
||||
modelName.toLowerCase().includes("glm") ||
|
||||
modelName.startsWith("cogview-") ||
|
||||
modelName.startsWith("cogvideox-")
|
||||
) {
|
||||
|
@@ -23,7 +23,6 @@ import CopyIcon from "../icons/copy.svg";
|
||||
import LoadingIcon from "../icons/three-dots.svg";
|
||||
import ChatGptIcon from "../icons/chatgpt.png";
|
||||
import ShareIcon from "../icons/share.svg";
|
||||
import BotIcon from "../icons/bot.png";
|
||||
|
||||
import DownloadIcon from "../icons/download.svg";
|
||||
import { useEffect, useMemo, useRef, useState } from "react";
|
||||
@@ -33,13 +32,13 @@ import dynamic from "next/dynamic";
|
||||
import NextImage from "next/image";
|
||||
|
||||
import { toBlob, toPng } from "html-to-image";
|
||||
import { DEFAULT_MASK_AVATAR } from "../store/mask";
|
||||
|
||||
import { prettyObject } from "../utils/format";
|
||||
import { EXPORT_MESSAGE_CLASS_NAME } from "../constant";
|
||||
import { getClientConfig } from "../config/client";
|
||||
import { type ClientApi, getClientApi } from "../client/api";
|
||||
import { getMessageTextContent } from "../utils";
|
||||
import { MaskAvatar } from "./mask";
|
||||
import clsx from "clsx";
|
||||
|
||||
const Markdown = dynamic(async () => (await import("./markdown")).Markdown, {
|
||||
@@ -407,22 +406,6 @@ export function PreviewActions(props: {
|
||||
);
|
||||
}
|
||||
|
||||
function ExportAvatar(props: { avatar: string }) {
|
||||
if (props.avatar === DEFAULT_MASK_AVATAR) {
|
||||
return (
|
||||
<img
|
||||
src={BotIcon.src}
|
||||
width={30}
|
||||
height={30}
|
||||
alt="bot"
|
||||
className="user-avatar"
|
||||
/>
|
||||
);
|
||||
}
|
||||
|
||||
return <Avatar avatar={props.avatar} />;
|
||||
}
|
||||
|
||||
export function ImagePreviewer(props: {
|
||||
messages: ChatMessage[];
|
||||
topic: string;
|
||||
@@ -546,9 +529,12 @@ export function ImagePreviewer(props: {
|
||||
github.com/ChatGPTNextWeb/ChatGPT-Next-Web
|
||||
</div>
|
||||
<div className={styles["icons"]}>
|
||||
<ExportAvatar avatar={config.avatar} />
|
||||
<MaskAvatar avatar={config.avatar} />
|
||||
<span className={styles["icon-space"]}>&</span>
|
||||
<ExportAvatar avatar={mask.avatar} />
|
||||
<MaskAvatar
|
||||
avatar={mask.avatar}
|
||||
model={session.mask.modelConfig.model}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
<div>
|
||||
@@ -576,9 +562,14 @@ export function ImagePreviewer(props: {
|
||||
key={i}
|
||||
>
|
||||
<div className={styles["avatar"]}>
|
||||
<ExportAvatar
|
||||
avatar={m.role === "user" ? config.avatar : mask.avatar}
|
||||
/>
|
||||
{m.role === "user" ? (
|
||||
<Avatar avatar={config.avatar}></Avatar>
|
||||
) : (
|
||||
<MaskAvatar
|
||||
avatar={session.mask.avatar}
|
||||
model={m.model || session.mask.modelConfig.model}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div className={styles["body"]}>
|
||||
|
@@ -258,6 +258,7 @@ export const ChatGLM = {
|
||||
export const SiliconFlow = {
|
||||
ExampleEndpoint: SILICONFLOW_BASE_URL,
|
||||
ChatPath: "v1/chat/completions",
|
||||
ListModelPath: "v1/models?&sub_type=chat",
|
||||
};
|
||||
|
||||
export const DEFAULT_INPUT_TEMPLATE = `{{input}}`; // input / time / model / lang
|
||||
@@ -462,6 +463,7 @@ export const VISION_MODEL_REGEXES = [
|
||||
/gpt-4-turbo(?!.*preview)/, // Matches "gpt-4-turbo" but not "gpt-4-turbo-preview"
|
||||
/^dall-e-3$/, // Matches exactly "dall-e-3"
|
||||
/glm-4v/,
|
||||
/vl/i,
|
||||
];
|
||||
|
||||
export const EXCLUDE_VISION_MODEL_REGEXES = [/claude-3-5-haiku-20241022/];
|
||||
@@ -814,5 +816,5 @@ export const internalAllowedWebDavEndpoints = [
|
||||
|
||||
export const DEFAULT_GA_ID = "G-89WN60ZK2E";
|
||||
|
||||
export const SAAS_CHAT_URL = "https://nextchat.dev/chat";
|
||||
export const SAAS_CHAT_UTM_URL = "https://nextchat.dev/chat?utm=github";
|
||||
export const SAAS_CHAT_URL = "https://nextchat.club";
|
||||
export const SAAS_CHAT_UTM_URL = "https://nextchat.club?utm=github";
|
||||
|
20
app/utils.ts
20
app/utils.ts
@@ -2,7 +2,11 @@ import { useEffect, useState } from "react";
|
||||
import { showToast } from "./components/ui-lib";
|
||||
import Locale from "./locales";
|
||||
import { RequestMessage } from "./client/api";
|
||||
import { ServiceProvider } from "./constant";
|
||||
import {
|
||||
REQUEST_TIMEOUT_MS,
|
||||
REQUEST_TIMEOUT_MS_FOR_THINKING,
|
||||
ServiceProvider,
|
||||
} from "./constant";
|
||||
// import { fetch as tauriFetch, ResponseType } from "@tauri-apps/api/http";
|
||||
import { fetch as tauriStreamFetch } from "./utils/stream";
|
||||
import { VISION_MODEL_REGEXES, EXCLUDE_VISION_MODEL_REGEXES } from "./constant";
|
||||
@@ -292,6 +296,20 @@ export function isDalle3(model: string) {
|
||||
return "dall-e-3" === model;
|
||||
}
|
||||
|
||||
export function getTimeoutMSByModel(model: string) {
|
||||
model = model.toLowerCase();
|
||||
if (
|
||||
model.startsWith("dall-e") ||
|
||||
model.startsWith("dalle") ||
|
||||
model.startsWith("o1") ||
|
||||
model.startsWith("o3") ||
|
||||
model.includes("deepseek-r") ||
|
||||
model.includes("-thinking")
|
||||
)
|
||||
return REQUEST_TIMEOUT_MS_FOR_THINKING;
|
||||
return REQUEST_TIMEOUT_MS;
|
||||
}
|
||||
|
||||
export function getModelSizes(model: string): ModelSize[] {
|
||||
if (isDalle3(model)) {
|
||||
return ["1024x1024", "1792x1024", "1024x1792"];
|
||||
|
@@ -400,6 +400,7 @@ export function streamWithThink(
|
||||
let responseRes: Response;
|
||||
let isInThinkingMode = false;
|
||||
let lastIsThinking = false;
|
||||
let lastIsThinkingTagged = false; //between <think> and </think> tags
|
||||
|
||||
// animate response to make it looks smooth
|
||||
function animateResponseText() {
|
||||
@@ -579,6 +580,23 @@ export function streamWithThink(
|
||||
if (!chunk?.content || chunk.content.length === 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
// deal with <think> and </think> tags start
|
||||
if (!chunk.isThinking) {
|
||||
if (chunk.content.startsWith("<think>")) {
|
||||
chunk.isThinking = true;
|
||||
chunk.content = chunk.content.slice(7).trim();
|
||||
lastIsThinkingTagged = true;
|
||||
} else if (chunk.content.endsWith("</think>")) {
|
||||
chunk.isThinking = false;
|
||||
chunk.content = chunk.content.slice(0, -8).trim();
|
||||
lastIsThinkingTagged = false;
|
||||
} else if (lastIsThinkingTagged) {
|
||||
chunk.isThinking = true;
|
||||
}
|
||||
}
|
||||
// deal with <think> and </think> tags start
|
||||
|
||||
// Check if thinking mode changed
|
||||
const isThinkingChanged = lastIsThinking !== chunk.isThinking;
|
||||
lastIsThinking = chunk.isThinking;
|
||||
|
Reference in New Issue
Block a user