feat: 可以手动停止AI的输出(左下角按钮)
This commit is contained in:
liuweiqing
parent
1eb3c596f3
commit
a72329d4a2
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@ -9,6 +9,7 @@
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"生成轮数": "Generation Rounds",
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"时间范围": "Range of literature release dates, from this time to this year",
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"更新文中的上标，使得数字顺序排列": "Update the superscript in the text to make the numbers in order",
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"停止生成": "Stop Generation",
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"+ Add Paper": "+ Add Paper",
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"Buy VIP TO UNLOCK Cloud Sync and Edit Mutiple Papers Simultaneously": "Buy VIP TO UNLOCK Cloud Sync and Edit Mutiple Papers Simultaneously",
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"Paper Management": "Paper Management",
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@ -9,6 +9,7 @@
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"生成轮数": "生成轮数",
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"时间范围": "文献发布日期范围，从这个时间到今年",
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"更新文中的上标，使得数字顺序排列": "更新文中的上标，使得数字顺序排列",
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"停止生成": "停止生成",
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"+ Add Paper": "+ 添加新论文（会直接替换编辑器里的内容）",
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"Buy VIP TO UNLOCK Cloud Sync and Edit Mutiple Papers Simultaneously": "购买VIP解锁云同步和同时编辑多篇论文",
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"Paper Management": "论文管理",
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@ -116,11 +116,12 @@ const QEditor = ({ lng }) => {
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//选择时间范围
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const [timeRange, setTimeRange] = useLocalStorage("时间范围", "2019");
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const [generateNumber, setGenerateNumber] = useState(0); //当前任务的进行数
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const [openProgressBar, setOpenProgressBar] = useState(false);
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const [openProgressBar, setOpenProgressBar] = useState(false); //设置进度条是否打开
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const [showAnnouncement, setShowAnnouncement] = useLocalStorage(
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"显示公告",
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true
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); // 是否显示公告
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const [controller, setController] = useState<AbortController | null>(null); // 创建 AbortController 的状态
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//redux
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const dispatch = useAppDispatch();
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@ -287,240 +288,280 @@ const QEditor = ({ lng }) => {
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};
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// 处理AI写作
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const handleAIWrite = async () => {
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quill!.setSelection(cursorPosition!, 0); // 将光标移动到原来的位置
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try {
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setOpenProgressBar(true); //开启进度条
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// 创建一个新的 AbortController 实例
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const newController = new AbortController();
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setController(newController);
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quill!.setSelection(cursorPosition!, 0); // 将光标移动到原来的位置
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const prompt = "请帮助用户完成论文写作，使用用户所说的语言完成";
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await sendMessageToOpenAI(
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userInput,
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quill!,
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selectedModel!,
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apiKey,
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upsreamUrl,
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prompt,
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cursorPosition!
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);
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// 清空input内容
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setUserInput("");
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// 重新获取更新后的内容并更新 Redux store
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const updatedContent = quill!.root.innerHTML;
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dispatch(setEditorContent(updatedContent));
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toast.success(`AI写作完成`, {
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position: "top-center",
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autoClose: 2000,
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pauseOnHover: true,
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});
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const prompt = "请帮助用户完成论文写作，使用用户所说的语言完成";
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await sendMessageToOpenAI(
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userInput,
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quill!,
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selectedModel!,
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apiKey,
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upsreamUrl,
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prompt,
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cursorPosition!,
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true,
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newController.signal // 传递 AbortSignal
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);
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// 清空input内容
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setUserInput("");
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// 重新获取更新后的内容并更新 Redux store
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const updatedContent = quill!.root.innerHTML;
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dispatch(setEditorContent(updatedContent));
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toast.success(`AI写作完成`, {
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position: "top-center",
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autoClose: 2000,
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pauseOnHover: true,
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});
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} catch (error) {
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toast.error(`AI写作出现错误: ${error}`, {
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position: "top-center",
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autoClose: 3000,
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pauseOnHover: true,
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});
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} finally {
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setOpenProgressBar(false); //关闭进度条
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}
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};
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// 处理paper2AI
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async function paper2AI(topic: string) {
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quill!.setSelection(cursorPosition!, 0); // 将光标移动到原来的位置
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let offset = -1;
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if (generatedPaperNumber != 1) offset = 0; //如果生成的数量不为1，则从0开始
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setOpenProgressBar(true); //开启进度条
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//如果说要评估主题是否匹配的话,就要多获取一些文献
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let limit = 2;
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if (isEvaluateTopicMatch) {
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limit = 4;
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}
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try {
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// 创建一个新的 AbortController 实例
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const newController = new AbortController();
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setController(newController);
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quill!.setSelection(cursorPosition!, 0); // 将光标移动到原来的位置
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let offset = -1;
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if (generatedPaperNumber != 1) offset = 0; //如果生成的数量不为1，则从0开始
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setOpenProgressBar(true); //开启进度条
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//如果说要评估主题是否匹配的话,就要多获取一些文献
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let limit = 2;
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if (isEvaluateTopicMatch) {
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limit = 4;
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}
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for (let i = 0; i < generatedPaperNumber!; i++) {
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try {
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if (!topic) {
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//使用ai提取当前要请求的论文主题
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const prompt =
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"As a topic extraction assistant, you can help me extract the current discussion of the paper topic, I will enter the content of the paper, you extract the paper topic , no more than two, Hyphenated query terms yield no matches (replace it with space to find matches) return format is: topic1 topic2";
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const userMessage = getTextBeforeCursor(quill!, 2000);
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topic = await sendMessageToOpenAI(
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userMessage,
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null,
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for (let i = 0; i < generatedPaperNumber!; i++) {
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try {
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if (!topic) {
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//使用ai提取当前要请求的论文主题
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const prompt =
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"As a topic extraction assistant, you can help me extract the current discussion of the paper topic, I will enter the content of the paper, you extract the paper topic , no more than two, Hyphenated query terms yield no matches (replace it with space to find matches) return format is: topic1 topic2";
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const userMessage = getTextBeforeCursor(quill!, 2000);
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topic = await sendMessageToOpenAI(
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userMessage,
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null,
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selectedModel!,
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apiKey,
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upsreamUrl,
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prompt,
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null,
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false,
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newController.signal // 传递 AbortSignal
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);
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console.log("topic in AI before removeSpecialCharacters", topic);
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topic = removeSpecialCharacters(topic);
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topic = topic.split(" ").slice(0, 2).join(" ");
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//如果超过十个字符就截断
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if (topic.length > 10) {
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topic = topic.slice(0, 10);
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}
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}
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console.log("topic in AI", topic);
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console.log("offset in paper2AI", offset);
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console.log("limit in paper2AI", limit);
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let rawData, dataString, newReferences;
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if (selectedSource === "arxiv") {
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rawData = await getArxivPapers(topic, limit, offset);
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//判断返回的文献是否跟用户输入的主题相关
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if (isEvaluateTopicMatch) {
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const { relevantPapers, nonRelevantPapers } =
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await evaluateTopicMatch(
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rawData,
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apiKey,
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upsreamUrl,
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selectedModel!,
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topic,
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newController.signal
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);
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rawData = relevantPapers;
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}
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console.log("arxiv rawdata:", rawData);
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// 将 rawData 转换为引用数组
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newReferences = rawData.map((entry: any) => ({
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url: entry.id,
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title: entry.title,
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year: entry.published,
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author: entry.authors?.slice(0, 3).join(", "),
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}));
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dataString = rawData
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.map((entry: any) => {
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return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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})
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.join("");
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} else if (selectedSource === "semanticScholar") {
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rawData = await getSemanticPapers(
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topic,
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`${timeRange}-2024`,
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offset,
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limit
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);
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//判断返回的文献是否跟用户输入的主题相关
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if (isEvaluateTopicMatch) {
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const { relevantPapers, nonRelevantPapers } =
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await evaluateTopicMatch(
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rawData,
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apiKey,
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upsreamUrl,
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selectedModel!,
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topic,
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newController.signal
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);
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rawData = relevantPapers;
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}
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// 将 rawData 转换为引用数组
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newReferences = rawData.map((entry: any) => ({
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url: entry.url,
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title: entry.title,
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year: entry.year,
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author: entry.authors?.slice(0, 3).join(", "),
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venue: entry.venue,
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journal: formatJournalReference(entry),
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doi: entry.externalIds.DOI,
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}));
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dataString = rawData
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.map((entry: any) => {
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return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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})
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.join("");
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} else if (selectedSource === "pubmed") {
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rawData = await fetchPubMedData(
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topic,
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Number(timeRange)!,
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offset,
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limit
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);
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if (!rawData) {
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throw new Error("未搜索到文献 from PubMed.");
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}
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//判断返回的文献是否跟用户输入的主题相关
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if (isEvaluateTopicMatch) {
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const { relevantPapers, nonRelevantPapers } =
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await evaluateTopicMatch(
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rawData,
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apiKey,
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upsreamUrl,
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selectedModel!,
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topic,
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newController.signal
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);
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rawData = relevantPapers;
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}
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newReferences = rawData.map((entry: any) => ({
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id: entry.id, // 文章的 PubMed ID
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title: entry.title, // 文章的标题
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abstract: entry.abstract, // 文章的摘要
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author: entry.authors?.slice(0, 3).join(", "), // 文章的作者列表，假设为字符串数组
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year: entry.year, // 文章的发表日期
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journal: entry.journal, // 文章的发表杂志
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url: entry.url, // 文章的 URL
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source: "PubMed", // 指示这些引用来自 PubMed
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doi: entry.doi, // 文章的 DOI
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}));
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// 打印 newReferences
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console.log(newReferences);
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dataString = rawData
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.map((entry: any) => {
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return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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})
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.join("");
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}
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// 确保搜索到的论文不超过 3000 个字符
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const trimmedMessage =
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dataString.length > 3000 ? dataString.slice(0, 3000) : dataString;
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//slate的方法
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// const content = `需要完成的论文主题：${topic}, 搜索到的论文内容:${trimmedMessage},之前已经完成的内容上下文：${extractText(
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// editorValue
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// )}`;
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const content = `之前用户已经完成的内容上下文：${getTextBeforeCursor(
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quill!,
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800
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)},搜索到的论文内容:${trimmedMessage},需要完成的论文主题：${topic},请根据搜索到的论文内容完成用户的论文`;
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showExpandableToast(`搜索论文完成，搜索到的论文:${trimmedMessage}`);
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await sendMessageToOpenAI(
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content,
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quill!,
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selectedModel!,
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apiKey,
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upsreamUrl,
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prompt,
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null,
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false
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systemPrompt,
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cursorPosition!,
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true,
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newController.signal // 传递 AbortSignal
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);
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console.log("topic in AI before removeSpecialCharacters", topic);
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topic = removeSpecialCharacters(topic);
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topic = topic.split(" ").slice(0, 2).join(" ");
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//如果超过十个字符就截断
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if (topic.length > 10) {
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topic = topic.slice(0, 10);
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}
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}
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console.log("topic in AI", topic);
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console.log("offset in paper2AI", offset);
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console.log("limit in paper2AI", limit);
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let rawData, dataString, newReferences;
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if (selectedSource === "arxiv") {
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rawData = await getArxivPapers(topic, limit, offset);
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//判断返回的文献是否跟用户输入的主题相关
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if (isEvaluateTopicMatch) {
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const { relevantPapers, nonRelevantPapers } =
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await evaluateTopicMatch(
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rawData,
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apiKey,
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upsreamUrl,
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selectedModel!,
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topic
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);
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rawData = relevantPapers;
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}
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console.log("arxiv rawdata:", rawData);
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// 将 rawData 转换为引用数组
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newReferences = rawData.map((entry: any) => ({
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url: entry.id,
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title: entry.title,
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year: entry.published,
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author: entry.authors?.slice(0, 3).join(", "),
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}));
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dataString = rawData
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.map((entry: any) => {
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return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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setUserInput("");
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// 重新获取更新后的内容并更新 Redux store
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const updatedContent = quill!.root.innerHTML;
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dispatch(setEditorContent(updatedContent));
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//在对应的位置添加文献
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const nearestNumber = getNumberBeforeCursor(quill!);
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dispatch(
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addReferencesRedux({
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references: newReferences,
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position: nearestNumber,
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})
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.join("");
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} else if (selectedSource === "semanticScholar") {
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rawData = await getSemanticPapers(
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topic,
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`${timeRange}-2024`,
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offset,
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limit
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);
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//判断返回的文献是否跟用户输入的主题相关
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if (isEvaluateTopicMatch) {
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const { relevantPapers, nonRelevantPapers } =
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await evaluateTopicMatch(
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rawData,
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apiKey,
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upsreamUrl,
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selectedModel!,
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topic
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);
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rawData = relevantPapers;
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if (isVip) {
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//在云端同步supabase
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const data = await submitPaper(
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supabase,
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updatedContent,
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references,
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paperNumberRedux
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);
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}
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// 将 rawData 转换为引用数组
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newReferences = rawData.map((entry: any) => ({
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url: entry.url,
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title: entry.title,
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year: entry.year,
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author: entry.authors?.slice(0, 3).join(", "),
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venue: entry.venue,
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journal: formatJournalReference(entry),
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doi: entry.externalIds.DOI,
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}));
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dataString = rawData
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.map((entry: any) => {
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return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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})
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.join("");
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} else if (selectedSource === "pubmed") {
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rawData = await fetchPubMedData(
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topic,
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Number(timeRange)!,
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offset,
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limit
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);
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if (!rawData) {
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throw new Error("未搜索到文献 from PubMed.");
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}
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//判断返回的文献是否跟用户输入的主题相关
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if (isEvaluateTopicMatch) {
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const { relevantPapers, nonRelevantPapers } =
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await evaluateTopicMatch(
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rawData,
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apiKey,
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upsreamUrl,
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selectedModel!,
|
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topic
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);
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rawData = relevantPapers;
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}
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newReferences = rawData.map((entry: any) => ({
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id: entry.id, // 文章的 PubMed ID
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title: entry.title, // 文章的标题
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abstract: entry.abstract, // 文章的摘要
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author: entry.authors?.slice(0, 3).join(", "), // 文章的作者列表，假设为字符串数组
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year: entry.year, // 文章的发表日期
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journal: entry.journal, // 文章的发表杂志
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url: entry.url, // 文章的 URL
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source: "PubMed", // 指示这些引用来自 PubMed
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doi: entry.doi, // 文章的 DOI
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}));
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// 打印 newReferences
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console.log(newReferences);
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dataString = rawData
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.map((entry: any) => {
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return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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})
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.join("");
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//修改offset使得按照接下来的顺序进行获取文献
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offset += 2;
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setGenerateNumber(i + 1);
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toast.success(`AI写作完成`, {
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position: "top-center",
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autoClose: 2000,
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pauseOnHover: true,
|
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});
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} catch (error) {
|
||||
console.error("Paper2AI出现错误", error);
|
||||
// 在处理错误后，再次抛出这个错误
|
||||
// throw new Error(`Paper2AI出现错误: ${error}`);
|
||||
toast.error(`Paper2AI出现错误: ${error}`, {
|
||||
position: "top-center",
|
||||
autoClose: 3000,
|
||||
pauseOnHover: true,
|
||||
});
|
||||
}
|
||||
|
||||
// 确保搜索到的论文不超过 3000 个字符
|
||||
const trimmedMessage =
|
||||
dataString.length > 3000 ? dataString.slice(0, 3000) : dataString;
|
||||
//slate的方法
|
||||
// const content = `需要完成的论文主题：${topic}, 搜索到的论文内容:${trimmedMessage},之前已经完成的内容上下文：${extractText(
|
||||
// editorValue
|
||||
// )}`;
|
||||
const content = `之前用户已经完成的内容上下文：${getTextBeforeCursor(
|
||||
quill!,
|
||||
800
|
||||
)},搜索到的论文内容:${trimmedMessage},需要完成的论文主题：${topic},请根据搜索到的论文内容完成用户的论文`;
|
||||
showExpandableToast(`搜索论文完成，搜索到的论文:${trimmedMessage}`);
|
||||
await sendMessageToOpenAI(
|
||||
content,
|
||||
quill!,
|
||||
selectedModel!,
|
||||
apiKey,
|
||||
upsreamUrl,
|
||||
systemPrompt,
|
||||
cursorPosition!
|
||||
);
|
||||
setUserInput("");
|
||||
// 重新获取更新后的内容并更新 Redux store
|
||||
const updatedContent = quill!.root.innerHTML;
|
||||
dispatch(setEditorContent(updatedContent));
|
||||
//在对应的位置添加文献
|
||||
const nearestNumber = getNumberBeforeCursor(quill!);
|
||||
dispatch(
|
||||
addReferencesRedux({
|
||||
references: newReferences,
|
||||
position: nearestNumber,
|
||||
})
|
||||
);
|
||||
if (isVip) {
|
||||
//在云端同步supabase
|
||||
const data = await submitPaper(
|
||||
supabase,
|
||||
updatedContent,
|
||||
references,
|
||||
paperNumberRedux
|
||||
);
|
||||
}
|
||||
//修改offset使得按照接下来的顺序进行获取文献
|
||||
offset += 2;
|
||||
setGenerateNumber(i + 1);
|
||||
toast.success(`AI写作完成`, {
|
||||
position: "top-center",
|
||||
autoClose: 2000,
|
||||
pauseOnHover: true,
|
||||
});
|
||||
} catch (error) {
|
||||
console.error("Paper2AI出现错误", error);
|
||||
// 在处理错误后，再次抛出这个错误
|
||||
// throw new Error(`Paper2AI出现错误: ${error}`);
|
||||
toast.error(`Paper2AI出现错误: ${error}`, {
|
||||
position: "top-center",
|
||||
autoClose: 3000,
|
||||
pauseOnHover: true,
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
toast.error(`Paper2AI出现错误: ${error}`, {
|
||||
position: "top-center",
|
||||
autoClose: 3000,
|
||||
pauseOnHover: true,
|
||||
});
|
||||
} finally {
|
||||
setOpenProgressBar(false);
|
||||
setGenerateNumber(0); //总的已经生成的数量
|
||||
}
|
||||
setOpenProgressBar(false);
|
||||
setGenerateNumber(0); //总的已经生成的数量
|
||||
}
|
||||
|
||||
const handleStop = () => {
|
||||
if (controller) {
|
||||
controller.abort(); // 取消请求
|
||||
setController(null); // 重置 controller 状态
|
||||
}
|
||||
};
|
||||
return (
|
||||
<div className="flex flex-col ">
|
||||
<div id="Qtoolbar" className="space-y-2 flex justify-between">
|
||||
|
|
@ -601,6 +642,16 @@ const QEditor = ({ lng }) => {
|
|||
<ReferenceList editor={quill} lng={lng} />
|
||||
<ExportDocx editor={quill} />
|
||||
</div>
|
||||
{/* 停止生成的按钮只有在开始对话之后才会出现 */}
|
||||
{openProgressBar ? (
|
||||
<button
|
||||
onClick={handleStop}
|
||||
className="fixed bottom-4 left-4 bg-red-500 hover:bg-red-600 focus:outline-none focus:ring-2 focus:ring-red-500 focus:ring-opacity-50 active:bg-red-700 text-white font-bold py-2 px-4 rounded transition ease-in-out duration-150 shadow-lg hover:shadow-xl"
|
||||
>
|
||||
{t("停止生成")}
|
||||
</button>
|
||||
) : null}
|
||||
|
||||
<ToastContainer />
|
||||
</div>
|
||||
);
|
||||
|
|
|
|||
|
|
@ -8,6 +8,7 @@ import {
|
|||
convertToSuperscript,
|
||||
deleteSameBracketNumber,
|
||||
} from "@/utils/others/quillutils";
|
||||
import { faSignal } from "@fortawesome/free-solid-svg-icons";
|
||||
//redux不能在普通函数使用
|
||||
|
||||
interface ChatData {
|
||||
|
|
@ -29,7 +30,8 @@ const sendMessageToOpenAI = async (
|
|||
upsreamUrl: string,
|
||||
prompt: string,
|
||||
cursorPosition: number | null,
|
||||
useEditorFlag = true // 新增的标志，用于决定操作
|
||||
useEditorFlag = true, // 新增的标志，用于决定操作
|
||||
signal: AbortSignal
|
||||
) => {
|
||||
//识别应该使用的模型
|
||||
let model = selectedModel;
|
||||
|
|
@ -37,6 +39,7 @@ const sendMessageToOpenAI = async (
|
|||
// 设置API请求参数
|
||||
const requestOptions = {
|
||||
method: "POST",
|
||||
signal: signal,
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
// "Upstream-Url": upsreamUrl,
|
||||
|
|
@ -106,7 +109,12 @@ const sendMessageToOpenAI = async (
|
|||
const content = data.choices[0].message.content;
|
||||
return content; // 或根据需要处理并返回数据
|
||||
}
|
||||
} catch (error) {
|
||||
} catch (error: any) {
|
||||
if (error.name === "AbortError") {
|
||||
console.log("Fetch operation was aborted");
|
||||
//这里不用产生报错因为是手动停止
|
||||
return;
|
||||
}
|
||||
console.error("Error:", error);
|
||||
// 如果有响应，返回响应的原始内容
|
||||
if (response) {
|
||||
|
|
|
|||
|
|
@ -74,7 +74,8 @@ export async function evaluateTopicMatch(
|
|||
apiKey: string,
|
||||
upsreamUrl: string,
|
||||
selectedModel: string,
|
||||
topic: string
|
||||
topic: string,
|
||||
signal: AbortSignal
|
||||
): Promise<{ relevantPapers: string[]; nonRelevantPapers: string[] }> {
|
||||
const prompt =
|
||||
"请判断文献是否跟用户输入的主题相关,只需要返回true或false的数组";
|
||||
|
|
@ -117,7 +118,8 @@ export async function evaluateTopicMatch(
|
|||
upsreamUrl,
|
||||
prompt,
|
||||
null,
|
||||
false
|
||||
false,
|
||||
signal
|
||||
);
|
||||
console.log("isrelevantResults in 相关性检查", isRelevantResults);
|
||||
// 处理每篇文献的相关性结果
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user