feat: 可以进行多轮文献查询
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@ -5,4 +5,5 @@ NEXT_PUBLIC_OPENAI_API_KEY=sk-ffe19ebe9fa44d00884330ff1c18cf82
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NEXT_PUBLIC_PAPER_URL=/api/paper
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NEXT_PUBLIC_SEMANTIC_API_KEY=hEQvK6ARe84dzDPcMnpzX4n9jfoqztkMfaftPWnb
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NEXT_PUBLIC_PUBMED_API_KEY=057616e7ce6c722f2ae8679e38a8be9b1a09
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VERCEL_URL=https://www.paperai.life
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VERCEL_URL=https://www.paperai.life
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NODE_ENV=production
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@ -19,7 +19,7 @@ const initialState: APIState = {
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2.文献引用:只引用与主题紧密相关的论文。在引用文献时,文末应使用方括号内的数字来标注引用来源,如 [1]。。请确保每个引用在文章中都有其对应的编号,*无需在文章末尾提供参考文献列表*。*每个文献对应的序号只应该出现一次,比如说引用了第一篇文献文中就只能出现一次[1]*。
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3.忽略无关文献:对于与主题无关的论文,请不要包含在您的写作中。只关注对理解和阐述主题有实质性帮助的资料。
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4.来源明确:在文章中,清楚地指出每个引用的具体来源。引用的信息应准确无误,确保读者能够追溯到原始文献。
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5.使用中文完成回答,不超过三百字
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5.使用用户所说的语言完成回答,不超过五百字
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6.只能对给出的文献进行引用,坚决不能虚构文献。
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返回格式举例:
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在某个方面,某论文实现了以下突破...[1],在另一篇论文中,研究了...[2]`,
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@ -38,12 +38,13 @@ interface Author {
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async function getArxivPapers(
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query: string,
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maxResults = 5,
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offset = -1,
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sortBy = "submittedDate",
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sortOrder = "descending"
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) {
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const maxOffset = 30 - maxResults; // 假设总记录数为 100
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const start = getRandomOffset(maxOffset);
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const url = `https://export.arxiv.org/api/query?search_query=${query}&start=${start}&max_results=${maxResults}&sortBy=${sortBy}&sortOrder=${sortOrder}`;
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const maxOffset = 20 - maxResults; // 假设总记录数为 20
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if (offset === -1) offset = getRandomOffset(maxOffset);
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const url = `https://export.arxiv.org/api/query?search_query=${query}&start=${offset}&max_results=${maxResults}&sortBy=${sortBy}&sortOrder=${sortOrder}`;
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try {
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const response = await axios.get(url);
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@ -10,14 +10,20 @@ type PubMedID = string;
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// 定义idList为PubMedID数组
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type IDList = PubMedID[];
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async function getPubMedPapers(query: string, year: number, limit = 2) {
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async function getPubMedPapers(
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query: string,
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year: number,
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offset = -1,
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limit = 2
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) {
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try {
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const baseURL =
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"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi";
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const db = "pubmed"; // 设定搜索的数据库为PubMed
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const retMax = limit; // 检索的最大记录数
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const retStart = getRandomOffset(20 - limit); // 假设每页最多30条,根据需要随机偏移
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const url = `${baseURL}?db=${db}&term=${query}[Title/Abstract]+AND+2018:3000[Date - Publication]&retMax=${retMax}&retStart=${retStart}&api_key=${process.env.NEXT_PUBLIC_PUBMED_API_KEY}`;
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const maxOffset = 20 - limit; // 假设总记录数为 20
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if (offset === -1) offset = getRandomOffset(maxOffset);
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const url = `${baseURL}?db=${db}&term=${query}[Title/Abstract]+AND+2018:3000[Date - Publication]&retMax=${retMax}&retStart=${offset}&api_key=${process.env.NEXT_PUBLIC_PUBMED_API_KEY}`;
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const response = await axios.get(url, { responseType: "text" });
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console.log(response.data);
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// 解析XML数据
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@ -155,9 +161,14 @@ async function getPubMedPaperDetails(idList: IDList) {
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}
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// 示例:使用这些函数
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async function fetchPubMedData(query: string, year: number, limit: number) {
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async function fetchPubMedData(
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query: string,
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year: number,
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limit: number,
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offset: number
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) {
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try {
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const idList = await getPubMedPapers(query, year, limit);
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const idList = await getPubMedPapers(query, year, offset, limit);
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if (idList && idList.length > 0) {
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const paperDetails = await getPubMedPaperDetails(idList);
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console.log("fetchPubMedData", paperDetails); // 处理或显示文章详情
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@ -15,10 +15,15 @@ interface Paper {
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url: string;
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}
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async function getSemanticPapers(query: string, year: string, limit = 2) {
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async function getSemanticPapers(
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query: string,
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year: string,
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offset = -1,
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limit = 2
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) {
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try {
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const maxOffset = 20 - limit; // 假设总记录数为 20
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const offset = getRandomOffset(maxOffset);
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if (offset === -1) offset = getRandomOffset(maxOffset);
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const url = `https://api.semanticscholar.org/graph/v1/paper/search`;
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const response = await axios.get(url, {
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headers: {
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@ -101,6 +101,11 @@ const QEditor = ({ lng }) => {
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"gpt语言模型",
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"gpt-4"
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); // 默认选项
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const [generatedPaperNumber, setGeneratedPaperNumber] = useLocalStorage(
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"生成次数",
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1
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); // 初始值设为1
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//redux
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const dispatch = useAppDispatch();
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const references = useAppSelector((state) => state.auth.referencesRedux);
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@ -231,16 +236,20 @@ const QEditor = ({ lng }) => {
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const handleInputChange = (event: any) => {
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setUserInput(event.target.value);
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};
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// 处理输入generatedPaperNumber变化的函数
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const handleGeneratedPaperNumberChange = (event: any) => {
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const newValue = parseInt(event.target.value, 10);
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setGeneratedPaperNumber(newValue);
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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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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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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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@ -248,132 +257,137 @@ const QEditor = ({ lng }) => {
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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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const updatedContent = quill!.root.innerHTML;
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dispatch(setEditorContent(updatedContent));
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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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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 getTopicFromAI(userMessage, prompt, apiKey);
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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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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) offset = 0;
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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 getTopicFromAI(userMessage, prompt, apiKey);
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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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}
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console.log("topic in AI", topic);
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let rawData, dataString, newReferences;
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if (selectedSource === "arxiv") {
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rawData = await getArxivPapers(topic);
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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) => ({
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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) => {
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return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.summary}\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(topic, "2015-2023");
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// 将 rawData 转换为引用数组
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newReferences = rawData.map((entry) => ({
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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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}));
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dataString = rawData
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.map((entry) => {
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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(topic, 2020, 2);
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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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console.log("topic in AI", topic);
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let rawData, dataString, newReferences;
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if (selectedSource === "arxiv") {
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rawData = await getArxivPapers(topic);
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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.summary}\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(topic, "2015-2023", offset);
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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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}));
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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(topic, 2020, offset, 2);
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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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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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}));
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// 打印或进一步处理 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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newReferences = rawData.map((entry) => ({
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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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}));
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// 打印或进一步处理 newReferences
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console.log(newReferences);
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dataString = rawData
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.map((entry) => {
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return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
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//在对应的位置添加文献
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const nearestNumber = getNumberBeforeCursor(quill!);
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dispatch(
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addReferencesRedux({
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references: newReferences,
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position: nearestNumber,
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})
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.join("");
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}
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//在对应的位置添加文献
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const nearestNumber = getNumberBeforeCursor(quill);
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dispatch(
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addReferencesRedux({
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references: newReferences,
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position: nearestNumber,
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})
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);
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// 确保搜索到的论文不超过 3000 个字符
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const trimmedMessage =
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dataString.length > 3000 ? dataString.slice(0, 3000) : dataString;
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//slate的方法
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// const content = `需要完成的论文主题:${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:${getTextBeforeCursor(
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quill,
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500
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)},搜索到的论文内容:${trimmedMessage},需要完成的论文主题:${topic},请根据搜索到的论文内容完成用户的论文`;
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await sendMessageToOpenAI(
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content,
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quill,
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selectedModel,
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apiKey,
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upsreamUrl,
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systemPrompt
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);
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setUserInput("");
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// 重新获取更新后的内容并更新 Redux store
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const updatedContent = quill.root.innerHTML;
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dispatch(setEditorContent(updatedContent));
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if (isVip) {
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//在云端同步supabase
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const data = await submitPaper(
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supabase,
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updatedContent,
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references,
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paperNumberRedux
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);
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// 确保搜索到的论文不超过 3000 个字符
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const trimmedMessage =
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dataString.length > 3000 ? dataString.slice(0, 3000) : dataString;
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//slate的方法
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// const content = `需要完成的论文主题:${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:${getTextBeforeCursor(
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quill!,
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900
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)},搜索到的论文内容:${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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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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systemPrompt
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);
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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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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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//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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} catch (error) {
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// console.error("Error fetching data:", error);
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// 在处理错误后,再次抛出这个错误
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throw new Error(`Paper2AI出现错误: ${error}`);
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}
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} catch (error) {
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// console.error("Error fetching data:", error);
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// 在处理错误后,再次抛出这个错误
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throw new Error(`Paper2AI出现错误: ${error}`);
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}
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}
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|
@ -414,12 +428,18 @@ const QEditor = ({ lng }) => {
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<select
|
||||
value={selectedModel}
|
||||
onChange={(e) => setSelectedModel(e.target.value)}
|
||||
className=" border border-gray-300 bg-white py-2 px-3 rounded leading-tight focus:outline-none focus:bg-white focus:border-gray-500"
|
||||
className=" border border-gray-300 bg-white py-2 px-3 rounded leading-tight focus:outline-none focus:bg-white focus:border-gray-500 "
|
||||
>
|
||||
<option value="gpt-3.5-turbo">gpt-3.5-turbo</option>
|
||||
<option value="gpt-4">gpt-4</option>
|
||||
<option value="deepseek-chat">deepseek-chat</option>
|
||||
</select>
|
||||
<input
|
||||
type="number"
|
||||
value={generatedPaperNumber}
|
||||
onChange={handleGeneratedPaperNumberChange}
|
||||
className="border border-gray-300 text-gray-700 text-sm p-1 rounded w-16"
|
||||
/>
|
||||
<button
|
||||
onClick={() => formatTextInEditor(quill)} // 假设 updateIndex 是处理更新操作的函数
|
||||
className="bg-gray-300 hover:bg-gray-400 text-black font-bold py-2 px-4 rounded"
|
||||
|
|
|
@ -1,5 +1,7 @@
|
|||
import { Transforms } from "slate";
|
||||
import { Editor } from "slate";
|
||||
import Quill from "quill";
|
||||
|
||||
import { extractText } from "@/utils/others/slateutils";
|
||||
import {
|
||||
updateBracketNumbersInDeltaKeepSelection,
|
||||
|
@ -20,8 +22,8 @@ function isValidApiKey(apiKey: string) {
|
|||
|
||||
const sendMessageToOpenAI = async (
|
||||
content: string,
|
||||
editor: Editor,
|
||||
selectedModel: "gpt3.5",
|
||||
editor: Quill,
|
||||
selectedModel: string,
|
||||
apiKey: string,
|
||||
upsreamUrl: string,
|
||||
prompt?: string
|
||||
|
@ -54,7 +56,7 @@ const sendMessageToOpenAI = async (
|
|||
2.文献引用:只引用与主题紧密相关的论文。在引用文献时,文末应使用方括号内的数字来标注引用来源,如 [1]。。请确保每个引用在文章中都有其对应的编号,*无需在文章末尾提供参考文献列表*。*每个文献对应的序号只应该出现一次,比如说引用了第一篇文献文中就只能出现一次[1]*。
|
||||
3.忽略无关文献:对于与主题无关的论文,请不要包含在您的写作中。只关注对理解和阐述主题有实质性帮助的资料。
|
||||
4.来源明确:在文章中,清楚地指出每个引用的具体来源。引用的信息应准确无误,确保读者能够追溯到原始文献。
|
||||
5.使用用户所说的语言完成回答,不超过三百字
|
||||
5.使用用户所说的语言完成回答,不超过五百字
|
||||
6.只能对给出的文献进行引用,坚决不能虚构文献。
|
||||
返回格式举例:
|
||||
在某个方面,某论文实现了以下突破...[1],在另一篇论文中,研究了...[2]`,
|
||||
|
|
|
@ -4,31 +4,33 @@
|
|||
|
||||
import * as Sentry from "@sentry/nextjs";
|
||||
|
||||
Sentry.init({
|
||||
dsn: "https://523c4056ba48d012c62a377dfc49f647@o4506728662564864.ingest.sentry.io/4506728672264192",
|
||||
if (process.env.NODE_ENV === "production") {
|
||||
Sentry.init({
|
||||
dsn: "https://523c4056ba48d012c62a377dfc49f647@o4506728662564864.ingest.sentry.io/4506728672264192",
|
||||
|
||||
// Adjust this value in production, or use tracesSampler for greater control
|
||||
tracesSampleRate: 1,
|
||||
// Adjust this value in production, or use tracesSampler for greater control
|
||||
tracesSampleRate: 1,
|
||||
|
||||
// Setting this option to true will print useful information to the console while you're setting up Sentry.
|
||||
debug: false,
|
||||
// Setting this option to true will print useful information to the console while you're setting up Sentry.
|
||||
debug: false,
|
||||
|
||||
replaysOnErrorSampleRate: 1.0,
|
||||
replaysOnErrorSampleRate: 1.0,
|
||||
|
||||
// This sets the sample rate to be 10%. You may want this to be 100% while
|
||||
// in development and sample at a lower rate in production
|
||||
replaysSessionSampleRate: 0.1,
|
||||
// This sets the sample rate to be 10%. You may want this to be 100% while
|
||||
// in development and sample at a lower rate in production
|
||||
replaysSessionSampleRate: 0.1,
|
||||
|
||||
// You can remove this option if you're not planning to use the Sentry Session Replay feature:
|
||||
integrations: [
|
||||
Sentry.replayIntegration({
|
||||
// Additional Replay configuration goes in here, for example:
|
||||
maskAllText: true,
|
||||
blockAllMedia: true,
|
||||
}),
|
||||
Sentry.feedbackIntegration({
|
||||
// Additional SDK configuration goes in here, for example:
|
||||
colorScheme: "light",
|
||||
}),
|
||||
],
|
||||
});
|
||||
// You can remove this option if you're not planning to use the Sentry Session Replay feature:
|
||||
integrations: [
|
||||
Sentry.replayIntegration({
|
||||
// Additional Replay configuration goes in here, for example:
|
||||
maskAllText: true,
|
||||
blockAllMedia: true,
|
||||
}),
|
||||
Sentry.feedbackIntegration({
|
||||
// Additional SDK configuration goes in here, for example:
|
||||
colorScheme: "light",
|
||||
}),
|
||||
],
|
||||
});
|
||||
}
|
||||
|
|
|
@ -4,13 +4,14 @@
|
|||
// https://docs.sentry.io/platforms/javascript/guides/nextjs/
|
||||
|
||||
import * as Sentry from "@sentry/nextjs";
|
||||
if (process.env.NODE_ENV === "production") {
|
||||
Sentry.init({
|
||||
dsn: "https://523c4056ba48d012c62a377dfc49f647@o4506728662564864.ingest.sentry.io/4506728672264192",
|
||||
|
||||
Sentry.init({
|
||||
dsn: "https://523c4056ba48d012c62a377dfc49f647@o4506728662564864.ingest.sentry.io/4506728672264192",
|
||||
// Adjust this value in production, or use tracesSampler for greater control
|
||||
tracesSampleRate: 1,
|
||||
|
||||
// Adjust this value in production, or use tracesSampler for greater control
|
||||
tracesSampleRate: 1,
|
||||
|
||||
// Setting this option to true will print useful information to the console while you're setting up Sentry.
|
||||
debug: false,
|
||||
});
|
||||
// Setting this option to true will print useful information to the console while you're setting up Sentry.
|
||||
debug: false,
|
||||
});
|
||||
}
|
||||
|
|
|
@ -3,13 +3,14 @@
|
|||
// https://docs.sentry.io/platforms/javascript/guides/nextjs/
|
||||
|
||||
import * as Sentry from "@sentry/nextjs";
|
||||
if (process.env.NODE_ENV === "production") {
|
||||
Sentry.init({
|
||||
dsn: "https://523c4056ba48d012c62a377dfc49f647@o4506728662564864.ingest.sentry.io/4506728672264192",
|
||||
|
||||
Sentry.init({
|
||||
dsn: "https://523c4056ba48d012c62a377dfc49f647@o4506728662564864.ingest.sentry.io/4506728672264192",
|
||||
// Adjust this value in production, or use tracesSampler for greater control
|
||||
tracesSampleRate: 1,
|
||||
|
||||
// Adjust this value in production, or use tracesSampler for greater control
|
||||
tracesSampleRate: 1,
|
||||
|
||||
// Setting this option to true will print useful information to the console while you're setting up Sentry.
|
||||
debug: false,
|
||||
});
|
||||
// Setting this option to true will print useful information to the console while you're setting up Sentry.
|
||||
debug: false,
|
||||
});
|
||||
}
|
||||
|
|
Loading…
Reference in New Issue
Block a user