diff --git a/.env.production b/.env.production
index 771e8883..9a7a8b38 100644
--- a/.env.production
+++ b/.env.production
@@ -5,4 +5,5 @@ NEXT_PUBLIC_OPENAI_API_KEY=sk-ffe19ebe9fa44d00884330ff1c18cf82
NEXT_PUBLIC_PAPER_URL=/api/paper
NEXT_PUBLIC_SEMANTIC_API_KEY=hEQvK6ARe84dzDPcMnpzX4n9jfoqztkMfaftPWnb
NEXT_PUBLIC_PUBMED_API_KEY=057616e7ce6c722f2ae8679e38a8be9b1a09
-VERCEL_URL=https://www.paperai.life
\ No newline at end of file
+VERCEL_URL=https://www.paperai.life
+NODE_ENV=production
diff --git a/app/store/slices/authSlice.ts b/app/store/slices/authSlice.ts
index 166fbdf9..7ac3eb6a 100644
--- a/app/store/slices/authSlice.ts
+++ b/app/store/slices/authSlice.ts
@@ -19,7 +19,7 @@ const initialState: APIState = {
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.使用中文完成回答,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]`,
diff --git a/components/GetArxiv.tsx b/components/GetArxiv.tsx
index 458e80ec..01f8c393 100644
--- a/components/GetArxiv.tsx
+++ b/components/GetArxiv.tsx
@@ -38,12 +38,13 @@ interface Author {
async function getArxivPapers(
query: string,
maxResults = 5,
+ offset = -1,
sortBy = "submittedDate",
sortOrder = "descending"
) {
- const maxOffset = 30 - maxResults; // 假设总记录数为 100
- const start = getRandomOffset(maxOffset);
- const url = `https://export.arxiv.org/api/query?search_query=${query}&start=${start}&max_results=${maxResults}&sortBy=${sortBy}&sortOrder=${sortOrder}`;
+ const maxOffset = 20 - maxResults; // 假设总记录数为 20
+ if (offset === -1) offset = getRandomOffset(maxOffset);
+ const url = `https://export.arxiv.org/api/query?search_query=${query}&start=${offset}&max_results=${maxResults}&sortBy=${sortBy}&sortOrder=${sortOrder}`;
try {
const response = await axios.get(url);
diff --git a/components/GetPubMed .tsx b/components/GetPubMed .tsx
index 9edafb2a..4349e821 100644
--- a/components/GetPubMed .tsx
+++ b/components/GetPubMed .tsx
@@ -10,14 +10,20 @@ type PubMedID = string;
// 定义idList为PubMedID数组
type IDList = PubMedID[];
-async function getPubMedPapers(query: string, year: number, limit = 2) {
+async function getPubMedPapers(
+ query: string,
+ year: number,
+ offset = -1,
+ limit = 2
+) {
try {
const baseURL =
"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi";
const db = "pubmed"; // 设定搜索的数据库为PubMed
const retMax = limit; // 检索的最大记录数
- const retStart = getRandomOffset(20 - limit); // 假设每页最多30条，根据需要随机偏移
- 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}`;
+ const maxOffset = 20 - limit; // 假设总记录数为 20
+ if (offset === -1) offset = getRandomOffset(maxOffset);
+ 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}`;
const response = await axios.get(url, { responseType: "text" });
console.log(response.data);
// 解析XML数据
@@ -155,9 +161,14 @@ async function getPubMedPaperDetails(idList: IDList) {
}
// 示例：使用这些函数
-async function fetchPubMedData(query: string, year: number, limit: number) {
+async function fetchPubMedData(
+ query: string,
+ year: number,
+ limit: number,
+ offset: number
+) {
try {
- const idList = await getPubMedPapers(query, year, limit);
+ const idList = await getPubMedPapers(query, year, offset, limit);
if (idList && idList.length > 0) {
const paperDetails = await getPubMedPaperDetails(idList);
console.log("fetchPubMedData", paperDetails); // 处理或显示文章详情
diff --git a/components/GetSemantic.tsx b/components/GetSemantic.tsx
index 5392f2f0..80e8cc6b 100644
--- a/components/GetSemantic.tsx
+++ b/components/GetSemantic.tsx
@@ -15,10 +15,15 @@ interface Paper {
url: string;
}
-async function getSemanticPapers(query: string, year: string, limit = 2) {
+async function getSemanticPapers(
+ query: string,
+ year: string,
+ offset = -1,
+ limit = 2
+) {
try {
const maxOffset = 20 - limit; // 假设总记录数为 20
- const offset = getRandomOffset(maxOffset);
+ if (offset === -1) offset = getRandomOffset(maxOffset);
const url = `https://api.semanticscholar.org/graph/v1/paper/search`;
const response = await axios.get(url, {
headers: {
diff --git a/components/QuillEditor.tsx b/components/QuillEditor.tsx
index 12d55e4c..33f6967a 100644
--- a/components/QuillEditor.tsx
+++ b/components/QuillEditor.tsx
@@ -101,6 +101,11 @@ const QEditor = ({ lng }) => {
"gpt语言模型",
"gpt-4"
); // 默认选项
+ const [generatedPaperNumber, setGeneratedPaperNumber] = useLocalStorage(
+ "生成次数",
+ 1
+ ); // 初始值设为1
+
//redux
const dispatch = useAppDispatch();
const references = useAppSelector((state) => state.auth.referencesRedux);
@@ -231,16 +236,20 @@ const QEditor = ({ lng }) => {
const handleInputChange = (event: any) => {
setUserInput(event.target.value);
};
-
+ // 处理输入generatedPaperNumber变化的函数
+ const handleGeneratedPaperNumberChange = (event: any) => {
+ const newValue = parseInt(event.target.value, 10);
+ setGeneratedPaperNumber(newValue);
+ };
// 处理AI写作
const handleAIWrite = async () => {
- quill.setSelection(cursorPosition, 0); // 将光标移动到原来的位置
+ quill!.setSelection(cursorPosition!, 0); // 将光标移动到原来的位置
const prompt = "请帮助用户完成论文写作，使用用户所说的语言完成";
await sendMessageToOpenAI(
userInput,
- quill,
- selectedModel,
+ quill!,
+ selectedModel!,
apiKey,
upsreamUrl,
prompt
@@ -248,132 +257,137 @@ const QEditor = ({ lng }) => {
// 清空input内容
setUserInput("");
// 重新获取更新后的内容并更新 Redux store
- const updatedContent = quill.root.innerHTML;
+ const updatedContent = quill!.root.innerHTML;
dispatch(setEditorContent(updatedContent));
};
// 处理paper2AI
async function paper2AI(topic: string) {
- quill.setSelection(cursorPosition, 0); // 将光标移动到原来的位置
-
- try {
- if (!topic) {
- //使用ai提取当前要请求的论文主题
- const prompt =
- "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";
- const userMessage = getTextBeforeCursor(quill, 2000);
- topic = await getTopicFromAI(userMessage, prompt, apiKey);
- console.log("topic in AI before removeSpecialCharacters", topic);
- topic = removeSpecialCharacters(topic);
- topic = topic.split(" ").slice(0, 2).join(" ");
- //如果超过十个字符就截断
- if (topic.length > 10) {
- topic = topic.slice(0, 10);
- }
- }
- console.log("topic in AI", topic);
- let rawData, dataString, newReferences;
- if (selectedSource === "arxiv") {
- rawData = await getArxivPapers(topic);
- console.log("arxiv rawdata:", rawData);
- // 将 rawData 转换为引用数组
- newReferences = rawData.map((entry) => ({
- url: entry.id,
- title: entry.title,
- year: entry.published,
- author: entry.authors?.slice(0, 3).join(", "),
- }));
- dataString = rawData
- .map((entry) => {
- return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.summary}\n\n`;
- })
- .join("");
- } else if (selectedSource === "semanticScholar") {
- rawData = await getSemanticPapers(topic, "2015-2023");
- // 将 rawData 转换为引用数组
- newReferences = rawData.map((entry) => ({
- url: entry.url,
- title: entry.title,
- year: entry.year,
- author: entry.authors?.slice(0, 3).join(", "),
- venue: entry.venue,
- journal: formatJournalReference(entry),
- }));
- dataString = rawData
- .map((entry) => {
- return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
- })
- .join("");
- } else if (selectedSource === "pubmed") {
- rawData = await fetchPubMedData(topic, 2020, 2);
- if (!rawData) {
- throw new Error("未搜索到文献 from PubMed.");
+ quill!.setSelection(cursorPosition!, 0); // 将光标移动到原来的位置
+ let offset = -1;
+ if (generatedPaperNumber) offset = 0;
+ for (let i = 0; i < generatedPaperNumber!; i++) {
+ try {
+ if (!topic) {
+ //使用ai提取当前要请求的论文主题
+ const prompt =
+ "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";
+ const userMessage = getTextBeforeCursor(quill!, 2000);
+ topic = await getTopicFromAI(userMessage, prompt, apiKey);
+ console.log("topic in AI before removeSpecialCharacters", topic);
+ topic = removeSpecialCharacters(topic);
+ topic = topic.split(" ").slice(0, 2).join(" ");
+ //如果超过十个字符就截断
+ if (topic.length > 10) {
+ topic = topic.slice(0, 10);
+ }
}
- newReferences = rawData.map((entry) => ({
- id: entry.id, // 文章的 PubMed ID
- title: entry.title, // 文章的标题
- abstract: entry.abstract, // 文章的摘要
- author: entry.authors?.slice(0, 3).join(", "), // 文章的作者列表，假设为字符串数组
- year: entry.year, // 文章的发表日期
- journal: entry.journal, // 文章的发表杂志
- url: entry.url, // 文章的 URL
- source: "PubMed", // 指示这些引用来自 PubMed
- }));
+ console.log("topic in AI", topic);
+ let rawData, dataString, newReferences;
+ if (selectedSource === "arxiv") {
+ rawData = await getArxivPapers(topic);
+ console.log("arxiv rawdata:", rawData);
+ // 将 rawData 转换为引用数组
+ newReferences = rawData.map((entry: any) => ({
+ url: entry.id,
+ title: entry.title,
+ year: entry.published,
+ author: entry.authors?.slice(0, 3).join(", "),
+ }));
+ dataString = rawData
+ .map((entry: any) => {
+ return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.summary}\n\n`;
+ })
+ .join("");
+ } else if (selectedSource === "semanticScholar") {
+ rawData = await getSemanticPapers(topic, "2015-2023", offset);
+ // 将 rawData 转换为引用数组
+ newReferences = rawData.map((entry: any) => ({
+ url: entry.url,
+ title: entry.title,
+ year: entry.year,
+ author: entry.authors?.slice(0, 3).join(", "),
+ venue: entry.venue,
+ journal: formatJournalReference(entry),
+ }));
+ dataString = rawData
+ .map((entry: any) => {
+ return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
+ })
+ .join("");
+ } else if (selectedSource === "pubmed") {
+ rawData = await fetchPubMedData(topic, 2020, offset, 2);
+ if (!rawData) {
+ throw new Error("未搜索到文献 from PubMed.");
+ }
+ newReferences = rawData.map((entry: any) => ({
+ id: entry.id, // 文章的 PubMed ID
+ title: entry.title, // 文章的标题
+ abstract: entry.abstract, // 文章的摘要
+ author: entry.authors?.slice(0, 3).join(", "), // 文章的作者列表，假设为字符串数组
+ year: entry.year, // 文章的发表日期
+ journal: entry.journal, // 文章的发表杂志
+ url: entry.url, // 文章的 URL
+ source: "PubMed", // 指示这些引用来自 PubMed
+ }));
- // 打印或进一步处理 newReferences
- console.log(newReferences);
+ // 打印或进一步处理 newReferences
+ console.log(newReferences);
- dataString = rawData
- .map((entry) => {
- return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
+ dataString = rawData
+ .map((entry: any) => {
+ return `Time: ${entry.year}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
+ })
+ .join("");
+ }
+ //在对应的位置添加文献
+ const nearestNumber = getNumberBeforeCursor(quill!);
+ dispatch(
+ addReferencesRedux({
+ references: newReferences,
+ position: nearestNumber,
})
- .join("");
- }
- //在对应的位置添加文献
- const nearestNumber = getNumberBeforeCursor(quill);
- dispatch(
- addReferencesRedux({
- references: newReferences,
- position: nearestNumber,
- })
- );
+ );
- // 确保搜索到的论文不超过 3000 个字符
- const trimmedMessage =
- dataString.length > 3000 ? dataString.slice(0, 3000) : dataString;
- //slate的方法
- // const content = `需要完成的论文主题：${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：${getTextBeforeCursor(
- quill,
- 500
- )},搜索到的论文内容:${trimmedMessage},需要完成的论文主题：${topic},请根据搜索到的论文内容完成用户的论文`;
- await sendMessageToOpenAI(
- content,
- quill,
- selectedModel,
- apiKey,
- upsreamUrl,
- systemPrompt
- );
- setUserInput("");
- // 重新获取更新后的内容并更新 Redux store
- const updatedContent = quill.root.innerHTML;
- dispatch(setEditorContent(updatedContent));
- if (isVip) {
- //在云端同步supabase
- const data = await submitPaper(
- supabase,
- updatedContent,
- references,
- paperNumberRedux
+ // 确保搜索到的论文不超过 3000 个字符
+ const trimmedMessage =
+ dataString.length > 3000 ? dataString.slice(0, 3000) : dataString;
+ //slate的方法
+ // const content = `需要完成的论文主题：${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：${getTextBeforeCursor(
+ quill!,
+ 900
+ )},搜索到的论文内容:${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`;
+ await sendMessageToOpenAI(
+ content,
+ quill!,
+ selectedModel!,
+ apiKey,
+ upsreamUrl,
+ systemPrompt
);
+ setUserInput("");
+ // 重新获取更新后的内容并更新 Redux store
+ const updatedContent = quill!.root.innerHTML;
+ dispatch(setEditorContent(updatedContent));
+ 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;
+ } catch (error) {
+ // console.error("Error fetching data:", error);
+ // 在处理错误后，再次抛出这个错误
+ throw new Error(`Paper2AI出现错误: ${error}`);
}
- } catch (error) {
- // console.error("Error fetching data:", error);
- // 在处理错误后，再次抛出这个错误
- throw new Error(`Paper2AI出现错误: ${error}`);
}
}
@@ -414,12 +428,18 @@ const QEditor = ({ lng }) => {
+