refractor: 使得判断文献是否修改更有效率

components/GetArxiv.tsx

@@ -76,7 +76,7 @@ function extractArxivData(data: ArxivFeed) {
       id: entry.id[0],
       published: entry.published[0],
       title: entry.title[0],
-      summary: entry.summary[0],
+      abstract: entry.summary[0],
       authors: entry.author.map((author) => author.name[0]),
     };
   });

components/GetPubMed .tsx

@@ -77,7 +77,7 @@ async function getPubMedPaperDetails(idList: IDList) {
     const articles = result.PubmedArticleSet.PubmedArticle.map((article) => {
       const medlineCitation = article.MedlineCitation;
       const articleDetails = medlineCitation.Article;
-
+      console.log("atricledetails", articleDetails);
       const abstractTexts = articleDetails.Abstract.AbstractText;
 
       let abstract;
@@ -155,8 +155,7 @@ async function getPubMedPaperDetails(idList: IDList) {
 
     return articles;
   } catch (error) {
-    console.error("Error fetching paper details from PubMed:", error);
-    return null;
+    throw new Error(`Error fetching paper details from PubMed:", ${error}`);
   }
 }
 

components/QuillEditor.tsx

@@ -10,7 +10,7 @@ import Link from "next/link";
 import getArxivPapers from "./GetArxiv";
 import getSemanticPapers from "./GetSemantic";
 import { fetchPubMedData } from "./GetPubMed ";
-import { getAI, sendMessageToOpenAI } from "./chatAI";
+import { sendMessageToOpenAI } from "./chatAI";
 import {
   getTextBeforeCursor,
   convertToSuperscript,
@@ -288,12 +288,15 @@ const QEditor = ({ lng }) => {
           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 getAI(
+          topic = await sendMessageToOpenAI(
             userMessage,
-            prompt,
+            null,
+            selectedModel!,
             apiKey,
             upsreamUrl,
-            selectedModel!
+            prompt,
+            null,
+            false
           );
           console.log("topic in AI before removeSpecialCharacters", topic);
           topic = removeSpecialCharacters(topic);
@@ -304,6 +307,8 @@ const QEditor = ({ lng }) => {
           }
         }
         console.log("topic in AI", topic);
+        console.log("offset in paper2AI", offset);
+        console.log("limit in paper2AI", limit);
         let rawData, dataString, newReferences;
         if (selectedSource === "arxiv") {
           rawData = await getArxivPapers(topic, limit, offset);
@@ -329,7 +334,7 @@ const QEditor = ({ lng }) => {
           }));
           dataString = rawData
             .map((entry: any) => {
-              return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.summary}\n\n`;
+              return `ID: ${entry.id}\nTime: ${entry.published}\nTitle: ${entry.title}\nSummary: ${entry.abstract}\n\n`;
             })
             .join("");
         } else if (selectedSource === "semanticScholar") {

components/Settings.tsx

@@ -47,7 +47,7 @@ const Settings = ({ lng }: { lng: string }) => {
       upstreamUrl: "https://cocopilot-pool.aivvm.com",
     },
     {
-      name: t("configurations.custom"),
+      name: t("configurations.蒙恬大将军"),
       apiKey: "sk-jokVJ90l5Swxr5dt2f3b0988C8A442A69f97Ee4eAf7aDcF4",
       upstreamUrl: "https://freeapi.iil.im",
     },

components/chatAI.tsx

@@ -23,12 +23,13 @@ function isValidApiKey(apiKey: string) {
 
 const sendMessageToOpenAI = async (
   content: string,
-  editor: Quill,
+  editor: Quill | null,
   selectedModel: string,
   apiKey: string,
   upsreamUrl: string,
   prompt: string,
-  cursorPosition: number
+  cursorPosition: number | null,
+  useEditorFlag = true // 新增的标志，用于决定操作
 ) => {
   //识别应该使用的模型
   let model = selectedModel;
@@ -47,7 +48,7 @@ const sendMessageToOpenAI = async (
     },
     body: JSON.stringify({
       model: model,
-      stream: true,
+      stream: useEditorFlag, // 根据标志确定是否使用streaming
       messages: [
         {
           role: "system",
@@ -83,16 +84,23 @@ const sendMessageToOpenAI = async (
     if (!response.ok || !response.body) {
       throw new Error("");
     }
-    const reader = response.body.getReader();
-    const decoder = new TextDecoder();
-    //开始前先进行换行
-    // editor.focus();
-    editor.insertText(editor.getSelection(true).index, "\n");
-    await processResult(reader, decoder, editor);
-    //搜索是否有相同的括号编号，如果有相同的则删除到只剩一个
-    convertToSuperscript(editor);
-    deleteSameBracketNumber(editor, cursorPosition);
-    updateBracketNumbersInDeltaKeepSelection(editor);
+    if (useEditorFlag && editor && cursorPosition !== null) {
+      const reader = response.body.getReader();
+      const decoder = new TextDecoder();
+      //开始前先进行换行
+      // editor.focus();
+      editor.insertText(editor.getSelection(true).index, "\n");
+      await processResult(reader, decoder, editor);
+      //搜索是否有相同的括号编号，如果有相同的则删除到只剩一个
+      convertToSuperscript(editor);
+      deleteSameBracketNumber(editor, cursorPosition);
+      updateBracketNumbersInDeltaKeepSelection(editor);
+    } else {
+      // 直接返回结果的逻辑
+      const data = await response.json();
+      const content = data.choices[0].message.content;
+      return content; // 或根据需要处理并返回数据
+    }
   } catch (error) {
     console.error("Error:", error);
     // 如果有响应，返回响应的原始内容
@@ -188,13 +196,6 @@ async function processResult(reader, decoder, editor) {
             }
           }
         } catch (error) {
-          // console.error(
-          //   "there is a error in parse JSON object:",
-          //   jsonStr,
-          //   "error reason",
-          //   error
-          // );
-          // break;
           throw new Error(`
             there is a error in parse JSON object: ${jsonStr},
             error reason: ${error}`);

utils/others/aiutils.ts

@@ -1,5 +1,5 @@
 // Path: utils/others/aiutils.ts
-import { getAI } from "@/components/chatAI";
+import { sendMessageToOpenAI } from "@/components/chatAI";
 //判断返回的文献是否跟用户输入的主题相关
 export async function evaluateTopicMatch(
   userMessage: any[],
@@ -13,13 +13,28 @@ export async function evaluateTopicMatch(
   let nonRelevantPapers: string[] = []; // 存储不相关论文的数组
 
   for (const paper of userMessage) {
+    if (relevantPapers.length >= 2) {
+      console.log("已找到两篇相关文献，停止处理剩余文献。");
+      break; // 如果已经有两篇相关文献，则停止处理
+    }
+    // 检查是否存在 abstract，如果不存在，直接将论文添加到 nonRelevantPapers
+    if (!paper.abstract) {
+      nonRelevantPapers.push(paper);
+      console.log(
+        `Paper titled "${paper.title}" has no abstract and was added to non-relevant papers.`
+      );
+      continue; // 跳过当前迭代，继续下一个论文
+    }
     const input = `user's topic:${topic}, \n paper's title: ${paper.title}, \n paper's abstract: ${paper.abstract}`;
-    const isRelevantResult = await getAI(
+    const isRelevantResult = await sendMessageToOpenAI(
       input,
-      prompt,
+      null,
+      selectedModel!,
       apiKey,
       upsreamUrl,
-      selectedModel!
+      prompt,
+      null,
+      false
     );
     console.log("isRelevantResult", isRelevantResult);
     // 尝试解析 JSON 结果，如果无法解析则直接使用结果字符串
@@ -38,14 +53,15 @@ export async function evaluateTopicMatch(
     } else {
       nonRelevantPapers.push(paper); // 如果论文不相关，则添加到不相关论文数组中
     }
-    console.log(
-      `这次有${nonRelevantPapers.length}篇文献没有通过相关性检查`,
-      nonRelevantPapers
-    );
   }
+  console.log(
+    `这次有${nonRelevantPapers.length}篇文献没有通过相关性检查`,
+    nonRelevantPapers
+  );
   //如果相关文献大于两片则缩减到两篇
-  if (relevantPapers.length > 2) {
-    relevantPapers = relevantPapers.slice(0, 2);
-  }
+  // if (relevantPapers.length > 2) {
+  //   relevantPapers = relevantPapers.slice(0, 2);
+  //   console.log("文献太多了，只取前两篇");
+  // }
   return { relevantPapers, nonRelevantPapers };
 }