feat(数据源): 添加Reddit数据源并优化现有功能

新增Reddit数据源支持，包括获取、翻译和展示功能
优化Twitter数据源显示逻辑
添加fetch请求超时处理
调整数据源配置和分类
更新页脚链接和图片地址

src/handlers/writeRssData.js

@@ -2,22 +2,31 @@ import { replaceImageProxy, formatMarkdownText, formatDateToGMT12WithTime } from
 import { getDailyReportContent } from '../github.js';
 import { storeInKV } from '../kv.js';
 import { marked } from '../marked.esm.js';
+import { callChatAPI } from '../chatapi.js'; // 导入 callChatAPI
+import { getSummarizationSimplifyPrompt } from "../prompt/summarizationSimplifyPrompt";
 
 export async function handleWriteRssData(request, env) {
     const url = new URL(request.url);
     const dateStr = url.searchParams.get('date');
+    console.log(`[writeRssData] Received request for date: ${dateStr}`);
 
     if (!dateStr) {
+        console.error('[writeRssData] Missing date parameter');
         return new Response('Missing date parameter', { status: 400 });
     }
 
     try {
         const path = `daily/${dateStr}.md`;
-        const content = await getDailyReportContent(env, path);
+        console.log(`[writeRssData] Attempting to get content from GitHub path: ${path}`);
+        let content = await getDailyReportContent(env, path);
+        
         if (!content) {
+            console.warn(`[writeRssData] No content found for ${path}. Returning 404.`);
             return new Response(`No content found for ${path}`, { status: 404 });
         }
+        console.log(`[writeRssData] Successfully retrieved content for ${path}. Content length: ${content.length}`);
 
+        //content = extractContentFromSecondHash(content);
         // 从 "YYYY-MM-DD" 格式的 dateStr 中提取 "YYYY-MM"
         const yearMonth = dateStr.substring(0, 7);
         const report = {
@@ -28,15 +37,61 @@ export async function handleWriteRssData(request, env) {
             // 可以添加其他相關欄位，例如作者、來源等
             published_date: formatDateToGMT12WithTime(new Date()) // 記錄保存時間
         }
-        report.content_html = marked.parse(formatMarkdownText(replaceImageProxy(env.IMG_PROXY, content)));
-        storeInKV(env.DATA_KV, `${dateStr}-report`, report);
+        report.content_html = marked.parse(formatMarkdownText(replaceImageProxy(env, content)));
+        
+        const kvKey = `${dateStr}-report`;
+        console.log(`[writeRssData] Preparing to store report in KV. Key: ${kvKey}, Report object:`, JSON.stringify(report).substring(0, 200) + '...'); // Log first 200 chars
+        await storeInKV(env.DATA_KV, kvKey, report);
+        console.log(`[writeRssData] Successfully stored report in KV with key: ${kvKey}`);
 
         return new Response(JSON.stringify(report), {
             headers: { 'Content-Type': 'application/json' },
             status: 200
         });
     } catch (error) {
-        console.error('Error handling daily report:', error.message);
+        console.error('[writeRssData] Error handling daily report:', error.message, error.stack);
         return new Response(`Error handling daily report: ${error.message}`, { status: 500 });
     }
-}
+}
+
+/**
+ * 从第二个 ### 开始截取内容，包括 ###。
+ *
+ * @param {string} content - 原始文本内容。
+ * @returns {string} 截取后的内容。
+ */
+export function extractContentFromSecondHash(content) {
+    const parts = content.split('###');
+    if (parts.length > 2) {
+        // 原始逻辑：重新组合从第二个 ### 开始的所有部分
+        const newcontent = '###' + parts.slice(2).join('###');
+        const lastHashIndex = newcontent.lastIndexOf('###');
+        if (lastHashIndex !== -1) {
+            return newcontent.substring(0, lastHashIndex);
+        }
+    }
+    return content; // 如果没有找到 ### 或不符合上述条件，则返回原始内容
+}
+
+/**
+ * 调用 Gemini 或 OpenAI 模型生成指定提示词的内容。
+ * 此方法可供外部调用。
+ *
+ * @param {object} env - 环境对象，包含 AI 模型相关的配置。
+ * @param {string} promptText - 用户提示词。
+ * @returns {Promise<string>} AI 模型生成的内容。
+ * @throws {Error} 如果 API 调用失败或返回空内容。
+ */
+export async function generateAIContent(env, promptText) {
+    console.log(`[generateAIContent] Calling AI model with prompt: ${promptText.substring(0, 100)}...`);
+    try {
+        let result = await callChatAPI(env, promptText, getSummarizationSimplifyPrompt());
+        console.log(`[generateAIContent] AI model returned content. Length: ${result.length}`);
+
+        result += "\n\n </br>"+env.INSERT_APP_URL;
+        return result;
+    } catch (error) {
+        console.error('[generateAIContent] Error calling AI model:', error.message, error.stack);
+        throw new Error(`Failed to generate AI content: ${error.message}`);
+    }
+}