feat: 首次推送到Gitea - 完整项目代码 + 安全加固 + 知识库

scripts/bot-feedback-loop.mjs

@@ -6,6 +6,8 @@ import { fileURLToPath } from "url";
 import OpenAI from "openai";
 import "dotenv/config";
 import { withRetry } from "./lib/retry.mjs";
+import { pickCommentStyle, getStyleHint } from "./lib/topic-diversity.mjs";
+import { validateContextRelevance, detectBadPatterns } from "./lib/reply-quality.mjs";
 
 const __dirname = dirname(fileURLToPath(import.meta.url));
 const base = process.env.DATABASE_URL.replace("mysql://", "mariadb://");
@@ -16,11 +18,11 @@ const prisma = new PrismaClient({ adapter });
 
 const openai = new OpenAI({
   apiKey: process.env.DEEPSEEK_API_KEY,
-  baseURL: "https://api.deepseek.com/v1",
+  baseURL: "https://api.deepseek.com",
 });
 
 const BOT_DATA_PATH = resolve(__dirname, "..", "data", "bot-characters.json");
-const MODEL = process.env.DEEPSEEK_MODEL || "deepseek-chat";
+const MODEL = process.env.DEEPSEEK_MODEL || "deepseek-v4-pro";
 
 const LAYER = {
   SESSION: "SESSION",
@@ -91,10 +93,13 @@ async function incrementStat(botUserId, field, by = 1) {
 }
 
 async function getProcessedReplyIds(botUserId) {
+  // 只回看最近 7 天的反馈记忆，避免全量扫描随数据增长而变慢
+  const since = new Date(Date.now() - 7 * 24 * 60 * 60 * 1000);
   const memories = await prisma.botMemory.findMany({
     where: {
       botId: botUserId,
       memoryType: MEMORY_TYPE.FEEDBACK,
+      createdAt: { gte: since },
     },
     select: { contextTags: true },
   });
@@ -108,12 +113,19 @@ async function getProcessedReplyIds(botUserId) {
   return ids;
 }
 
-function buildFollowUpPrompt(bot, topicTitle, topicContent, originalPost, allReplies) {
+// 📄 核心 Prompt 模板参考: scripts/prompts/bot-feedback.txt
+// 实际 prompt 构建逻辑保留了动态参数注入（角色设定、回复风格、上下文等）
+function buildFollowUpPrompt(bot, topicTitle, topicContent, originalPost, allReplies, options = {}) {
+  const { commentStyle = null } = options;
   const p = bot.personality;
   const repliesText = allReplies
     .map((r, i) => `${i + 1}. ${r.author}: ${r.content.slice(0, 250)}`)
     .join("\n");
 
+  const styleHint = commentStyle
+    ? `\n[本次回复风格指引] ${getStyleHint(commentStyle)}\n`
+    : "";
+
   return `你正在参与"追光AI行业论坛"。你之前在"${topicTitle}"这个话题下发了主帖，现在有用户回复了你，你需要用你的人格接着聊。
 
 [你的角色设定]
@@ -128,7 +140,7 @@ ${topicContent}
 
 [新收到的回复]
 ${repliesText}
-
+${styleHint}
 [二次回复要求]
 1. 像真人接话，120-350字，不能太长刷屏
 2. 必须对前面至少一个具体观点有回应（赞同/质疑/补充案例/反问）
@@ -150,7 +162,8 @@ async function callDeepSeek(prompt) {
       model: MODEL,
       messages: [{ role: "user", content: prompt }],
       temperature: 0.88,
-      max_tokens: 800,
+      // DeepSeek V4 推理 token 计入 max_tokens，预算不足会导致正文截断/为空
+      max_tokens: 4096,
     })
   );
   const text = response.choices[0].message.content.trim();
@@ -272,7 +285,9 @@ async function processBotFeedback(botKey, botChar) {
       await incrementStat(botConfig.id, "humanInteractions", humanCount);
     }
 
+    // 只有当有真人回复时，Bot才进行二次回复（避免Bot之间互相回复）
     if (
+      humanCount > 0 &&
       newReplies.length >= MIN_FEEDBACK_TO_FOLLOWUP &&
       Math.random() < FOLLOW_UP_PROBABILITY &&
       followUpsSent < MAX_FOLLOWUP_PER_RUN_PER_BOT &&
@@ -283,12 +298,16 @@ async function processBotFeedback(botKey, botChar) {
           author: p.user.name || "匿名",
           content: p.content,
         }));
+
+        // 选择回复风格，确保多样性
+        const commentStyle = pickCommentStyle();
         const prompt = buildFollowUpPrompt(
           botChar,
           topic.title,
           topic.content,
           null,
-          repliesForPrompt
+          repliesForPrompt,
+          { commentStyle }
         );
         const result = await callDeepSeek(prompt);
         const followUpContent = (result.content || "").trim();
@@ -297,6 +316,19 @@ async function processBotFeedback(botKey, botChar) {
           continue;
         }
 
+        // 质量检查：反模式检测
+        const badPatterns = detectBadPatterns(followUpContent);
+        if (badPatterns.isGeneric) {
+          console.warn(`${ts()}   ⚠️ ${botChar.displayName} 回复过于通用 (pattern_matches=${badPatterns.matchCount}), 但仍保留`);
+        }
+
+        // 关联度检查
+        const contextForRelevance = repliesForPrompt.map(r => r.content).join(" ");
+        const { score: relevanceScore } = validateContextRelevance(followUpContent, contextForRelevance);
+
+        // 多样性度量日志
+        console.log(`${ts()}   📊 ${botChar.displayName}: comment_style=${commentStyle}, relevance=${(relevanceScore / 100).toFixed(2)}, generic=${badPatterns.isGeneric}`);
+
         const post = await prisma.forumPost.create({
           data: {
             topicId: topic.id,
@@ -324,6 +356,12 @@ async function processBotFeedback(botKey, botChar) {
             topicId: topic.id,
             triggeredBy: "feedback_loop",
             summary: followUpContent.slice(0, 100),
+            qualityMetrics: {
+              commentStyle,
+              relevance: relevanceScore / 100,
+              isGeneric: badPatterns.isGeneric,
+              patternMatches: badPatterns.matchCount,
+            },
           },
           0.6,
           {