feat: 修剪用户输入并清理大模型响应以优化输出格式

controller/groupAgent/agent.ts

@@ -45,7 +45,7 @@ const agent = async (ctx: Context.Data) => {
   logger.debug(`Chat history: ${JSON.stringify(chatHistory)}`)
 
   // 根据Mention，拼装原始消息
-  let userInput = rawMsgText
+  let userInput = rawMsgText.trim()
   for (const mention of mentions ?? []) {
     if (mention.name !== appInfo.app_name) {
       userInput = userInput.replace(mention.key, `@${mention.name}`)
@@ -57,7 +57,7 @@ const agent = async (ctx: Context.Data) => {
   // 调用大模型
   try {
     await updateCard(cardGender.genPendingCard("LLM激情输出中，请稍等..."))
-    const llmRes = await llm.invoke(
+    const llmRes = (await llm.invoke(
       "groupAgent",
       {
         userName: historyMentions.get(openId || "") ?? "用户",
@@ -66,11 +66,14 @@ const agent = async (ctx: Context.Data) => {
         time: new Date().toLocaleString("zh-CN", { timeZone: "Asia/Shanghai" }),
       },
       requestId
-    )
+    )) as string
     logger.info(
       `LLM invoked successfully, see detail: http://langfuse.ai.srv/project/cm1j2tkj9001gukrgdvc1swuw/sessions/${requestId}`
     )
-    await updateCard(cardGender.genSuccessCard(llmRes))
+    const cleanedLlmRes = llmRes
+      .replace(/```(\w+)?\n([\s\S]*?)```/g, "$2")
+      .trim()
+    await updateCard(cardGender.genSuccessCard(cleanedLlmRes))
   } catch (error: any) {
     logger.error(`Failed to invoke llm: ${error.message}`)
     await updateCard(cardGender.genErrorCard("LLM调用失败: " + error.message))