diff --git a/plugin/aichat/main.go b/plugin/aichat/main.go
index dbb9e9aa..fc78af58 100644
--- a/plugin/aichat/main.go
+++ b/plugin/aichat/main.go
@@ -2,6 +2,7 @@
 package aichat
 
 import (
+	"errors"
 	"math/rand"
 	"strconv"
 	"strings"
@@ -46,7 +47,9 @@ var (
 			"- 设置AI聊天(不)以AI语音输出\n" +
 			"- 查看AI聊天配置\n" +
 			"- 重置AI聊天\n" +
-			"- 群聊总结 [消息数目]|群聊总结 1000\n",
+			"- 群聊总结 [消息数目]|群聊总结 1000\n" +
+			"- /gpt [内容] （使用大模型聊天）\n",
+
 		PrivateDataFolder: "aichat",
 	})
 )
@@ -61,6 +64,32 @@ var (
 	limit   = ctxext.NewLimiterManager(time.Second*30, 1)
 )
 
+// getModelParams 获取模型参数：温度(float32(temp)/100)、TopP和最大长度
+func getModelParams(temp int64) (temperature float32, topp float32, maxn uint) {
+	// 处理温度参数
+	if temp <= 0 {
+		temp = 70 // default setting
+	}
+	if temp > 100 {
+		temp = 100
+	}
+	temperature = float32(temp) / 100
+
+	// 处理TopP参数
+	topp = cfg.TopP
+	if topp == 0 {
+		topp = 0.9
+	}
+
+	// 处理最大长度参数
+	maxn = cfg.MaxN
+	if maxn == 0 {
+		maxn = 4096
+	}
+
+	return temperature, topp, maxn
+}
+
 func init() {
 	en.OnMessage(ensureconfig, func(ctx *zero.Ctx) bool {
 		return ctx.ExtractPlainText() != "" &&
@@ -88,39 +117,25 @@ func init() {
 			return
 		}
 
-		if temp <= 0 {
-			temp = 70 // default setting
-		}
-		if temp > 100 {
-			temp = 100
-		}
+		temperature, topp, maxn := getModelParams(temp)
 
 		x := deepinfra.NewAPI(cfg.API, cfg.Key)
 		var mod model.Protocol
-		maxn := cfg.MaxN
-		if maxn == 0 {
-			maxn = 4096
-		}
-		topp := cfg.TopP
-		if topp == 0 {
-			topp = 0.9
-		}
-
 		switch cfg.Type {
 		case 0:
 			mod = model.NewOpenAI(
 				cfg.ModelName, cfg.Separator,
-				float32(temp)/100, topp, maxn,
+				temperature, topp, maxn,
 			)
 		case 1:
 			mod = model.NewOLLaMA(
 				cfg.ModelName, cfg.Separator,
-				float32(temp)/100, topp, maxn,
+				temperature, topp, maxn,
 			)
 		case 2:
 			mod = model.NewGenAI(
 				cfg.ModelName,
-				float32(temp)/100, topp, maxn,
+				temperature, topp, maxn,
 			)
 		default:
 			logrus.Warnln("[aichat] unsupported AI type", cfg.Type)
@@ -319,6 +334,16 @@ func init() {
 	// 添加群聊总结功能
 	en.OnRegex(`^群聊总结\s?(\d*)$`, ensureconfig, zero.OnlyGroup, zero.AdminPermission).SetBlock(true).Limit(limit.LimitByGroup).Handle(func(ctx *zero.Ctx) {
 		ctx.SendChain(message.Text("少女思考中..."))
+		gid := ctx.Event.GroupID
+		if gid == 0 {
+			gid = -ctx.Event.UserID
+		}
+		c, ok := ctx.State["manager"].(*ctrl.Control[*zero.Ctx])
+		if !ok {
+			return
+		}
+		rate := c.GetData(gid)
+		temp := (rate >> 8) & 0xff
 		p, _ := strconv.ParseInt(ctx.State["regex_matched"].([]string)[1], 10, 64)
 		if p > 1000 {
 			p = 1000
@@ -326,10 +351,9 @@ func init() {
 		if p == 0 {
 			p = 200
 		}
-		gid := ctx.Event.GroupID
 		group := ctx.GetGroupInfo(gid, false)
 		if group.MemberCount == 0 {
-			ctx.SendChain(message.Text(zero.BotConfig.NickName[0], "未加入", group.Name, "(", gid, "),无法获取摘要"))
+			ctx.SendChain(message.Text(zero.BotConfig.NickName[0], "未加入", group.Name, "(", gid, "),无法获取总结"))
 			return
 		}
 
@@ -350,8 +374,13 @@ func init() {
 			return
 		}
 
-		// 调用大模型API进行摘要
-		summary, err := summarizeMessages(messages)
+		// 构造总结请求提示
+		summaryPrompt := "请总结这个群聊内容，要求按发言顺序梳理，明确标注每个发言者的昵称，并完整呈现其核心观点、提出的问题、发表的看法或做出的回应，确保不遗漏关键信息，且能体现成员间的对话逻辑和互动关系:\n" +
+			strings.Join(messages, "\n")
+
+		// 调用大模型API进行总结
+		summary, err := llmchat(summaryPrompt, temp)
+
 		if err != nil {
 			ctx.SendChain(message.Text("ERROR: ", err))
 			return
@@ -367,13 +396,108 @@ func init() {
 		b.WriteString(" 条消息总结:\n\n")
 		b.WriteString(summary)
 
-		// 分割总结内容为多段
-		parts := strings.Split(b.String(), "\n\n")
-		msg := make(message.Message, 0, len(parts))
-		for _, part := range parts {
-			if part != "" {
-				msg = append(msg, ctxext.FakeSenderForwardNode(ctx, message.Text(part)))
+		// 分割总结内容为多段（按1000字符长度切割）
+		summaryText := b.String()
+		msg := make(message.Message, 0)
+		for len(summaryText) > 0 {
+			if len(summaryText) <= 1000 {
+				msg = append(msg, ctxext.FakeSenderForwardNode(ctx, message.Text(summaryText)))
+				break
 			}
+
+			// 查找1000字符内的最后一个换行符，尽量在换行处分割
+			chunk := summaryText[:1000]
+			lastNewline := strings.LastIndex(chunk, "\n")
+			if lastNewline > 0 {
+				chunk = summaryText[:lastNewline+1]
+			}
+
+			msg = append(msg, ctxext.FakeSenderForwardNode(ctx, message.Text(chunk)))
+			summaryText = summaryText[len(chunk):]
+		}
+		if len(msg) > 0 {
+			ctx.Send(msg)
+		}
+	})
+
+	// 添加 /gpt 命令处理（同时支持回复消息和直接使用）
+	en.OnKeyword("/gpt", ensureconfig).SetBlock(true).Handle(func(ctx *zero.Ctx) {
+		gid := ctx.Event.GroupID
+		if gid == 0 {
+			gid = -ctx.Event.UserID
+		}
+		c, ok := ctx.State["manager"].(*ctrl.Control[*zero.Ctx])
+		if !ok {
+			return
+		}
+		rate := c.GetData(gid)
+		temp := (rate >> 8) & 0xff
+		text := ctx.MessageString()
+
+		var query string
+		var replyContent string
+
+		// 检查是否是回复消息 (使用MessageElement检查而不是CQ码)
+		for _, elem := range ctx.Event.Message {
+			if elem.Type == "reply" {
+				// 提取被回复的消息ID
+				replyIDStr := elem.Data["id"]
+				replyID, err := strconv.ParseInt(replyIDStr, 10, 64)
+				if err == nil {
+					// 获取被回复的消息内容
+					replyMsg := ctx.GetMessage(replyID)
+					if replyMsg.Elements != nil {
+						replyContent = replyMsg.Elements.ExtractPlainText()
+					}
+				}
+				break // 找到回复元素后退出循环
+			}
+		}
+
+		// 提取 /gpt 后面的内容
+		parts := strings.SplitN(text, "/gpt", 2)
+
+		var gContent string
+		if len(parts) > 1 {
+			gContent = strings.TrimSpace(parts[1])
+		}
+
+		// 组合内容：优先使用回复内容，如果同时有/gpt内容则拼接
+		switch {
+		case replyContent != "" && gContent != "":
+			query = replyContent + "\n" + gContent
+		case replyContent != "":
+			query = replyContent
+		case gContent != "":
+			query = gContent
+		default:
+			return
+		}
+
+		// 调用大模型API进行聊天
+		reply, err := llmchat(query, temp)
+		if err != nil {
+			ctx.SendChain(message.Text("ERROR: ", err))
+			return
+		}
+
+		// 分割总结内容为多段（按1000字符长度切割）
+		msg := make(message.Message, 0)
+		for len(reply) > 0 {
+			if len(reply) <= 1000 {
+				msg = append(msg, ctxext.FakeSenderForwardNode(ctx, message.Text(reply)))
+				break
+			}
+
+			// 查找1000字符内的最后一个换行符，尽量在换行处分割
+			chunk := reply[:1000]
+			lastNewline := strings.LastIndex(chunk, "\n")
+			if lastNewline > 0 {
+				chunk = reply[:lastNewline+1]
+			}
+
+			msg = append(msg, ctxext.FakeSenderForwardNode(ctx, message.Text(chunk)))
+			reply = reply[len(chunk):]
 		}
 		if len(msg) > 0 {
 			ctx.Send(msg)
@@ -381,20 +505,34 @@ func init() {
 	})
 }
 
-// summarizeMessages 调用大模型API进行消息摘要
-func summarizeMessages(messages []string) (string, error) {
-	// 使用现有的AI配置进行摘要
+// llmchat 调用大模型API包装
+func llmchat(prompt string, temp int64) (string, error) {
+	temperature, topp, maxn := getModelParams(temp) // 使用默认温度70
+
 	x := deepinfra.NewAPI(cfg.API, cfg.Key)
-	mod := model.NewOpenAI(
-		cfg.ModelName, cfg.Separator,
-		float32(70)/100, 0.9, 4096,
-	)
+	var mod model.Protocol
+	switch cfg.Type {
+	case 0:
+		mod = model.NewOpenAI(
+			cfg.ModelName, cfg.Separator,
+			temperature, topp, maxn,
+		)
+	case 1:
+		mod = model.NewOLLaMA(
+			cfg.ModelName, cfg.Separator,
+			temperature, topp, maxn,
+		)
+	case 2:
+		mod = model.NewGenAI(
+			cfg.ModelName,
+			temperature, topp, maxn,
+		)
+	default:
+		logrus.Warnln("[aichat] unsupported AI type", cfg.Type)
+		return "", errors.New("不支持的AI类型")
+	}
 
-	// 构造摘要请求提示
-	summaryPrompt := "请总结这个群聊内容，要求按发言顺序梳理，明确标注每个发言者的昵称，并完整呈现其核心观点、提出的问题、发表的看法或做出的回应，确保不遗漏关键信息，且能体现成员间的对话逻辑和互动关系:\n\n" +
-		strings.Join(messages, "\n---\n")
-
-	data, err := x.Request(mod.User(summaryPrompt))
+	data, err := x.Request(mod.User(prompt))
 	if err != nil {
 		return "", err
 	}