feat(chat): add langchaingo agent execution path for chat module

chat/chat.go

@@ -120,6 +120,19 @@ type promptData struct {
 	BotUsername     string // 添加 Bot 用户名字段
 }
 
+func extractInputFromMessage(msg *tb.Message, trigger *config.ChatTrigger) string {
+	input := msg.Text
+	if input == "" {
+		input = msg.Caption
+	}
+	if trigger.Command != "" {
+		if _, text, err := entities.CommandFromText(input, 0); err == nil {
+			input = text
+		}
+	}
+	return input
+}
+
 // Chat 处理聊天请求
 func Chat(ctx tb.Context, v2 *config.ChatConfigSingle, trigger *config.ChatTrigger) error {
 
@@ -137,16 +150,7 @@ func Chat(ctx tb.Context, v2 *config.ChatConfigSingle, trigger *config.ChatTrigg
 		return nil
 	}
 
-	input := ctx.Message().Text
-	if input == "" {
-		input = ctx.Message().Caption
-	}
-	if trigger.Command != "" {
-		_, text, err := entities.CommandFromText(input, 0)
-		if err != nil {
-			input = text
-		}
-	}
+	input := extractInputFromMessage(ctx.Message(), trigger)
 
 	// if gacha, reply and not send placeholder
 	isGacha := trigger.Gacha > 0
@@ -206,6 +210,7 @@ func Chat(ctx tb.Context, v2 *config.ChatConfigSingle, trigger *config.ChatTrigg
 	}
 
 	multiPartContent := false
+	var imageDataURL string
 	var contents []openai.ChatMessagePart
 	if v2.Model.Features.Image && v2.Features.Image {
 		// TODO handle multi photos album
@@ -244,11 +249,12 @@ func Chat(ctx tb.Context, v2 *config.ChatConfigSingle, trigger *config.ChatTrigg
 			base64Img := []byte("data:image/jpeg;base64,")
 			base64Img = base64.StdEncoding.AppendEncode(base64Img, buf.Bytes())
 			log.Info("encoded base64 image data url size", zap.Int("size", len(base64Img)))
+			imageDataURL = string(base64Img)
 			contents = append(contents,
 				openai.ChatMessagePart{
 					Type: openai.ChatMessagePartTypeImageURL,
 					ImageURL: &openai.ChatMessageImageURL{
-						URL: string(base64Img),
+						URL: imageDataURL,
 					},
 				},
 				openai.ChatMessagePart{
@@ -275,8 +281,6 @@ final:
 
 	// zap.L().Debug("Chat context messages", zap.Any("messages", messages))
 
-	client := clients[v2.Model.Name]
-
 	// 处理place_holder功能
 	var placeholderMsg *tb.Message
 	switch {
@@ -288,7 +292,6 @@ final:
 		placeholderMsg, placeHolderErr = ctx.Bot().Reply(ctx.Message(), v2.PlaceHolder, tb.ModeMarkdownV2)
 		if placeHolderErr != nil {
 			log.Error("Failed to send placeholder message", zap.Error(placeHolderErr))
-			// 如果发送placeholder失败，继续正常流程，不使用placeholder功能
 		}
 	default:
 		err = ctx.Bot().Notify(ctx.Chat(), tb.Typing)
@@ -300,24 +303,91 @@ final:
 	chatCtx, cancel := context.WithTimeout(context.Background(), v2.GetTimeout())
 	defer cancel()
 
+	// Use agent-based execution path if enabled
+	if v2.Agent.Enabled {
+		return chatWithAgent(chatCtx, ctx, v2, systemPrompt, promptBuf.String(),
+			multiPartContent, imageDataURL, placeholderMsg, messages)
+	}
+
+	// Legacy execution path using direct OpenAI SDK
+	return chatWithLegacy(chatCtx, ctx, v2, messages, placeholderMsg)
+
+}
+
+// chatWithAgent executes the chat using the langchaingo agent-based path.
+func chatWithAgent(
+	chatCtx context.Context, ctx tb.Context, v2 *config.ChatConfigSingle,
+	systemPrompt string, userPrompt string,
+	multiPartContent bool, imageURL string,
+	placeholderMsg *tb.Message,
+	messages []openai.ChatCompletionMessage,
+) error {
+	model := getLangchainModel(v2.Model.Name)
+	if model == nil {
+		log.Error("langchain model not found, falling back to legacy path", zap.String("model", v2.Model.Name))
+		return chatWithLegacy(chatCtx, ctx, v2, messages, placeholderMsg)
+	}
+
+	lcMessages := convertToLangchainMessages(systemPrompt, userPrompt, multiPartContent, imageURL)
+
+	ap := newAgentProcessor(chatCtx, ctx, model, v2, lcMessages, placeholderMsg)
+	response, err := ap.run()
+	if err != nil {
+		log.Error("agent execution failed", zap.Error(err))
+		if placeholderMsg != nil {
+			_, editErr := util.EditMessageWithError(placeholderMsg, v2.GetErrorMessage(), tb.ModeMarkdownV2)
+			if editErr != nil {
+				log.Error("Failed to edit placeholder with error", zap.Error(editErr))
+			}
+		}
+		return err
+	}
+
+	// Process outgoing filters
+	for _, filterConfig := range v2.Filters.Filters {
+		filter := createFilter(&filterConfig)
+		if filter == nil {
+			continue
+		}
+		response = filter.ProcessOutgoing(response, ctx, v2)
+	}
+
+	log.Debug("Agent chat response", zap.String("response", response))
+	return nil
+}
+
+// chatWithLegacy executes the chat using the legacy direct OpenAI SDK path.
+func chatWithLegacy(
+	chatCtx context.Context, ctx tb.Context, v2 *config.ChatConfigSingle,
+	messages []openai.ChatCompletionMessage, placeholderMsg *tb.Message,
+) error {
+	client := clients[v2.Model.Name]
 	useMcp := v2.UseMcpo && config.BotConfig.McpoServer.Enable
+	useInternalTools := v2.UseInternalTools
 
 	request := openai.ChatCompletionRequest{
 		Model:           v2.Model.Model,
 		Messages:        messages,
 		Temperature:     v2.GetTemperature(),
-		Stream:          true, // Enable streaming
+		Stream:          true,
 		ReasoningEffort: v2.ReasoningEffort,
 	}
-	if useMcp {
-		request.Tools = mcpo.GetToolSet("")
+
+	// Add tools to request
+	var allTools []openai.Tool
+	if useInternalTools {
+		allTools = append(allTools, GetInternalToolDefinitions()...)
+	}
+	if useMcp && mcpo != nil {
+		allTools = append(allTools, mcpo.GetToolSet("")...)
+	}
+	if len(allTools) > 0 {
+		request.Tools = allTools
 	}
 
-	// Create a streaming response
 	stream, err := client.CreateChatCompletionStream(chatCtx, request)
 	if err != nil {
 		log.Error("Failed to create chat completion stream", zap.Error(err))
-		// 如果使用了placeholder且出现错误，更新placeholder消息为错误提示
 		if placeholderMsg != nil {
 			_, editErr := util.EditMessageWithError(placeholderMsg, v2.GetErrorMessage(), tb.ModeMarkdownV2)
 			if editErr != nil {
@@ -327,8 +397,7 @@ final:
 		return err
 	}
 
-	// Process the streaming response using streamProcessor
-	processor := newStreamProcessor(chatCtx, ctx, placeholderMsg, useMcp, &request, &messages, v2)
+	processor := newStreamProcessor(chatCtx, ctx, placeholderMsg, useMcp || useInternalTools, &request, &messages, v2)
 	response, err := processor.process(stream)
 	if err != nil {
 		log.Error("Failed to process streaming response", zap.Error(err))
@@ -341,7 +410,7 @@ final:
 		return err
 	}
 
-	// 处理过滤器的Outgoing
+	// Process outgoing filters
 	for _, filterConfig := range v2.Filters.Filters {
 		filter := createFilter(&filterConfig)
 		if filter == nil {
@@ -352,7 +421,6 @@ final:
 
 	log.Debug("Chat response", zap.String("response", response))
 	return nil
-
 }
 
 var extractReasonPatt = regexp.MustCompile(`(?si)^\s*<think>\s*(?P<reason>.*?)(?:\s*</think>|$)\s*`)

chat/chat_input_test.go

@@ -0,0 +1,42 @@
+package chat
+
+import (
+	"testing"
+
+	"csust-got/config"
+
+	"github.com/stretchr/testify/assert"
+	tb "gopkg.in/telebot.v3"
+)
+
+func TestExtractInputFromMessage_RemovesCommandPrefix(t *testing.T) {
+	trigger := &config.ChatTrigger{Command: "think"}
+	tests := []struct {
+		name string
+		msg  *tb.Message
+		want string
+	}{
+		{
+			name: "plain command prefix stripped",
+			msg:  &tb.Message{Text: "/think hello world"},
+			want: "hello world",
+		},
+		{
+			name: "command with bot mention stripped",
+			msg:  &tb.Message{Text: "/think@bot hello world"},
+			want: "hello world",
+		},
+		{
+			name: "no command prefix kept",
+			msg:  &tb.Message{Text: "hello world"},
+			want: "hello world",
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			got := extractInputFromMessage(tt.msg, trigger)
+			assert.Equal(t, tt.want, got)
+		})
+	}
+}