🐛 fix(ai/query-editor/mac-window): 修复模型兼容性并优化即时执行与窗口交互

- AI 兼容性：为 Anthropic Provider 补齐 tools/tool_use/tool_result 协议转换，支持工具调用与流式工具结果解析
- 降级策略：OpenAI 兼容接口在 tools 请求返回 400/422/404 时自动回退为纯文本模式
- 配置修复：调整 MiniMax 预设为 Anthropic 兼容端点并更新默认模型列表
- 状态隔离：AI 聊天面板停止将动态模型列表写回供应商配置，避免污染静态 models 数据
- 编辑器修复：QueryEditor 在 runImmediately 场景下避免重复追加 SQL，改为直接选中并执行
- 交互优化：修复 macOS 原生窗口控制切换与标题栏点击行为，避免窗口按钮状态异常

frontend/src/App.tsx

@@ -1215,9 +1215,6 @@ function App() {
       if (target?.closest('[data-no-titlebar-toggle="true"]')) {
           return;
       }
-      if (useNativeMacWindowControls) {
-          return;
-      }
       void handleTitleBarWindowToggle();
   };
   

frontend/src/components/AIChatPanel.tsx

@@ -333,21 +333,8 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
         }
     }, [activeProvider?.id]);
 
-    useEffect(() => {
+
-        if (activeProvider && dynamicModels.length > 0) {
+    // dynamicModels 仅在内存中使用，不再写回供应商配置，避免污染静态 models 列表
-            const currentModels = activeProvider.models || [];
-            if (JSON.stringify(currentModels) !== JSON.stringify(dynamicModels)) {
-                try {
-                    const Service = (window as any).go?.aiservice?.Service;
-                    const payload = { ...activeProvider, models: dynamicModels };
-                    Service?.AISaveProvider?.(payload);
-                    setActiveProvider(payload);
-                } catch (e) {
-                    console.warn('Failed to cache models', e);
-                }
-            }
-        }
-    }, [activeProvider, dynamicModels]);
 
     const fetchDynamicModels = useCallback(async () => {
         try {

frontend/src/components/AISettingsModal.tsx

@@ -34,7 +34,7 @@ const PROVIDER_PRESETS: ProviderPreset[] = [
     { key: 'anthropic', label: 'Claude', icon: <ExperimentOutlined />, desc: 'Claude Opus/Sonnet 4.6', color: '#d97706', backendType: 'anthropic', defaultBaseUrl: 'https://api.anthropic.com', defaultModel: 'claude-sonnet-4-6', models: ['claude-opus-4-6', 'claude-sonnet-4-6'] },
     { key: 'gemini', label: 'Gemini', icon: <CloudOutlined />, desc: 'Gemini 3.1 / 2.5 系列', color: '#059669', backendType: 'gemini', defaultBaseUrl: 'https://generativelanguage.googleapis.com', defaultModel: 'gemini-2.5-flash', models: ['gemini-3.1-pro', 'gemini-2.5-flash', 'gemini-2.5-pro'] },
     { key: 'volcengine', label: '火山引擎', icon: <CloudOutlined />, desc: '火山方舟 / 豆包大模型', color: '#0ea5e9', backendType: 'openai', defaultBaseUrl: 'https://ark.cn-beijing.volces.com/api/v3', defaultModel: 'ep-xxxxxx', models: [] },
-    { key: 'minimax', label: 'MiniMax', icon: <ExperimentOutlined />, desc: 'abab6.5 / abab7 系列', color: '#e11d48', backendType: 'openai', defaultBaseUrl: 'https://api.minimax.chat/v1', defaultModel: 'abab7-chat-preview', models: ['abab7-chat-preview', 'abab6.5-chat', 'abab6.5g-chat'] },
+    { key: 'minimax', label: 'MiniMax', icon: <ExperimentOutlined />, desc: 'abab6.5 / abab7 系列', color: '#e11d48', backendType: 'anthropic', defaultBaseUrl: 'https://api.minimaxi.com/anthropic', defaultModel: 'MiniMax-Text-01', models: ['MiniMax-Text-01', 'MiniMax-Text-01-vision', 'MiniMax-Text-01-search', 'MiniMax-Text-01-code', 'MiniMax-Text-01-web', 'MiniMax-Text-01-sql', 'MiniMax-Text-01-python', 'MiniMax-Text-01-math', 'MiniMax-Text-01-doc'] },
     { key: 'ollama', label: 'Ollama', icon: <AppstoreOutlined />, desc: '本地部署开源模型', color: '#78716c', backendType: 'openai', defaultBaseUrl: 'http://localhost:11434/v1', defaultModel: 'llama3', models: [] },
     { key: 'custom', label: '自定义', icon: <AppstoreOutlined />, desc: '自定义 API 端点', color: '#64748b', backendType: 'custom', defaultBaseUrl: '', defaultModel: '', models: [] },
 ];

frontend/src/components/QueryEditor.tsx

@@ -2040,11 +2040,25 @@ const QueryEditor: React.FC<{ tab: TabData }> = ({ tab }) => {
               setCurrentDb(dbName);
           }
 
+
           const editor = editorRef.current;
           const monaco = monacoRef.current;
           if (editor && monaco) {
-              let position = editor.getPosition();
               const model = editor.getModel();
+              const existingContent = editor.getValue?.() || '';
+
+              // runImmediately 模式下，如果编辑器内容已是待注入的 SQL（TabManager 创建时已传入），
+              // 跳过追加，直接选中全部内容并执行
+              if (e.detail.runImmediately && existingContent.trim() === sqlText.trim()) {
+                  if (model) {
+                      const lineCount = model.getLineCount();
+                      const maxCol = model.getLineMaxColumn(lineCount);
+                      editor.setSelection(new monaco.Range(1, 1, lineCount, maxCol));
+                      editor.focus();
+                      setTimeout(() => handleRun(), 500);
+                  }
+              } else {
+              let position = editor.getPosition();
               if (!position && model) {
                   const lineCount = model.getLineCount();
                   const maxCol = model.getLineMaxColumn(lineCount);
@@ -2081,6 +2095,7 @@ const QueryEditor: React.FC<{ tab: TabData }> = ({ tab }) => {
                       setTimeout(() => handleRun(), 500);
                   }
               }
+              }
           } else {
               setQuery((prev: string) => prev ? prev + '\n' + sqlText : sqlText);
               message.success('代码已追加');

frontend/src/components/TabManager.tsx

@@ -151,7 +151,7 @@ const TabManager: React.FC = () => {
             id: newTabId,
             type: 'query',
             title: '新建查询',
-            query: '',
+            query: sql,
             connectionId: resolvedConnId,
             dbName: resolvedDbName
         });

internal/ai/provider/anthropic.go

@@ -72,13 +72,23 @@ func (p *AnthropicProvider) Validate() error {
 	return nil
 }
 
+// --- 请求体类型 ---
+
 type anthropicRequest struct {
-	Model       string             `json:"model"`
+	Model       string              `json:"model"`
-	Messages    []anthropicMessage `json:"messages"`
+	Messages    []anthropicMessage  `json:"messages"`
-	System      string             `json:"system,omitempty"`
+	System      string              `json:"system,omitempty"`
-	MaxTokens   int                `json:"max_tokens"`
+	MaxTokens   int                 `json:"max_tokens"`
-	Temperature float64            `json:"temperature,omitempty"`
+	Temperature float64             `json:"temperature,omitempty"`
-	Stream      bool               `json:"stream,omitempty"`
+	Stream      bool                `json:"stream,omitempty"`
+	Tools       []anthropicTool     `json:"tools,omitempty"`
+}
+
+// anthropicTool Anthropic 格式的工具定义
+type anthropicTool struct {
+	Name        string `json:"name"`
+	Description string `json:"description,omitempty"`
+	InputSchema any    `json:"input_schema"`
 }
 
 type anthropicMessage struct {
@@ -86,9 +96,66 @@ type anthropicMessage struct {
 	Content interface{} `json:"content"`
 }
 
+// convertToolsToAnthropic 将 OpenAI 格式的 tools 转换为 Anthropic 格式
+func convertToolsToAnthropic(tools []ai.Tool) []anthropicTool {
+	if len(tools) == 0 {
+		return nil
+	}
+	result := make([]anthropicTool, 0, len(tools))
+	for _, t := range tools {
+		result = append(result, anthropicTool{
+			Name:        t.Function.Name,
+			Description: t.Function.Description,
+			InputSchema: t.Function.Parameters,
+		})
+	}
+	return result
+}
+
 func buildAnthropicMessages(reqMessages []ai.Message) []anthropicMessage {
 	messages := make([]anthropicMessage, 0, len(reqMessages))
 	for _, m := range reqMessages {
+		// tool result 消息：转换为 Anthropic 的 tool_result content block
+		if m.Role == "tool" {
+			messages = append(messages, anthropicMessage{
+				Role: "user",
+				Content: []map[string]interface{}{
+					{
+						"type":        "tool_result",
+						"tool_use_id": m.ToolCallID,
+						"content":     m.Content,
+					},
+				},
+			})
+			continue
+		}
+
+		// assistant 带 tool_calls：转换为 Anthropic 的 tool_use content block
+		if m.Role == "assistant" && len(m.ToolCalls) > 0 {
+			var contentParts []map[string]interface{}
+			if m.Content != "" {
+				contentParts = append(contentParts, map[string]interface{}{
+					"type": "text",
+					"text": m.Content,
+				})
+			}
+			for _, tc := range m.ToolCalls {
+				var input interface{}
+				if err := json.Unmarshal([]byte(tc.Function.Arguments), &input); err != nil {
+					input = map[string]interface{}{}
+				}
+				contentParts = append(contentParts, map[string]interface{}{
+					"type":  "tool_use",
+					"id":    tc.ID,
+					"name":  tc.Function.Name,
+					"input": input,
+				})
+			}
+			messages = append(messages, anthropicMessage{Role: "assistant", Content: contentParts})
+			continue
+		}
+
+		// 图片消息
 		if len(m.Images) > 0 {
 			var contentParts []map[string]interface{}
 			for _, img := range m.Images {
@@ -106,7 +173,7 @@ func buildAnthropicMessages(reqMessages []ai.Message) []anthropicMessage {
 			}
 			text := m.Content
 			if text == "" {
-				text = "请描述和分析这张图片。" // 防止强 System Prompt 下模型仅看到空文本且忽略图片直接回复打招呼
+				text = "请描述和分析这张图片。"
 			}
 			contentParts = append(contentParts, map[string]interface{}{
 				"type": "text",
@@ -120,11 +187,19 @@ func buildAnthropicMessages(reqMessages []ai.Message) []anthropicMessage {
 	return messages
 }
 
+// --- 响应体类型 ---
+
+type anthropicContentBlock struct {
+	Type  string          `json:"type"` // "text" | "tool_use"
+	Text  string          `json:"text,omitempty"`
+	ID    string          `json:"id,omitempty"`    // tool_use
+	Name  string          `json:"name,omitempty"`  // tool_use
+	Input json.RawMessage `json:"input,omitempty"` // tool_use
+}
+
 type anthropicResponse struct {
-	Content []struct {
+	Content []anthropicContentBlock `json:"content"`
-		Text string `json:"text"`
+	Usage   struct {
-	} `json:"content"`
-	Usage struct {
 		InputTokens  int `json:"input_tokens"`
 		OutputTokens int `json:"output_tokens"`
 	} `json:"usage"`
@@ -133,13 +208,20 @@ type anthropicResponse struct {
 	} `json:"error,omitempty"`
 }
 
+// 流式事件类型
 type anthropicStreamEvent struct {
-	Type  string `json:"type"`
+	Type         string                 `json:"type"`
-	Delta *struct {
+	Index        int                    `json:"index,omitempty"`
-		Text string `json:"text"`
+	ContentBlock *anthropicContentBlock `json:"content_block,omitempty"`
+	Delta        *struct {
+		Type        string `json:"type,omitempty"`
+		Text        string `json:"text,omitempty"`
+		PartialJSON string `json:"partial_json,omitempty"`
 	} `json:"delta,omitempty"`
 }
 
+// --- Chat 非流式 ---
+
 func (p *AnthropicProvider) Chat(ctx context.Context, req ai.ChatRequest) (*ai.ChatResponse, error) {
 	if err := p.Validate(); err != nil {
 		return nil, err
@@ -163,6 +245,7 @@ func (p *AnthropicProvider) Chat(ctx context.Context, req ai.ChatRequest) (*ai.C
 		System:      systemMsg,
 		MaxTokens:   maxTokens,
 		Temperature: temperature,
+		Tools:       convertToolsToAnthropic(req.Tools),
 	}
 
 	respBody, err := p.doRequest(ctx, body)
@@ -182,8 +265,35 @@ func (p *AnthropicProvider) Chat(ctx context.Context, req ai.ChatRequest) (*ai.C
 		return nil, fmt.Errorf("Anthropic 返回空响应")
 	}
 
+	// 解析响应中的 text 和 tool_use content blocks
+	var textContent string
+	var toolCalls []ai.ToolCall
+	for _, block := range result.Content {
+		switch block.Type {
+		case "text":
+			textContent += block.Text
+		case "tool_use":
+			argsStr := "{}"
+			if len(block.Input) > 0 {
+				argsStr = string(block.Input)
+			}
+			toolCalls = append(toolCalls, ai.ToolCall{
+				ID:   block.ID,
+				Type: "function",
+				Function: struct {
+					Name      string `json:"name"`
+					Arguments string `json:"arguments"`
+				}{
+					Name:      block.Name,
+					Arguments: argsStr,
+				},
+			})
+		}
+	}
+
 	return &ai.ChatResponse{
-		Content: result.Content[0].Text,
+		Content:   textContent,
+		ToolCalls: toolCalls,
 		TokensUsed: ai.TokenUsage{
 			PromptTokens:     result.Usage.InputTokens,
 			CompletionTokens: result.Usage.OutputTokens,
@@ -192,6 +302,8 @@ func (p *AnthropicProvider) Chat(ctx context.Context, req ai.ChatRequest) (*ai.C
 	}, nil
 }
 
+// --- ChatStream 流式 ---
+
 func (p *AnthropicProvider) ChatStream(ctx context.Context, req ai.ChatRequest, callback func(ai.StreamChunk)) error {
 	if err := p.Validate(); err != nil {
 		return err
@@ -216,6 +328,7 @@ func (p *AnthropicProvider) ChatStream(ctx context.Context, req ai.ChatRequest,
 		MaxTokens:   maxTokens,
 		Temperature: temperature,
 		Stream:      true,
+		Tools:       convertToolsToAnthropic(req.Tools),
 	}
 
 	respBody, err := p.doRequest(ctx, body)
@@ -224,6 +337,14 @@ func (p *AnthropicProvider) ChatStream(ctx context.Context, req ai.ChatRequest,
 	}
 	defer respBody.Close()
 
+	// 跟踪当前活跃的 tool_use blocks
+	type activeToolUse struct {
+		id        string
+		name      string
+		argsJSON  strings.Builder
+	}
+	activeBlocks := make(map[int]*activeToolUse) // index -> block
+
 	scanner := bufio.NewScanner(respBody)
 	for scanner.Scan() {
 		line := scanner.Text()
@@ -238,10 +359,54 @@ func (p *AnthropicProvider) ChatStream(ctx context.Context, req ai.ChatRequest,
 		}
 
 		switch event.Type {
-		case "content_block_delta":
+		case "content_block_start":
-			if event.Delta != nil && event.Delta.Text != "" {
+			if event.ContentBlock != nil && event.ContentBlock.Type == "tool_use" {
-				callback(ai.StreamChunk{Content: event.Delta.Text})
+				activeBlocks[event.Index] = &activeToolUse{
+					id:   event.ContentBlock.ID,
+					name: event.ContentBlock.Name,
+				}
 			}
+
+		case "content_block_delta":
+			if event.Delta == nil {
+				continue
+			}
+			switch event.Delta.Type {
+			case "text_delta":
+				if event.Delta.Text != "" {
+					callback(ai.StreamChunk{Content: event.Delta.Text})
+				}
+			case "input_json_delta":
+				if block, ok := activeBlocks[event.Index]; ok {
+					block.argsJSON.WriteString(event.Delta.PartialJSON)
+				}
+			}
+
+		case "content_block_stop":
+			if block, ok := activeBlocks[event.Index]; ok {
+				argsStr := block.argsJSON.String()
+				if argsStr == "" {
+					argsStr = "{}"
+				}
+				// 产出完整的 tool call
+				callback(ai.StreamChunk{
+					ToolCalls: []ai.ToolCall{
+						{
+							ID:   block.id,
+							Type: "function",
+							Function: struct {
+								Name      string `json:"name"`
+								Arguments string `json:"arguments"`
+							}{
+								Name:      block.name,
+								Arguments: argsStr,
+							},
+						},
+					},
+				})
+				delete(activeBlocks, event.Index)
+			}
+
 		case "message_stop":
 			callback(ai.StreamChunk{Done: true})
 			return nil
@@ -252,6 +417,8 @@ func (p *AnthropicProvider) ChatStream(ctx context.Context, req ai.ChatRequest,
 	return scanner.Err()
 }
 
+// --- HTTP 请求 ---
+
 func (p *AnthropicProvider) doRequest(ctx context.Context, body interface{}) (io.ReadCloser, error) {
 	jsonBody, err := json.Marshal(body)
 	if err != nil {
@@ -263,15 +430,6 @@ func (p *AnthropicProvider) doRequest(ctx context.Context, body interface{}) (io
 		url = p.baseURL + "/messages"
 	}
 
-	// 调试日志：打印实际请求信息
-	bodyStr := string(jsonBody)
-	if len(bodyStr) > 500 {
-		bodyStr = bodyStr[:500] + "..."
-	}
-	fmt.Printf("[Anthropic DEBUG] URL: %s\n", url)
-	fmt.Printf("[Anthropic DEBUG] BaseURL: %s\n", p.baseURL)
-	fmt.Printf("[Anthropic DEBUG] Body: %s\n", bodyStr)
-
 	httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, url, bytes.NewReader(jsonBody))
 	if err != nil {
 		return nil, fmt.Errorf("创建 HTTP 请求失败: %w", err)

internal/ai/provider/openai.go

@@ -209,7 +209,17 @@ func (p *OpenAIProvider) Chat(ctx context.Context, req ai.ChatRequest) (*ai.Chat
 
 	respBody, err := p.doRequest(ctx, body)
 	if err != nil {
-		return nil, err
+		// 当带 tools 的请求返回 400 时，自动降级为不带 tools 的纯文本请求
+		if len(req.Tools) > 0 && isHTTP400Error(err) {
+			fmt.Println("[OpenAI] 模型不支持 Function Calling，自动降级为纯文本模式")
+			body.Tools = nil
+			respBody, err = p.doRequest(ctx, body)
+			if err != nil {
+				return nil, err
+			}
+		} else {
+			return nil, err
+		}
 	}
 	defer respBody.Close()
 
@@ -257,7 +267,17 @@ func (p *OpenAIProvider) ChatStream(ctx context.Context, req ai.ChatRequest, cal
 
 	respBody, err := p.doRequest(ctx, body)
 	if err != nil {
-		return err
+		// 当带 tools 的请求返回 400 时，自动降级为不带 tools 的纯文本请求
+		if len(req.Tools) > 0 && isHTTP400Error(err) {
+			fmt.Println("[OpenAI] 模型不支持 Function Calling，自动降级为纯文本模式")
+			body.Tools = nil
+			respBody, err = p.doRequest(ctx, body)
+			if err != nil {
+				return err
+			}
+		} else {
+			return err
+		}
 	}
 	defer respBody.Close()
 
@@ -366,14 +386,7 @@ func (p *OpenAIProvider) doRequest(ctx context.Context, body interface{}) (io.Re
 
 	url := p.baseURL + "/chat/completions"
 
-	// 调试日志
+
-	bodyStr := string(jsonBody)
-	if len(bodyStr) > 500 {
-		bodyStr = bodyStr[:500] + "..."
-	}
-	fmt.Printf("[OpenAI DEBUG] URL: %s\n", url)
-	fmt.Printf("[OpenAI DEBUG] BaseURL: %s\n", p.baseURL)
-	fmt.Printf("[OpenAI DEBUG] Body: %s\n", bodyStr)
 
 	httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, url, bytes.NewReader(jsonBody))
 	if err != nil {
@@ -408,3 +421,15 @@ func (p *OpenAIProvider) doRequest(ctx context.Context, body interface{}) (io.Re
 
 	return resp.Body, nil
 }
+
+// isHTTP400Error 检查错误是否为 HTTP 4xx 客户端错误（400/422 等），
+// 通常表示模型不支持请求中的某些参数（如 tools/functions）。
+func isHTTP400Error(err error) bool {
+	if err == nil {
+		return false
+	}
+	msg := err.Error()
+	return strings.Contains(msg, "(HTTP 400)") ||
+		strings.Contains(msg, "(HTTP 422)") ||
+		strings.Contains(msg, "(HTTP 404)")
+}

internal/app/window_style_darwin.go

@@ -8,6 +8,9 @@ package app
 #import <Cocoa/Cocoa.h>
 #import <dispatch/dispatch.h>
 
+static inline BOOL gonaviBoolYES() { return YES; }
+static inline BOOL gonaviBoolNO()  { return NO; }
+
 static void gonaviSetWindowButtonsVisible(NSWindow *window, BOOL visible) {
 	if (window == nil) {
 		return;
@@ -62,9 +65,9 @@ import "C"
 
 func setMacNativeWindowControls(enabled bool) {
 	state := resolveMacNativeWindowControlState(enabled)
-	flag := C.BOOL(false)
 	if state.ShowNativeButtons {
-		flag = C.BOOL(true)
+		C.gonaviApplyMacWindowStyle(C.gonaviBoolYES())
+	} else {
+		C.gonaviApplyMacWindowStyle(C.gonaviBoolNO())
 	}
-	C.gonaviApplyMacWindowStyle(flag)
 }