feat: LLM 调用日志 + ModelSelector 优化 + devtools.bat 编码修复

- 新增 call_log.go: 全局环形缓冲区记录每次 LLM 调用(模型/Token/耗时/错误)
- OpenAIProvider.doChat/ChatStreamWithTools 自动记录调用日志
- ai-core 暴露 GET /api/v1/llm-calls 端点, DevTools 代理 + UI 面板
- ModelSelector.envProvider 改为单例缓存, 避免重复创建 HTTP Client
- 新增 PurposeToolCalling 适配器, 后台思考工具调用走专用路由
- envFallback 超时 120s→180s, 显式设置 MaxRetries
- devtools.bat 全英文, 解决 Windows CMD GBK 编码乱码问题

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend/ai-core/internal/llm/openai.go

@@ -139,14 +139,38 @@ func (p *OpenAIProvider) ChatStreamWithTools(ctx context.Context, messages []mod
 	go func() {
 		defer close(ch)
 
+		startTime := time.Now()
+		modelName := p.config.Model
+		var streamErr error
+		var finalUsage *model.Usage
+
+		defer func() {
+			r := CallRecord{
+				Model:    modelName,
+				Duration: time.Since(startTime),
+				Success:  streamErr == nil,
+			}
+			if streamErr != nil {
+				r.Error = streamErr.Error()
+			}
+			if finalUsage != nil {
+				r.PromptTokens = finalUsage.PromptTokens
+				r.CompletionTokens = finalUsage.CompletionTokens
+				r.TotalTokens = finalUsage.TotalTokens
+			}
+			LogCall(r)
+		}()
+
 		resp, err := p.doChatStream(ctx, messages, p.config.Model, tools)
 		if err != nil {
 			// Fallback
 			if p.config.FallbackModel != "" {
 				logger.Printf("[LLM] 流式调用主模型失败，降级: %v", err)
+				modelName = p.config.FallbackModel
 				resp, err = p.doChatStream(ctx, messages, p.config.FallbackModel, tools)
 			}
 			if err != nil {
+				streamErr = err
 				ch <- StreamChunk{Error: err, Done: true}
 				return
 			}
@@ -184,20 +208,22 @@ func (p *OpenAIProvider) ChatStreamWithTools(ctx context.Context, messages []mod
 					ch <- StreamChunk{Content: deltaStr}
 				}
 				if streamResp.Choices[0].FinishReason != "" {
-					usage := &model.Usage{}
 					if streamResp.Usage != nil {
-						usage.PromptTokens = streamResp.Usage.PromptTokens
-						usage.CompletionTokens = streamResp.Usage.CompletionTokens
-						usage.TotalTokens = streamResp.Usage.TotalTokens
+						finalUsage = &model.Usage{
+							PromptTokens:     streamResp.Usage.PromptTokens,
+							CompletionTokens: streamResp.Usage.CompletionTokens,
+							TotalTokens:      streamResp.Usage.TotalTokens,
+						}
 					}
-					ch <- StreamChunk{Done: true, Usage: usage}
+					ch <- StreamChunk{Done: true, Usage: finalUsage}
 					return
 				}
 			}
 		}
 
 		if err := scanner.Err(); err != nil {
-			ch <- StreamChunk{Error: fmt.Errorf("读取流式响应失败: %w", err), Done: true}
+			streamErr = fmt.Errorf("读取流式响应失败: %w", err)
+			ch <- StreamChunk{Error: streamErr, Done: true}
 			return
 		}
 
@@ -222,7 +248,25 @@ type openAIStreamChoice struct {
 }
 
 // doChat 执行同步对话请求
-func (p *OpenAIProvider) doChat(ctx context.Context, messages []model.LLMMessage, modelName string, stream bool, tools []OpenAITool) (*model.LLMResponse, error) {
+func (p *OpenAIProvider) doChat(ctx context.Context, messages []model.LLMMessage, modelName string, stream bool, tools []OpenAITool) (llmResp *model.LLMResponse, err error) {
+	startTime := time.Now()
+	defer func() {
+		r := CallRecord{
+			Model:    modelName,
+			Duration: time.Since(startTime),
+			Success:  err == nil,
+		}
+		if err != nil {
+			r.Error = err.Error()
+		}
+		if llmResp != nil {
+			r.PromptTokens = llmResp.Usage.PromptTokens
+			r.CompletionTokens = llmResp.Usage.CompletionTokens
+			r.TotalTokens = llmResp.Usage.TotalTokens
+		}
+		LogCall(r)
+	}()
+
 	// 转换消息格式
 	oaiMessages := make([]openAIMessage, len(messages))
 	for i, msg := range messages {
@@ -304,7 +348,7 @@ func (p *OpenAIProvider) doChat(ctx context.Context, messages []model.LLMMessage
 
 	// 检查是否有工具调用
 	choice := oaiResp.Choices[0]
-	llmResp := &model.LLMResponse{
+	llmResp = &model.LLMResponse{
 		Content:          contentString(choice.Message.Content),
 		FinishReason:     choice.FinishReason,
 		ReasoningContent: choice.Message.ReasoningContent,