🐛 fix(ai): 兼容 DeepSeek reasoning 内容响应

- 增加 reasoning_content 字段解析与前后端类型定义 - 兼容 DeepSeek 流式和非流式响应中的推理内容 - 统一 AI 消息 payload 映射，避免历史消息丢失推理内容 - 补充 OpenAI 兼容 Provider 与前端消息映射测试
2026-05-06 20:03:05 +08:00 · 2026-04-30 17:26:36 +08:00
parent d2dad75167
commit 5f9adcac37
9 changed files with 283 additions and 60 deletions
--- a/frontend/src/components/AIChatPanel.tsx
+++ b/frontend/src/components/AIChatPanel.tsx
@@ -28,6 +28,7 @@ import {
 import { buildAIReadonlyPreviewSQL } from '../utils/aiSqlLimit';
 import { resolveAITableSchemaToolResult } from '../utils/aiTableSchemaTool';
 import { consumeAIChatSendShortcutOnKeyDown } from '../utils/aiChatSendShortcut';
+import { toAIRequestMessage } from '../utils/aiMessagePayload';

 interface AIChatPanelProps {
    width?: number;
@@ -74,7 +75,7 @@ export const getDynamicMaxContextChars = (modelName?: string) => {
 // 当超出指定字符上限时触发上下文自建压缩
 const compressContextIfNeeded = async (sid: string, messagesPayload: any[], maxLimit: number) => {
    try {
-        const chars = messagesPayload.reduce((sum, m) => sum + (m.content?.length || 0) + JSON.stringify(m.tool_calls || []).length, 0);
+        const chars = messagesPayload.reduce((sum, m) => sum + (m.content?.length || 0) + (m.reasoning_content?.length || 0) + JSON.stringify(m.tool_calls || []).length, 0);
        if (chars < maxLimit) return null;

        const Service = (window as any).go?.aiservice?.Service;
@@ -508,7 +509,7 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
        let isFirstCompletion = false;

        // 新增：利用 requestAnimationFrame 缓冲高频事件，避免 React 重绘阻塞导致感官吞吐变慢
-        const streamBuffer = { thinking: '', content: '' };
+        const streamBuffer = { thinking: '', reasoningContent: '', content: '' };
        let flushPending = false;

        const flushStreamBuffer = () => {
@@ -523,6 +524,10 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
                updates.phase = 'thinking';
                streamBuffer.thinking = '';
            }
+            if (streamBuffer.reasoningContent) {
+                updates.reasoning_content = (existing.reasoning_content || '') + streamBuffer.reasoningContent;
+                streamBuffer.reasoningContent = '';
+            }
            if (streamBuffer.content) {
                updates.content = (existing.content || '') + streamBuffer.content;
                updates.phase = 'generating';
@@ -535,7 +540,7 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
            flushPending = false;
        };

-        const handler = (data: { content?: string; thinking?: string; tool_calls?: AIToolCall[]; done?: boolean; error?: string }) => {
+        const handler = (data: { content?: string; thinking?: string; reasoning_content?: string; tool_calls?: AIToolCall[]; done?: boolean; error?: string }) => {
            // Find connecting message if there's no active assistant string
            if (!assistantMsgId) {
                const history = useStore.getState().aiChatHistory[sid] || [];
@@ -589,7 +594,8 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
            }

            // 处理 thinking（模型思考过程）
-            if (data.thinking) {
+            const displayThinking = data.thinking || data.reasoning_content || '';
+            if (displayThinking || data.reasoning_content) {
                if (!assistantMsgId) {
                    assistantMsgId = genId();
                    addAIChatMessage(sid, {
@@ -597,7 +603,8 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
                        role: 'assistant',
                        phase: 'thinking',
                        content: '',
-                        thinking: data.thinking,
+                        thinking: displayThinking || undefined,
+                        reasoning_content: data.reasoning_content || undefined,
                        timestamp: Date.now(),
                        loading: true,
                        jvmPlanContext: pendingJVMPlanContextRef.current,
@@ -605,7 +612,10 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
                    });
                    if (sending) setSending(false);
                } else {
-                    streamBuffer.thinking += data.thinking;
+                    streamBuffer.thinking += displayThinking;
+                    if (data.reasoning_content) {
+                        streamBuffer.reasoningContent += data.reasoning_content;
+                    }
                    if (sending) setSending(false);
                }
            }
@@ -632,7 +642,7 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
                }
            }

-            if (streamBuffer.thinking || streamBuffer.content) {
+            if (streamBuffer.thinking || streamBuffer.reasoningContent || streamBuffer.content) {
                if (!flushPending) {
                    flushPending = true;
                    requestAnimationFrame(flushStreamBuffer);
@@ -641,7 +651,7 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({

            if (data.done) {
                // 如果有残留未 flush 的 buffer，立刻推入状态树
-                if (streamBuffer.thinking || streamBuffer.content) {
+                if (streamBuffer.thinking || streamBuffer.reasoningContent || streamBuffer.content) {
                    flushStreamBuffer();
                }
                const doneAssistantId = assistantMsgId;
@@ -676,12 +686,7 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
                            (async () => {
                                try {
                                    const currentHistory = useStore.getState().aiChatHistory[sid] || [];
-                                    const messagesPayload = currentHistory.map(m => {
-                                        const mapped: any = { role: m.role, content: m.content, images: m.images };
-                                        if (m.tool_calls) mapped.tool_calls = m.tool_calls;
-                                        if (m.tool_call_id) mapped.tool_call_id = m.tool_call_id;
-                                        return mapped;
-                                    });
+                                    const messagesPayload = currentHistory.map(toAIRequestMessage);
                                    const sysMessages = await buildSystemContextMessages(
                                        existing.jvmPlanContext,
                                        existing.jvmDiagnosticPlanContext,
@@ -804,7 +809,7 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
            addAIChatMessage(sid, connectingMsg);

            const truncatedHistory = historyLocal.slice(0, lastUserMsgIndex + 1);
-            const messagesPayload = truncatedHistory.map(m => ({ role: m.role, content: m.content, images: m.images }));
+            const messagesPayload = truncatedHistory.map(toAIRequestMessage);
            
            try {
                const sysMessages = await buildSystemContextMessages(
@@ -823,6 +828,8 @@ export const AIChatPanel: React.FC<AIChatPanelProps> = ({
                     addAIChatMessage(sid, {
                         id: genId(), role: 'assistant', 
                         content: result?.success ? result.content : `❌ ${errClean}`,
+                         thinking: result?.success ? result.reasoning_content : undefined,
+                         reasoning_content: result?.success ? result.reasoning_content : undefined,
                         rawError: (!result?.success && errClean !== errRaw) ? errRaw : undefined,
                         timestamp: Date.now(),
                         jvmPlanContext: retryJVMPlanContext,
@@ -1268,12 +1275,7 @@ SELECT * FROM users WHERE status = 1;
            setSending(true);
            const currentHistory = useStore.getState().aiChatHistory[sid] || [];
            // 过滤掉 connecting 占位消息，不发给模型
-            const messagesPayload = currentHistory.filter(m => m.phase !== 'connecting').map(m => {
-                const mapped: any = { role: m.role, content: m.content, images: m.images };
-                if (m.tool_calls) mapped.tool_calls = m.tool_calls;
-                if (m.tool_call_id) mapped.tool_call_id = m.tool_call_id;
-                return mapped;
-            });
+            const messagesPayload = currentHistory.filter(m => m.phase !== 'connecting').map(toAIRequestMessage);
            const sysMessages = await buildSystemContextMessages(
                inheritedJVMPlanContext,
                inheritedJVMDiagnosticPlanContext,
@@ -1313,6 +1315,8 @@ SELECT * FROM users WHERE status = 1;
                useStore.getState().addAIChatMessage(sid, {
                    id: genId(), role: 'assistant',
                    content: result?.success ? result.content : `❌ ${errC}`,
+                    thinking: result?.success ? result.reasoning_content : undefined,
+                    reasoning_content: result?.success ? result.reasoning_content : undefined,
                    rawError: (!result?.success && errC !== errR) ? errR : undefined,
                    timestamp: Date.now(),
                    jvmPlanContext: inheritedJVMPlanContext,
@@ -1380,12 +1384,7 @@ SELECT * FROM users WHERE status = 1;
        // 【过渡状态 2】上下文已组装完成，即将接入模型
        updateAIChatMessage(sid, connectingMsg.id, { content: '模型接入中' });

-        const chatMessages = [...messages, userMsg].map(m => {
-            const mapped: any = { role: m.role, content: m.content, images: m.images };
-            if (m.tool_calls) mapped.tool_calls = m.tool_calls;
-            if (m.tool_call_id) mapped.tool_call_id = m.tool_call_id;
-            return mapped;
-        });
+        const chatMessages = [...messages, userMsg].map(toAIRequestMessage);

        let finalMessagesPayload = chatMessages;
        const dynamicMaxLimit = getDynamicMaxContextChars(activeProvider?.model);
@@ -1421,6 +1420,8 @@ SELECT * FROM users WHERE status = 1;
                const assistantMsg: AIChatMessage = {
                    id: genId(), role: 'assistant',
                    content: result?.success ? result.content : `❌ ${errC2}`,
+                    thinking: result?.success ? result.reasoning_content : undefined,
+                    reasoning_content: result?.success ? result.reasoning_content : undefined,
                    rawError: (!result?.success && errC2 !== errR2) ? errR2 : undefined,
                    timestamp: Date.now(),
                    jvmPlanContext: currentJVMPlanContext,
@@ -1588,7 +1589,7 @@ SELECT * FROM users WHERE status = 1;
        return connection ? buildRpcConnectionConfig(connection.config) : undefined;
    }, [inferredConnectionId, connections]);
    const contextUsageChars = useMemo(() =>
-        messages.reduce((sum, m) => sum + (m.content?.length || 0) + JSON.stringify(m.tool_calls || []).length, 0),
+        messages.reduce((sum, m) => sum + (m.content?.length || 0) + (m.reasoning_content?.length || 0) + JSON.stringify(m.tool_calls || []).length, 0),
    [messages]);
    const contextTableNames = useMemo(() => {
        const ck = activeContext?.connectionId ? `${activeContext.connectionId}:${activeContext.dbName || ''}` : 'default';
--- a/frontend/src/types.ts
+++ b/frontend/src/types.ts
@@ -554,6 +554,7 @@ export interface AIChatMessage {
  phase?: ChatPhase;
  content: string;
  thinking?: string;
+  reasoning_content?: string;
  timestamp: number;
  loading?: boolean;
  images?: string[]; // base64 encoded images with data URI prefix
--- a/frontend/src/utils/aiMessagePayload.test.ts
+++ b/frontend/src/utils/aiMessagePayload.test.ts
@@ -0,0 +1,78 @@
+import { describe, expect, it } from 'vitest';
+import type { AIChatMessage, AIToolCall } from '../types';
+import { toAIRequestMessage } from './aiMessagePayload';
+
+const toolCall: AIToolCall = {
+  id: 'call_schema',
+  type: 'function',
+  function: {
+    name: 'inspect_table_schema',
+    arguments: '{"table":"orders"}',
+  },
+};
+
+const message = (overrides: Partial<AIChatMessage>): AIChatMessage => ({
+  id: 'msg-1',
+  role: 'assistant',
+  content: '',
+  timestamp: 1,
+  ...overrides,
+});
+
+describe('toAIRequestMessage', () => {
+  it('keeps reasoning_content on assistant tool-call messages', () => {
+    const payload = toAIRequestMessage(message({
+      tool_calls: [toolCall],
+      reasoning_content: '需要先检查表结构',
+    }));
+
+    expect(payload).toMatchObject({
+      role: 'assistant',
+      tool_calls: [toolCall],
+      reasoning_content: '需要先检查表结构',
+    });
+  });
+
+  it('keeps reasoning_content on assistant messages without tool calls', () => {
+    const payload = toAIRequestMessage(message({
+      content: '最终分析',
+      reasoning_content: '工具调用轮次的最终思考也需要保留',
+    }));
+
+    expect(payload).toMatchObject({
+      role: 'assistant',
+      content: '最终分析',
+      reasoning_content: '工具调用轮次的最终思考也需要保留',
+    });
+  });
+
+  it('omits reasoning_content from tool result messages while keeping tool_call_id', () => {
+    const payload = toAIRequestMessage(message({
+      role: 'tool',
+      content: '{"ok":true}',
+      tool_call_id: 'call_schema',
+      reasoning_content: '不应回传',
+    }));
+
+    expect(payload).toMatchObject({
+      role: 'tool',
+      content: '{"ok":true}',
+      tool_call_id: 'call_schema',
+    });
+    expect(payload).not.toHaveProperty('reasoning_content');
+  });
+
+  it('keeps user images without adding empty tool fields', () => {
+    const payload = toAIRequestMessage(message({
+      role: 'user',
+      content: '看图',
+      images: ['data:image/png;base64,abc'],
+    }));
+
+    expect(payload).toEqual({
+      role: 'user',
+      content: '看图',
+      images: ['data:image/png;base64,abc'],
+    });
+  });
+});
--- a/frontend/src/utils/aiMessagePayload.ts
+++ b/frontend/src/utils/aiMessagePayload.ts
@@ -0,0 +1,32 @@
+import type { AIChatMessage, AIToolCall } from '../types';
+
+export interface AIRequestMessage {
+  role: AIChatMessage['role'];
+  content: string;
+  images?: string[];
+  tool_calls?: AIToolCall[];
+  tool_call_id?: string;
+  reasoning_content?: string;
+}
+
+export const toAIRequestMessage = (message: AIChatMessage): AIRequestMessage => {
+  const payload: AIRequestMessage = {
+    role: message.role,
+    content: message.content,
+  };
+
+  if (message.images && message.images.length > 0) {
+    payload.images = message.images;
+  }
+  if (message.tool_calls && message.tool_calls.length > 0) {
+    payload.tool_calls = message.tool_calls;
+  }
+  if (message.tool_call_id) {
+    payload.tool_call_id = message.tool_call_id;
+  }
+  if (message.role === 'assistant' && message.reasoning_content) {
+    payload.reasoning_content = message.reasoning_content;
+  }
+
+  return payload;
+};
--- a/frontend/wailsjs/go/models.ts
+++ b/frontend/wailsjs/go/models.ts
@@ -41,6 +41,7 @@ export namespace ai {
 	    images?: string[];
 	    tool_call_id?: string;
 	    tool_calls?: ToolCall[];
+	    reasoning_content?: string;
 	
 	    static createFrom(source: any = {}) {
 	        return new Message(source);
@@ -53,6 +54,7 @@ export namespace ai {
 	        this.images = source["images"];
 	        this.tool_call_id = source["tool_call_id"];
 	        this.tool_calls = this.convertValues(source["tool_calls"], ToolCall);
+	        this.reasoning_content = source["reasoning_content"];
 	    }
 	
 		convertValues(a: any, classs: any, asMap: boolean = false): any {
--- a/internal/ai/provider/openai.go
+++ b/internal/ai/provider/openai.go
@@ -84,21 +84,25 @@ type openAIChatRequest struct {
 }

 type openAIChatMessage struct {
-	Role       string        `json:"role"`
-	Content    interface{}   `json:"content,omitempty"`
-	ToolCalls  []ai.ToolCall `json:"tool_calls,omitempty"`
-	ToolCallID string        `json:"tool_call_id,omitempty"`
+	Role             string        `json:"role"`
+	Content          interface{}   `json:"content,omitempty"`
+	ToolCalls        []ai.ToolCall `json:"tool_calls,omitempty"`
+	ToolCallID       string        `json:"tool_call_id,omitempty"`
+	ReasoningContent string        `json:"reasoning_content,omitempty"`
 }

 func buildOpenAIMessages(reqMessages []ai.Message, modelName string, baseURL string) []openAIChatMessage {
 	messages := make([]openAIChatMessage, len(reqMessages))
+	replayReasoningContent := shouldReplayReasoningContent(modelName, baseURL)
 	for i, m := range reqMessages {
 		if m.Role == "tool" {
 			messages[i] = openAIChatMessage{Role: m.Role, Content: m.Content, ToolCallID: m.ToolCallID}
 			continue
 		}
 		if len(m.ToolCalls) > 0 {
-			messages[i] = openAIChatMessage{Role: m.Role, Content: m.Content, ToolCalls: m.ToolCalls}
+			msg := openAIChatMessage{Role: m.Role, Content: m.Content, ToolCalls: m.ToolCalls}
+			attachReasoningContent(&msg, m, replayReasoningContent)
+			messages[i] = msg
 			continue
 		}

@@ -127,20 +131,37 @@ func buildOpenAIMessages(reqMessages []ai.Message, modelName string, baseURL str
 					},
 				})
 			}
-			messages[i] = openAIChatMessage{Role: m.Role, Content: contentParts}
+			msg := openAIChatMessage{Role: m.Role, Content: contentParts}
+			attachReasoningContent(&msg, m, replayReasoningContent)
+			messages[i] = msg
 		} else {
-			messages[i] = openAIChatMessage{Role: m.Role, Content: m.Content}
+			msg := openAIChatMessage{Role: m.Role, Content: m.Content}
+			attachReasoningContent(&msg, m, replayReasoningContent)
+			messages[i] = msg
 		}
 	}
 	return messages
 }

+func attachReasoningContent(msg *openAIChatMessage, source ai.Message, enabled bool) {
+	if enabled && source.Role == "assistant" && source.ReasoningContent != "" {
+		msg.ReasoningContent = source.ReasoningContent
+	}
+}
+
+func shouldReplayReasoningContent(modelName string, baseURL string) bool {
+	model := strings.ToLower(strings.TrimSpace(modelName))
+	base := strings.ToLower(strings.TrimSpace(baseURL))
+	return strings.Contains(model, "deepseek") || strings.Contains(base, "deepseek")
+}
+
 // openAIChatResponse OpenAI API 响应体
 type openAIChatResponse struct {
 	Choices []struct {
 		Message struct {
-			Content   string        `json:"content"`
-			ToolCalls []ai.ToolCall `json:"tool_calls,omitempty"`
+			Content          string        `json:"content"`
+			ReasoningContent string        `json:"reasoning_content,omitempty"`
+			ToolCalls        []ai.ToolCall `json:"tool_calls,omitempty"`
 		} `json:"message"`
 		FinishReason string `json:"finish_reason"`
 	} `json:"choices"`
@@ -227,7 +248,8 @@ func (p *OpenAIProvider) Chat(ctx context.Context, req ai.ChatRequest) (*ai.Chat
 	}

 	return &ai.ChatResponse{
-		Content: result.Choices[0].Message.Content,
+		Content:          result.Choices[0].Message.Content,
+		ReasoningContent: result.Choices[0].Message.ReasoningContent,
 		TokensUsed: ai.TokenUsage{
 			PromptTokens:     result.Usage.PromptTokens,
 			CompletionTokens: result.Usage.CompletionTokens,
@@ -342,7 +364,10 @@ func (p *OpenAIProvider) ChatStream(ctx context.Context, req ai.ChatRequest, cal
 			// 支持 DeepSeek/千问等模型的 reasoning_content 字段
 			if choice.Delta.ReasoningContent != "" {
 				receivedContent = true
-				callback(ai.StreamChunk{Thinking: choice.Delta.ReasoningContent})
+				callback(ai.StreamChunk{
+					Thinking:         choice.Delta.ReasoningContent,
+					ReasoningContent: choice.Delta.ReasoningContent,
+				})
 			}

 			if choice.FinishReason != nil {
--- a/internal/ai/provider/openai_test.go
+++ b/internal/ai/provider/openai_test.go
@@ -2,6 +2,8 @@ package provider

 import (
 	"GoNavi-Wails/internal/ai"
+	"encoding/json"
+	"strings"
 	"testing"
 )

@@ -165,3 +167,80 @@ func TestOpenAIProvider_DefaultMaxTokens(t *testing.T) {
 		t.Fatalf("expected default max tokens 4096, got %d", op.config.MaxTokens)
 	}
 }
+
+func TestBuildOpenAIMessages_ReplaysDeepSeekReasoningContentForToolCalls(t *testing.T) {
+	toolCall := testOpenAIToolCall()
+	got := buildOpenAIMessages([]ai.Message{
+		{
+			Role:             "assistant",
+			Content:          "",
+			ToolCalls:        []ai.ToolCall{toolCall},
+			ReasoningContent: "需要先检查表结构",
+		},
+		{
+			Role:       "tool",
+			Content:    `{"ok":true}`,
+			ToolCallID: toolCall.ID,
+		},
+	}, "deepseek-v4", "https://api.deepseek.com/v1")
+
+	if got[0].ReasoningContent != "需要先检查表结构" {
+		t.Fatalf("expected reasoning_content to be replayed for DeepSeek tool call, got %q", got[0].ReasoningContent)
+	}
+	if got[1].ReasoningContent != "" {
+		t.Fatalf("expected tool result message not to carry reasoning_content, got %q", got[1].ReasoningContent)
+	}
+
+	body, err := json.Marshal(got[0])
+	if err != nil {
+		t.Fatalf("marshal message: %v", err)
+	}
+	if !strings.Contains(string(body), `"reasoning_content":"需要先检查表结构"`) {
+		t.Fatalf("expected JSON payload to include reasoning_content, got %s", body)
+	}
+}
+
+func TestBuildOpenAIMessages_OmitsReasoningContentForNonDeepSeekProviders(t *testing.T) {
+	got := buildOpenAIMessages([]ai.Message{
+		{
+			Role:             "assistant",
+			Content:          "",
+			ToolCalls:        []ai.ToolCall{testOpenAIToolCall()},
+			ReasoningContent: "reasoning should stay local",
+		},
+	}, "gpt-4o", "https://api.openai.com/v1")
+
+	if got[0].ReasoningContent != "" {
+		t.Fatalf("expected non-DeepSeek provider to omit reasoning_content, got %q", got[0].ReasoningContent)
+	}
+	body, err := json.Marshal(got[0])
+	if err != nil {
+		t.Fatalf("marshal message: %v", err)
+	}
+	if strings.Contains(string(body), "reasoning_content") {
+		t.Fatalf("expected JSON payload to omit reasoning_content for non-DeepSeek provider, got %s", body)
+	}
+}
+
+func TestBuildOpenAIMessages_ReplaysDeepSeekAssistantReasoningContentWithoutToolCalls(t *testing.T) {
+	got := buildOpenAIMessages([]ai.Message{
+		{
+			Role:             "assistant",
+			Content:          "最终分析",
+			ReasoningContent: "工具调用轮次的最终思考也需要保留",
+		},
+	}, "deepseek-v4", "https://api.deepseek.com/v1")
+
+	if got[0].ReasoningContent != "工具调用轮次的最终思考也需要保留" {
+		t.Fatalf("expected DeepSeek assistant reasoning_content to be replayed, got %q", got[0].ReasoningContent)
+	}
+}
+
+func testOpenAIToolCall() ai.ToolCall {
+	var toolCall ai.ToolCall
+	toolCall.ID = "call_schema"
+	toolCall.Type = "function"
+	toolCall.Function.Name = "inspect_table_schema"
+	toolCall.Function.Arguments = `{"table":"orders"}`
+	return toolCall
+}
--- a/internal/ai/service/service.go
+++ b/internal/ai/service/service.go
@@ -866,9 +866,10 @@ func (s *Service) AIChatSend(messages []ai.Message, tools []ai.Tool) map[string]
 	}

 	return map[string]interface{}{
-		"success":    true,
-		"content":    resp.Content,
-		"tool_calls": resp.ToolCalls,
+		"success":           true,
+		"content":           resp.Content,
+		"reasoning_content": resp.ReasoningContent,
+		"tool_calls":        resp.ToolCalls,
 		"tokensUsed": map[string]int{
 			"promptTokens":     resp.TokensUsed.PromptTokens,
 			"completionTokens": resp.TokensUsed.CompletionTokens,
@@ -903,11 +904,12 @@ func (s *Service) AIChatStream(sessionID string, messages []ai.Message, tools []

 		err = p.ChatStream(streamCtx, ai.ChatRequest{Messages: messages, Tools: tools}, func(chunk ai.StreamChunk) {
 			wailsRuntime.EventsEmit(s.ctx, "ai:stream:"+sessionID, map[string]interface{}{
-				"content":    chunk.Content,
-				"thinking":   chunk.Thinking,
-				"tool_calls": chunk.ToolCalls,
-				"done":       chunk.Done,
-				"error":      chunk.Error,
+				"content":           chunk.Content,
+				"thinking":          chunk.Thinking,
+				"reasoning_content": chunk.ReasoningContent,
+				"tool_calls":        chunk.ToolCalls,
+				"done":              chunk.Done,
+				"error":             chunk.Error,
 			})
 		})

--- a/internal/ai/types.go
+++ b/internal/ai/types.go
@@ -25,11 +25,12 @@ type Tool struct {

 // Message 表示一条对话消息
 type Message struct {
-	Role       string     `json:"role"` // "system" | "user" | "assistant" | "tool"
-	Content    string     `json:"content"`
-	Images     []string   `json:"images,omitempty"`       // base64 encoded images with data:image/png;base64,... prefix
-	ToolCallID string     `json:"tool_call_id,omitempty"` // 当 role 为 "tool" 时必须传递
-	ToolCalls  []ToolCall `json:"tool_calls,omitempty"`   // 当 role 为 "assistant" 并试图调工具时传递
+	Role             string     `json:"role"` // "system" | "user" | "assistant" | "tool"
+	Content          string     `json:"content"`
+	Images           []string   `json:"images,omitempty"`            // base64 encoded images with data:image/png;base64,... prefix
+	ToolCallID       string     `json:"tool_call_id,omitempty"`      // 当 role 为 "tool" 时必须传递
+	ToolCalls        []ToolCall `json:"tool_calls,omitempty"`        // 当 role 为 "assistant" 并试图调工具时传递
+	ReasoningContent string     `json:"reasoning_content,omitempty"` // DeepSeek thinking mode 工具调用链路要求原样回传
 }

 // ChatRequest AI 对话请求
@@ -42,9 +43,10 @@ type ChatRequest struct {

 // ChatResponse AI 对话响应
 type ChatResponse struct {
-	Content    string     `json:"content"`
-	TokensUsed TokenUsage `json:"tokensUsed"`
-	ToolCalls  []ToolCall `json:"tool_calls,omitempty"`
+	Content          string     `json:"content"`
+	ReasoningContent string     `json:"reasoning_content,omitempty"`
+	TokensUsed       TokenUsage `json:"tokensUsed"`
+	ToolCalls        []ToolCall `json:"tool_calls,omitempty"`
 }

 // TokenUsage token 用量统计
@@ -56,11 +58,12 @@ type TokenUsage struct {

 // StreamChunk 流式响应片段
 type StreamChunk struct {
-	Content   string     `json:"content"`
-	Thinking  string     `json:"thinking,omitempty"`
-	Done      bool       `json:"done"`
-	Error     string     `json:"error,omitempty"`
-	ToolCalls []ToolCall `json:"tool_calls,omitempty"`
+	Content          string     `json:"content"`
+	Thinking         string     `json:"thinking,omitempty"`
+	ReasoningContent string     `json:"reasoning_content,omitempty"`
+	Done             bool       `json:"done"`
+	Error            string     `json:"error,omitempty"`
+	ToolCalls        []ToolCall `json:"tool_calls,omitempty"`
 }

 // ProviderConfig AI Provider 配置