feat: 改造query_llm_with_grounding支持多轮对话

- 扩展RAG Grounding数据模型支持会话管理
- 添加多轮对话的RAG查询方法query_llm_with_grounding_multi_turn
- 集成现有会话管理服务，支持历史消息存储和检索
- 更新前端类型定义和服务层，支持多轮对话参数
- 创建多轮RAG对话测试组件和页面
- 支持系统提示词、历史消息数量控制等配置选项
- 保持向后兼容，单轮对话功能不受影响

核心功能:
 多轮RAG对话 - 基于检索增强生成的多轮对话
 会话历史管理 - 自动保存和加载对话历史
 智能检索增强 - 结合Vertex AI Search的知识检索
 上下文保持 - 在多轮对话中保持对话上下文
 灵活配置 - 支持历史消息数量、系统提示词等配置
 来源追踪 - 显示检索来源和相关性信息

遵循promptx/tauri-desktop-app-expert开发规范

apps/desktop/src-tauri/src/infrastructure/gemini_service.rs

@@ -11,6 +11,13 @@ use reqwest::multipart;
 use crate::infrastructure::tolerant_json_parser::{TolerantJsonParser, ParserConfig, RecoveryStrategy};
 use std::sync::{Arc, Mutex};
 
+// 导入会话管理相关模块
+use crate::data::models::conversation::{
+    ConversationMessage, MessageRole, MessageContent, ConversationHistoryQuery,
+    CreateConversationSessionRequest, AddMessageRequest,
+};
+use crate::data::repositories::conversation_repository::ConversationRepository;
+
 /// Gemini API配置
 #[derive(Debug, Clone)]
 pub struct GeminiConfig {
@@ -180,6 +187,9 @@ pub struct RagGroundingRequest {
     pub user_input: String,
     pub config: Option<RagGroundingConfig>,
     pub session_id: Option<String>,
+    pub include_history: Option<bool>,
+    pub max_history_messages: Option<u32>,
+    pub system_prompt: Option<String>,
 }
 
 /// RAG Grounding 响应
@@ -189,6 +199,9 @@ pub struct RagGroundingResponse {
     pub grounding_metadata: Option<GroundingMetadata>,
     pub response_time_ms: u64,
     pub model_used: String,
+    pub session_id: Option<String>,
+    pub message_id: Option<String>,
+    pub conversation_context: Option<ConversationContext>,
 }
 
 /// Grounding 元数据
@@ -206,6 +219,14 @@ pub struct GroundingSource {
     pub content: Option<serde_json::Value>,
 }
 
+/// 对话上下文
+#[derive(Debug, Serialize, Deserialize)]
+pub struct ConversationContext {
+    pub total_messages: u32,
+    pub history_included: bool,
+    pub context_length: u32,
+}
+
 /// Vertex AI Search 工具配置
 #[derive(Debug, Serialize)]
 struct VertexAISearchTool {
@@ -903,6 +924,17 @@ impl GeminiService {
 
     /// RAG Grounding 查询 (参考 RAGUtils.py 中的 query_llm_with_grounding)
     pub async fn query_llm_with_grounding(&mut self, request: RagGroundingRequest) -> Result<RagGroundingResponse> {
+        // 如果请求包含会话管理参数，使用多轮对话版本
+        if request.session_id.is_some() || request.include_history.unwrap_or(false) {
+            return self.query_llm_with_grounding_multi_turn(request, None).await;
+        }
+
+        // 否则使用原有的单轮对话逻辑
+        self.query_llm_with_grounding_single_turn(request).await
+    }
+
+    /// 单轮RAG Grounding查询（原有逻辑）
+    async fn query_llm_with_grounding_single_turn(&mut self, request: RagGroundingRequest) -> Result<RagGroundingResponse> {
         let start_time = std::time::Instant::now();
         println!("🔍 开始RAG Grounding查询: {}", request.user_input);
 
@@ -976,6 +1008,9 @@ impl GeminiService {
                         grounding_metadata: response.grounding_metadata,
                         response_time_ms: elapsed.as_millis() as u64,
                         model_used: rag_config.model_id,
+                        session_id: None,
+                        message_id: None,
+                        conversation_context: None,
                     });
                 }
                 Err(e) => {
@@ -990,6 +1025,267 @@ impl GeminiService {
         Err(anyhow!("RAG Grounding查询失败，已重试{}次: {}", self.config.max_retries, last_error.unwrap()))
     }
 
+    /// 多轮RAG Grounding查询（支持会话历史）
+    pub async fn query_llm_with_grounding_multi_turn(
+        &mut self,
+        request: RagGroundingRequest,
+        conversation_repo: Option<Arc<ConversationRepository>>,
+    ) -> Result<RagGroundingResponse> {
+        let start_time = std::time::Instant::now();
+        println!("🔍 开始多轮RAG Grounding查询: {}", request.user_input);
+
+        // 获取配置
+        let rag_config = request.config.unwrap_or_default();
+
+        // 1. 确定或创建会话
+        let session_id = match &request.session_id {
+            Some(id) => id.clone(),
+            None => {
+                // 如果没有提供session_id，生成一个新的
+                uuid::Uuid::new_v4().to_string()
+            }
+        };
+
+        // 2. 获取历史消息（如果需要且有会话仓库）
+        let mut contents = Vec::new();
+        let mut conversation_context = ConversationContext {
+            total_messages: 0,
+            history_included: false,
+            context_length: 0,
+        };
+
+        if let (Some(repo), true) = (&conversation_repo, request.include_history.unwrap_or(false)) {
+            match self.get_conversation_history(&repo, &session_id, request.max_history_messages.unwrap_or(10)).await {
+                Ok(history_messages) => {
+                    conversation_context.total_messages = history_messages.len() as u32;
+                    conversation_context.history_included = true;
+
+                    // 添加系统提示（如果有）
+                    if let Some(system_prompt) = &request.system_prompt {
+                        contents.push(ContentPart {
+                            role: "system".to_string(),
+                            parts: vec![Part::Text { text: system_prompt.clone() }],
+                        });
+                    } else if let Some(default_prompt) = &rag_config.system_prompt {
+                        contents.push(ContentPart {
+                            role: "system".to_string(),
+                            parts: vec![Part::Text { text: default_prompt.clone() }],
+                        });
+                    }
+
+                    // 添加历史消息
+                    for msg in &history_messages {
+                        let parts = self.convert_message_content_to_parts(&msg.content)?;
+                        contents.push(ContentPart {
+                            role: msg.role.to_string(),
+                            parts,
+                        });
+                    }
+
+                    conversation_context.context_length = contents.len() as u32;
+                    println!("📚 加载了 {} 条历史消息", history_messages.len());
+                }
+                Err(e) => {
+                    println!("⚠️ 获取历史消息失败: {}", e);
+                }
+            }
+        }
+
+        // 3. 添加当前用户消息
+        contents.push(ContentPart {
+            role: "user".to_string(),
+            parts: vec![Part::Text { text: request.user_input.clone() }],
+        });
+
+        // 4. 执行RAG查询
+        let response = self.execute_rag_grounding_with_contents(contents, rag_config).await?;
+
+        // 5. 保存消息到会话历史（如果有会话仓库）
+        let message_id = if let Some(repo) = &conversation_repo {
+            match self.save_conversation_messages(&repo, &session_id, &request.user_input, &response.answer).await {
+                Ok(id) => Some(id),
+                Err(e) => {
+                    println!("⚠️ 保存会话消息失败: {}", e);
+                    None
+                }
+            }
+        } else {
+            None
+        };
+
+        let elapsed = start_time.elapsed();
+        println!("✅ 多轮RAG Grounding查询完成，耗时: {:?}", elapsed);
+
+        Ok(RagGroundingResponse {
+            answer: response.answer,
+            grounding_metadata: response.grounding_metadata,
+            response_time_ms: elapsed.as_millis() as u64,
+            model_used: response.model_used,
+            session_id: Some(session_id),
+            message_id,
+            conversation_context: Some(conversation_context),
+        })
+    }
+
+    /// 获取会话历史消息
+    async fn get_conversation_history(
+        &self,
+        repo: &Arc<ConversationRepository>,
+        session_id: &str,
+        max_messages: u32,
+    ) -> Result<Vec<ConversationMessage>> {
+        let query = ConversationHistoryQuery {
+            session_id: session_id.to_string(),
+            limit: Some(max_messages),
+            offset: None,
+            include_system_messages: Some(false),
+        };
+
+        match repo.get_conversation_history(query) {
+            Ok(history) => Ok(history.messages),
+            Err(e) => Err(anyhow!("获取会话历史失败: {}", e)),
+        }
+    }
+
+    /// 保存会话消息
+    async fn save_conversation_messages(
+        &self,
+        repo: &Arc<ConversationRepository>,
+        session_id: &str,
+        user_input: &str,
+        assistant_response: &str,
+    ) -> Result<String> {
+        // 保存用户消息
+        let user_message_request = AddMessageRequest {
+            session_id: session_id.to_string(),
+            role: MessageRole::User,
+            content: vec![MessageContent::Text { text: user_input.to_string() }],
+            metadata: None,
+        };
+
+        repo.add_message(user_message_request)?;
+
+        // 保存助手回复
+        let assistant_message_request = AddMessageRequest {
+            session_id: session_id.to_string(),
+            role: MessageRole::Assistant,
+            content: vec![MessageContent::Text { text: assistant_response.to_string() }],
+            metadata: None,
+        };
+
+        let assistant_message = repo.add_message(assistant_message_request)?;
+        Ok(assistant_message.id)
+    }
+
+    /// 执行带有完整contents的RAG查询
+    async fn execute_rag_grounding_with_contents(
+        &mut self,
+        contents: Vec<ContentPart>,
+        rag_config: RagGroundingConfig,
+    ) -> Result<RagGroundingResponse> {
+        // 获取访问令牌
+        let access_token = self.get_access_token().await?;
+
+        // 创建客户端配置
+        let client_config = self.create_gemini_client(&access_token);
+
+        // 构建数据存储路径
+        let datastore_path = format!(
+            "projects/{}/locations/{}/collections/default_collection/dataStores/{}",
+            rag_config.project_id,
+            rag_config.location,
+            rag_config.data_store_id
+        );
+
+        // 构建工具配置 (Vertex AI Search)
+        let tools = vec![VertexAISearchTool {
+            retrieval: VertexAIRetrieval {
+                vertex_ai_search: VertexAISearchConfig {
+                    datastore: datastore_path,
+                },
+            },
+        }];
+
+        // 构建生成配置
+        let generation_config = GenerationConfig {
+            temperature: rag_config.temperature,
+            top_k: 32,
+            top_p: 1.0,
+            max_output_tokens: rag_config.max_output_tokens,
+        };
+
+        // 准备请求数据
+        let request_data = serde_json::json!({
+            "contents": contents,
+            "tools": tools,
+            "generationConfig": generation_config,
+            "toolConfig": {
+                "functionCallingConfig": {
+                    "mode": "ANY",
+                    "allowedFunctionNames": ["retrieval"]
+                }
+            }
+        });
+
+        // 发送请求到Cloudflare Gateway (使用beta API)
+        let generate_url = format!("{}/{}:generateContent", client_config.gateway_url, rag_config.model_id);
+
+        // 重试机制
+        let mut last_error = None;
+        for attempt in 0..self.config.max_retries {
+            match self.send_rag_grounding_request(&generate_url, &client_config, &request_data).await {
+                Ok(response) => {
+                    return Ok(RagGroundingResponse {
+                        answer: response.answer,
+                        grounding_metadata: response.grounding_metadata,
+                        response_time_ms: 0, // 这里会在调用方设置
+                        model_used: rag_config.model_id,
+                        session_id: None,
+                        message_id: None,
+                        conversation_context: None,
+                    });
+                }
+                Err(e) => {
+                    last_error = Some(e);
+                    if attempt < self.config.max_retries - 1 {
+                        tokio::time::sleep(tokio::time::Duration::from_secs(self.config.retry_delay)).await;
+                    }
+                }
+            }
+        }
+
+        Err(anyhow!("RAG Grounding查询失败，已重试{}次: {}", self.config.max_retries, last_error.unwrap()))
+    }
+
+    /// 将消息内容转换为Gemini API的Part格式
+    fn convert_message_content_to_parts(&self, content: &[MessageContent]) -> Result<Vec<Part>> {
+        let mut parts = Vec::new();
+        for item in content {
+            match item {
+                MessageContent::Text { text } => {
+                    parts.push(Part::Text { text: text.clone() });
+                }
+                MessageContent::File { file_uri, mime_type, .. } => {
+                    parts.push(Part::FileData {
+                        file_data: FileData {
+                            mime_type: mime_type.clone(),
+                            file_uri: file_uri.clone(),
+                        }
+                    });
+                }
+                MessageContent::InlineData { data, mime_type, .. } => {
+                    parts.push(Part::InlineData {
+                        inline_data: InlineData {
+                            mime_type: mime_type.clone(),
+                            data: data.clone(),
+                        }
+                    });
+                }
+            }
+        }
+        Ok(parts)
+    }
+
     /// 发送RAG Grounding请求
     async fn send_rag_grounding_request(
         &self,
@@ -1067,6 +1363,9 @@ impl GeminiService {
             grounding_metadata,
             response_time_ms: 0, // 将在调用方设置
             model_used: "gemini-2.5-flash".to_string(),
+            session_id: None,
+            message_id: None,
+            conversation_context: None,
         })
     }
 

apps/desktop/src-tauri/src/presentation/commands/rag_grounding_commands.rs

@@ -4,9 +4,10 @@ use crate::app_state::AppState;
 
 /// RAG Grounding 查询命令
 /// 基于数据存储的检索增强生成，参考 RAGUtils.py 中的 query_llm_with_grounding 实现
+/// 现已支持多轮对话功能
 #[command]
 pub async fn query_rag_grounding(
-    _state: State<'_, AppState>,
+    state: State<'_, AppState>,
     request: RagGroundingRequest,
 ) -> Result<RagGroundingResponse, String> {
     println!("🔍 收到RAG Grounding查询请求: {}", request.user_input);
@@ -16,14 +17,37 @@ pub async fn query_rag_grounding(
     let mut gemini_service = GeminiService::new(Some(config))
         .map_err(|e| format!("创建GeminiService失败: {}", e))?;
 
+    // 如果请求包含会话管理参数，获取会话仓库
+    let conversation_repo = if request.session_id.is_some() || request.include_history.unwrap_or(false) {
+        match state.inner().get_conversation_repository() {
+            Ok(repo) => Some(repo),
+            Err(e) => {
+                println!("⚠️ 获取会话仓库失败，将使用单轮对话模式: {}", e);
+                None
+            }
+        }
+    } else {
+        None
+    };
+
     // 执行RAG Grounding查询
-    let response = gemini_service
+    let response = if conversation_repo.is_some() {
+        gemini_service
+            .query_llm_with_grounding_multi_turn(request, conversation_repo)
+            .await
+            .map_err(|e| {
+                eprintln!("多轮RAG Grounding查询失败: {}", e);
+                format!("多轮RAG Grounding查询失败: {}", e)
+            })?
+    } else {
+        gemini_service
             .query_llm_with_grounding(request)
             .await
             .map_err(|e| {
                 eprintln!("RAG Grounding查询失败: {}", e);
                 format!("RAG Grounding查询失败: {}", e)
-        })?;
+            })?
+    };
 
     println!("✅ RAG Grounding查询成功，响应时间: {}ms", response.response_time_ms);
 
@@ -47,6 +71,9 @@ pub async fn test_rag_grounding_connection(
         user_input: "测试连接".to_string(),
         config: None,
         session_id: Some("test-session".to_string()),
+        include_history: Some(false),
+        max_history_messages: None,
+        system_prompt: None,
     };
 
     // 执行测试查询

apps/desktop/src/components/MultiTurnRagChatTest.tsx

@@ -0,0 +1,334 @@
+import React, { useState, useCallback, useRef, useEffect } from 'react';
+import { queryRagGrounding } from '../services/ragGroundingService';
+import { 
+  RagGroundingQueryOptions, 
+  RagGroundingResponse,
+  GroundingSource,
+  ConversationContext,
+} from '../types/ragGrounding';
+
+/**
+ * 多轮RAG对话测试组件
+ * 支持基于检索增强生成的多轮对话功能
+ */
+
+interface ChatMessage {
+  id: string;
+  type: 'user' | 'assistant';
+  content: string;
+  timestamp: Date;
+  status: 'sending' | 'sent' | 'error';
+  metadata?: {
+    responseTime?: number;
+    modelUsed?: string;
+    groundingSources?: GroundingSource[];
+    conversationContext?: ConversationContext;
+  };
+}
+
+export const MultiTurnRagChatTest: React.FC = () => {
+  const [messages, setMessages] = useState<ChatMessage[]>([]);
+  const [input, setInput] = useState('');
+  const [isLoading, setIsLoading] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const [sessionId, setSessionId] = useState<string | null>(null);
+  const [showHistory, setShowHistory] = useState(true);
+  const [maxHistoryMessages, setMaxHistoryMessages] = useState(10);
+  const [systemPrompt, setSystemPrompt] = useState('你是一个专业的服装搭配顾问，基于检索到的相关信息为用户提供准确、实用的搭配建议。');
+  const [showGroundingSources, setShowGroundingSources] = useState(true);
+  
+  const messagesEndRef = useRef<HTMLDivElement>(null);
+
+  // 自动滚动到底部
+  const scrollToBottom = useCallback(() => {
+    messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
+  }, []);
+
+  useEffect(() => {
+    scrollToBottom();
+  }, [messages, scrollToBottom]);
+
+  // 生成消息ID
+  const generateMessageId = () => {
+    return `msg_${Date.now()}_${Math.random().toString(36).substring(2, 11)}`;
+  };
+
+  // 发送消息
+  const handleSendMessage = useCallback(async () => {
+    if (!input.trim() || isLoading) return;
+
+    const userMessage: ChatMessage = {
+      id: generateMessageId(),
+      type: 'user',
+      content: input.trim(),
+      timestamp: new Date(),
+      status: 'sent'
+    };
+
+    const assistantMessage: ChatMessage = {
+      id: generateMessageId(),
+      type: 'assistant',
+      content: '',
+      timestamp: new Date(),
+      status: 'sending'
+    };
+
+    // 添加用户消息和占位助手消息
+    setMessages(prev => [...prev, userMessage, assistantMessage]);
+    setInput('');
+    setIsLoading(true);
+    setError(null);
+
+    try {
+      // 构建查询选项
+      const options: RagGroundingQueryOptions = {
+        sessionId: sessionId || undefined,
+        includeHistory: showHistory,
+        maxHistoryMessages: maxHistoryMessages,
+        systemPrompt: systemPrompt.trim() || undefined,
+        includeMetadata: showGroundingSources,
+      };
+
+      // 调用RAG Grounding服务
+      const result = await queryRagGrounding(userMessage.content, options);
+
+      if (result.success && result.data) {
+        // 更新会话ID
+        if (!sessionId && result.data.session_id) {
+          setSessionId(result.data.session_id);
+        }
+
+        // 更新助手消息
+        setMessages(prev => prev.map(msg => 
+          msg.id === assistantMessage.id 
+            ? { 
+                ...msg, 
+                content: result.data!.answer, 
+                status: 'sent' as const,
+                metadata: {
+                  responseTime: result.data!.response_time_ms,
+                  modelUsed: result.data!.model_used,
+                  groundingSources: result.data!.grounding_metadata?.sources,
+                  conversationContext: result.data!.conversation_context,
+                }
+              }
+            : msg
+        ));
+      } else {
+        // 处理错误
+        setError(result.error || '查询失败');
+        setMessages(prev => prev.map(msg => 
+          msg.id === assistantMessage.id 
+            ? { ...msg, content: '抱歉，查询过程中发生了错误', status: 'error' as const }
+            : msg
+        ));
+      }
+    } catch (err) {
+      const errorMessage = err instanceof Error ? err.message : '未知错误';
+      setError(errorMessage);
+      setMessages(prev => prev.map(msg => 
+        msg.id === assistantMessage.id 
+          ? { ...msg, content: '抱歉，发生了系统错误', status: 'error' as const }
+          : msg
+      ));
+    } finally {
+      setIsLoading(false);
+    }
+  }, [input, isLoading, sessionId, showHistory, maxHistoryMessages, systemPrompt, showGroundingSources]);
+
+  // 清空对话
+  const handleClearChat = useCallback(() => {
+    setMessages([]);
+    setSessionId(null);
+    setError(null);
+  }, []);
+
+  // 处理键盘事件
+  const handleKeyPress = useCallback((e: React.KeyboardEvent) => {
+    if (e.key === 'Enter' && !e.shiftKey) {
+      e.preventDefault();
+      handleSendMessage();
+    }
+  }, [handleSendMessage]);
+
+  // 格式化响应时间
+  const formatResponseTime = (ms: number) => {
+    if (ms < 1000) return `${ms}ms`;
+    return `${(ms / 1000).toFixed(1)}s`;
+  };
+
+  return (
+    <div className="flex flex-col h-full max-w-6xl mx-auto p-4">
+      {/* 标题和设置 */}
+      <div className="mb-4">
+        <h2 className="text-2xl font-bold mb-2">多轮RAG对话测试</h2>
+        <div className="grid grid-cols-1 md:grid-cols-2 gap-4 text-sm">
+          <div className="space-y-2">
+            <div className="flex items-center gap-2">
+              <label className="flex items-center gap-1">
+                <input
+                  type="checkbox"
+                  checked={showHistory}
+                  onChange={(e) => setShowHistory(e.target.checked)}
+                  className="rounded"
+                />
+                包含历史消息
+              </label>
+            </div>
+            <div className="flex items-center gap-2">
+              <label>最大历史消息数:</label>
+              <input
+                type="number"
+                value={maxHistoryMessages}
+                onChange={(e) => setMaxHistoryMessages(parseInt(e.target.value) || 10)}
+                min="1"
+                max="50"
+                className="w-16 px-2 py-1 border rounded"
+              />
+            </div>
+            <div className="flex items-center gap-2">
+              <label className="flex items-center gap-1">
+                <input
+                  type="checkbox"
+                  checked={showGroundingSources}
+                  onChange={(e) => setShowGroundingSources(e.target.checked)}
+                  className="rounded"
+                />
+                显示检索来源
+              </label>
+            </div>
+          </div>
+          <div className="space-y-2">
+            <div className="text-gray-600">
+              会话ID: {sessionId ? sessionId.substring(0, 8) + '...' : '未创建'}
+            </div>
+            <button
+              onClick={handleClearChat}
+              className="px-3 py-1 bg-gray-500 text-white rounded hover:bg-gray-600"
+            >
+              清空对话
+            </button>
+          </div>
+        </div>
+        
+        {/* 系统提示词设置 */}
+        <div className="mt-4">
+          <label className="block text-sm font-medium mb-1">系统提示词:</label>
+          <textarea
+            value={systemPrompt}
+            onChange={(e) => setSystemPrompt(e.target.value)}
+            placeholder="设置系统提示词..."
+            className="w-full px-3 py-2 border rounded-lg resize-none"
+            rows={2}
+          />
+        </div>
+      </div>
+
+      {/* 错误提示 */}
+      {error && (
+        <div className="mb-4 p-3 bg-red-100 border border-red-400 text-red-700 rounded">
+          错误: {error}
+        </div>
+      )}
+
+      {/* 消息列表 */}
+      <div className="flex-1 overflow-y-auto border rounded-lg p-4 mb-4 bg-gray-50">
+        {messages.length === 0 ? (
+          <div className="text-center text-gray-500 py-8">
+            开始RAG对话吧！这是一个基于检索增强生成的多轮对话测试界面。
+          </div>
+        ) : (
+          <div className="space-y-4">
+            {messages.map((message) => (
+              <div
+                key={message.id}
+                className={`flex ${message.type === 'user' ? 'justify-end' : 'justify-start'}`}
+              >
+                <div
+                  className={`max-w-2xl px-4 py-2 rounded-lg ${
+                    message.type === 'user'
+                      ? 'bg-blue-500 text-white'
+                      : message.status === 'error'
+                      ? 'bg-red-100 text-red-800 border border-red-300'
+                      : 'bg-white border border-gray-300'
+                  }`}
+                >
+                  <div className="whitespace-pre-wrap">{message.content}</div>
+                  
+                  {/* 消息元数据 */}
+                  <div className="text-xs mt-2 opacity-70">
+                    {message.timestamp.toLocaleTimeString()}
+                    {message.metadata?.responseTime && (
+                      <span className="ml-2">
+                        ({formatResponseTime(message.metadata.responseTime)})
+                      </span>
+                    )}
+                    {message.status === 'sending' && (
+                      <span className="ml-2">发送中...</span>
+                    )}
+                  </div>
+
+                  {/* 检索来源 */}
+                  {message.metadata?.groundingSources && message.metadata.groundingSources.length > 0 && (
+                    <div className="mt-2 pt-2 border-t border-gray-200">
+                      <div className="text-xs font-medium mb-1">检索来源:</div>
+                      <div className="space-y-1">
+                        {message.metadata.groundingSources.map((source, index) => (
+                          <div key={index} className="text-xs bg-gray-100 p-2 rounded">
+                            <div className="font-medium">{source.title}</div>
+                            {source.uri && (
+                              <div className="text-blue-600 truncate">{source.uri}</div>
+                            )}
+                          </div>
+                        ))}
+                      </div>
+                    </div>
+                  )}
+
+                  {/* 对话上下文信息 */}
+                  {message.metadata?.conversationContext && (
+                    <div className="mt-2 pt-2 border-t border-gray-200 text-xs text-gray-600">
+                      上下文: {message.metadata.conversationContext.total_messages} 条消息
+                      {message.metadata.conversationContext.history_included && 
+                        ` (包含 ${message.metadata.conversationContext.context_length} 条历史)`
+                      }
+                    </div>
+                  )}
+                </div>
+              </div>
+            ))}
+          </div>
+        )}
+        <div ref={messagesEndRef} />
+      </div>
+
+      {/* 输入区域 */}
+      <div className="flex gap-2">
+        <textarea
+          value={input}
+          onChange={(e) => setInput(e.target.value)}
+          onKeyPress={handleKeyPress}
+          placeholder="输入消息... (Enter发送，Shift+Enter换行)"
+          className="flex-1 px-3 py-2 border rounded-lg resize-none"
+          rows={2}
+          disabled={isLoading}
+        />
+        <button
+          onClick={handleSendMessage}
+          disabled={!input.trim() || isLoading}
+          className="px-6 py-2 bg-blue-500 text-white rounded-lg hover:bg-blue-600 disabled:bg-gray-300 disabled:cursor-not-allowed"
+        >
+          {isLoading ? '查询中...' : '发送'}
+        </button>
+      </div>
+
+      {/* 统计信息 */}
+      <div className="mt-2 text-xs text-gray-500 text-center">
+        消息数: {messages.length} | 
+        历史消息: {showHistory ? '开启' : '关闭'} | 
+        最大历史: {maxHistoryMessages}条 |
+        检索来源: {showGroundingSources ? '显示' : '隐藏'}
+      </div>
+    </div>
+  );
+};

apps/desktop/src/pages/MultiTurnRagChatTestPage.tsx

@@ -0,0 +1,49 @@
+import React from 'react';
+import { MultiTurnRagChatTest } from '../components/MultiTurnRagChatTest';
+
+/**
+ * 多轮RAG对话测试页面
+ * 基于检索增强生成的多轮对话功能测试界面
+ */
+export const MultiTurnRagChatTestPage: React.FC = () => {
+  return (
+    <div className="h-screen flex flex-col">
+      {/* 页面头部 */}
+      <header className="bg-white border-b border-gray-200 px-6 py-4">
+        <div className="flex items-center justify-between">
+          <div>
+            <h1 className="text-2xl font-bold text-gray-900">多轮RAG对话功能测试</h1>
+            <p className="text-sm text-gray-600 mt-1">
+              基于检索增强生成(RAG)的多轮对话系统，支持会话历史管理和智能检索
+            </p>
+          </div>
+          <div className="text-sm text-gray-500">
+            <div>版本: v0.2.2</div>
+            <div>模型: Gemini 2.5 Flash</div>
+            <div>检索: Vertex AI Search</div>
+          </div>
+        </div>
+      </header>
+
+      {/* 主要内容区域 */}
+      <main className="flex-1 overflow-hidden">
+        <MultiTurnRagChatTest />
+      </main>
+
+      {/* 页面底部 */}
+      <footer className="bg-gray-50 border-t border-gray-200 px-6 py-3">
+        <div className="flex items-center justify-between text-sm text-gray-600">
+          <div>
+            基于 Tauri + React + TypeScript 构建的RAG多轮对话系统
+          </div>
+          <div className="flex items-center gap-4">
+            <span>🔍 智能检索</span>
+            <span>💬 多轮对话</span>
+            <span>📚 知识增强</span>
+            <span>🔄 上下文保持</span>
+          </div>
+        </div>
+      </footer>
+    </div>
+  );
+};

apps/desktop/src/services/ragGroundingService.ts

@@ -60,6 +60,9 @@ export class RagGroundingService {
         user_input: userInput,
         config,
         session_id: options.sessionId,
+        include_history: options.includeHistory,
+        max_history_messages: options.maxHistoryMessages,
+        system_prompt: options.systemPrompt,
       };
 
       console.log('🔍 发起RAG Grounding查询:', { userInput, options });

apps/desktop/src/types/ragGrounding.ts

@@ -23,6 +23,9 @@ export interface RagGroundingRequest {
   user_input: string;
   config?: RagGroundingConfig;
   session_id?: string;
+  include_history?: boolean;
+  max_history_messages?: number;
+  system_prompt?: string;
 }
 
 /**
@@ -33,6 +36,9 @@ export interface RagGroundingResponse {
   grounding_metadata?: GroundingMetadata;
   response_time_ms: number;
   model_used: string;
+  session_id?: string;
+  message_id?: string;
+  conversation_context?: ConversationContext;
 }
 
 /**
@@ -52,6 +58,15 @@ export interface GroundingSource {
   content?: any; // JSON 内容
 }
 
+/**
+ * 对话上下文
+ */
+export interface ConversationContext {
+  total_messages: number;
+  history_included: boolean;
+  context_length: number;
+}
+
 /**
  * RAG Grounding 配置信息
  */
@@ -93,6 +108,12 @@ export interface RagGroundingQueryOptions {
   customConfig?: Partial<RagGroundingConfig>;
   /** 超时时间（毫秒） */
   timeout?: number;
+  /** 是否包含历史消息 */
+  includeHistory?: boolean;
+  /** 最大历史消息数 */
+  maxHistoryMessages?: number;
+  /** 系统提示词 */
+  systemPrompt?: string;
 }
 
 /**