Feature/model

internal/service/chat_mode.go

@@ -45,14 +45,23 @@ func (s *chatService) processMessage(ctx context.Context, userID, sessionID stri
 
 	chatModel := client.ChatModel()
 
-	// Step 2+3: 检索（条件改写，优先速度）
-	sendProgressEvent(eventCh, "正在检索知识库...")
+	// Step 2: 轻量意图分析，决定是否需要检索
+	intent := AnalyzeIntent(req.Content)
+	logger.Infof("意图识别: sessionID=%s, intent=%s, confidence=%.2f, reason=%s, skipRetrieval=%v",
+		sessionID, intent.Intent, intent.Confidence, intent.Reason, intent.SkipRetrieval)
 
 	var sources []dto.SourceInfo
 	var retrieveResult rag.Result
 
-	needRewrite := len(history) > 0 && needsQueryRewrite(req.Content)
-	if needRewrite {
+	if intent.SkipRetrieval {
+		sendProgressEvent(eventCh, "正在整理回答...")
+		// 问候/身份/元问题/闲聊/列表查询等直接跳过 RAG，由 System Prompt 指导回答
+	} else {
+		// Step 3: 检索（条件改写，优先速度）
+		sendProgressEvent(eventCh, "正在检索知识库...")
+
+		needRewrite := len(history) > 0 && needsQueryRewrite(req.Content)
+		if needRewrite {
 		// 并行：查询改写 + 原始查询先行检索
 		g, gCtx := errgroup.WithContext(ctx)
 
@@ -97,10 +106,11 @@ func (s *chatService) processMessage(ctx context.Context, userID, sessionID stri
 			return
 		}
 	}
+}
 
 	// Step 4: 组装 Prompt（用原始问题，改写后的查询仅用于检索）
 	sendProgressEvent(eventCh, "正在整理资料...")
-	messages := buildMessages(history, req.Content, retrieveResult, enhancedCtx.Summary, enhancedCtx.Memories, enhancedCtx.RetrievalBudget)
+	messages := buildMessages(history, req.Content, retrieveResult, enhancedCtx.Summary, enhancedCtx.Memories, enhancedCtx.UserCtx, enhancedCtx.RetrievalBudget)
 
 	// Step 5: LLM 流式生成
 	assistantMsgID := uuid.New().String()

internal/service/chat_service.go

@@ -217,7 +217,10 @@ func (s *chatService) initContext(ctx context.Context, userID, sessionID, modelI
 	maxCtx := llm.GetEffectiveMaxContextLength(modelID, client.MaxContextLength())
 	historyBudget, retrievalBudget, memoryBudget := calculateContextBudgets(maxCtx)
 
-	// 3. 使用 ContextService 构建增强上下文
+	// 3. 加载用户基本信息
+	userCtx := s.loadUserContext(ctx, userID)
+
+	// 4. 使用 ContextService 构建增强上下文
 	var enhancedCtx *EnhancedContext
 	if s.contextSvc != nil {
 		t1 = time.Now()
@@ -242,15 +245,29 @@ func (s *chatService) initContext(ctx context.Context, userID, sessionID, modelI
 			RetrievalBudget: retrievalBudget,
 		}
 	}
+	enhancedCtx.UserCtx = userCtx
 
-	logger.Infof("增强上下文: 历史 %d 条(预算 %d), 记忆 %d 条(预算 %d), 检索预算 %d, 摘要存在=%v, 模型窗口=%d",
+	logger.Infof("增强上下文: 历史 %d 条(预算 %d), 记忆 %d 条(预算 %d), 检索预算 %d, 摘要存在=%v, 模型窗口=%d, 用户=%s",
 		len(enhancedCtx.History), enhancedCtx.HistoryBudget,
 		len(enhancedCtx.Memories), memoryBudget,
-		enhancedCtx.RetrievalBudget, enhancedCtx.Summary != nil, maxCtx)
+		enhancedCtx.RetrievalBudget, enhancedCtx.Summary != nil, maxCtx, userCtx.Username)
 	logger.Infof("[Timing] initContext 总耗时: cost=%dms", time.Since(t0).Milliseconds())
 	return client, enhancedCtx, nil
 }
 
+// loadUserContext 加载用户基本信息，失败时返回空上下文（不阻断主流程）
+func (s *chatService) loadUserContext(ctx context.Context, userID string) UserContext {
+	if s.userRepo == nil || userID == "" {
+		return NewUserContext(entity.User{})
+	}
+	user, err := s.userRepo.FindByID(userID)
+	if err != nil {
+		logger.Warnf("加载用户信息失败, userID=%s: %v", userID, err)
+		return NewUserContext(entity.User{})
+	}
+	return NewUserContext(*user)
+}
+
 // calculateContextBudgets 根据模型最大上下文窗口，分配历史、检索、记忆的 token 预算
 func calculateContextBudgets(maxContextLength int) (historyBudget, retrievalBudget, memoryBudget int) {
 	if maxContextLength <= 0 {

internal/service/chat_service_prompt.go

@@ -3,6 +3,7 @@ package service
 import (
 	"fmt"
 	"strings"
+	"time"
 	"unicode/utf8"
 
 	"github.com/cloudwego/eino/schema"
@@ -12,6 +13,28 @@ import (
 	"solvify-agent/pkg/tokenutil"
 )
 
+// UserContext 注入到 System Prompt 的用户上下文信息
+type UserContext struct {
+	ID       string
+	Username string
+	Role     string
+	TimeStr  string
+}
+
+// NewUserContext 创建用户上下文，TimeStr 使用当前时间
+func NewUserContext(user entity.User) UserContext {
+	roleText := "普通用户"
+	if user.Role == 2 {
+		roleText = "管理员"
+	}
+	return UserContext{
+		ID:       user.ID,
+		Username: user.Username,
+		Role:     roleText,
+		TimeStr:  time.Now().Format("2006-01-02 15:04:05（Monday）"),
+	}
+}
+
 const (
 	// maxContextTokens 检索结果注入 Prompt 的最大 token 预算（估算值）
 	maxContextTokens = 3000
@@ -102,8 +125,8 @@ const quickModeSystemPrompt = `你是 Solvify-Agent（Solvify 知识助理），
 - 结构清晰：必要时用小标题或列表，避免一整段堆砌`
 
 // buildMessages 组装快速检索模式的 LLM 消息列表
-func buildMessages(history []entity.ChatMessage, question string, retrieveResult rag.Result, summary *entity.ChatSummary, memories []entity.UserMemory, retrievalBudget int) []*schema.Message {
-	systemPrompt := buildEnhancedSystemPrompt(quickModeSystemPrompt, summary, memories)
+func buildMessages(history []entity.ChatMessage, question string, retrieveResult rag.Result, summary *entity.ChatSummary, memories []entity.UserMemory, userCtx UserContext, retrievalBudget int) []*schema.Message {
+	systemPrompt := buildEnhancedSystemPrompt(quickModeSystemPrompt, summary, memories, userCtx)
 	messages := []*schema.Message{
 		schema.SystemMessage(systemPrompt),
 	}
@@ -129,10 +152,21 @@ func buildMessages(history []entity.ChatMessage, question string, retrieveResult
 	return messages
 }
 
-// buildEnhancedSystemPrompt 在基础 System Prompt 上注入摘要和记忆
-func buildEnhancedSystemPrompt(base string, summary *entity.ChatSummary, memories []entity.UserMemory) string {
+// buildEnhancedSystemPrompt 在基础 System Prompt 上注入时间、用户信息、摘要和记忆
+func buildEnhancedSystemPrompt(base string, summary *entity.ChatSummary, memories []entity.UserMemory, userCtx UserContext) string {
 	var extras []string
 
+	// 注入当前时间和用户上下文
+	userInfo := "## 当前信息\n"
+	userInfo += "- 当前时间：" + userCtx.TimeStr + "\n"
+	if userCtx.Username != "" {
+		userInfo += "- 用户：" + userCtx.Username + "\n"
+	}
+	if userCtx.Role != "" {
+		userInfo += "- 角色：" + userCtx.Role + "\n"
+	}
+	extras = append(extras, userInfo)
+
 	if summary != nil && summary.Summary != "" {
 		extras = append(extras, "## 本次对话摘要\n"+summary.Summary)
 	}

internal/service/context_interface.go

@@ -22,6 +22,7 @@ type EnhancedContext struct {
 	History         []entity.ChatMessage
 	Summary         *entity.ChatSummary
 	Memories        []entity.UserMemory
+	UserCtx         UserContext
 	HistoryBudget   int // 实际使用的历史消息 token 预算
 	RetrievalBudget int // 实际使用的检索上下文 token 预算
 }

internal/service/intent_analyzer.go

@@ -0,0 +1,187 @@
+package service
+
+import (
+	"strings"
+	"unicode/utf8"
+)
+
+// Intent 表示识别出的用户意图类型
+type Intent string
+
+const (
+	// IntentQuestion 知识库问答类（默认）
+	IntentQuestion Intent = "question"
+	// IntentGreeting 问候类
+	IntentGreeting Intent = "greeting"
+	// IntentIdentity 询问助手身份/模型
+	IntentIdentity Intent = "identity"
+	// IntentMeta 询问能力、模式、帮助等元问题
+	IntentMeta Intent = "meta"
+	// IntentChitchat 闲聊/结束语/致谢等
+	IntentChitchat Intent = "chitchat"
+	// IntentListQuery 列表/元数据查询（快速模式无法完成）
+	IntentListQuery Intent = "list_query"
+)
+
+// IntentResult 轻量意图分析结果
+type IntentResult struct {
+	Intent        Intent
+	Confidence    float64
+	SkipRetrieval bool
+	Reason        string
+}
+
+// AnalyzeIntent 基于规则的轻量意图分析
+// 不调用 LLM，仅通过关键词和句式识别常见意图
+func AnalyzeIntent(query string) IntentResult {
+	q := strings.TrimSpace(query)
+	if q == "" {
+		return IntentResult{
+			Intent:        IntentQuestion,
+			Confidence:    1.0,
+			SkipRetrieval: false,
+			Reason:        "空问题按问答处理",
+		}
+	}
+
+	lower := strings.ToLower(q)
+
+	// 1. 问候
+	if isGreeting(lower) {
+		return IntentResult{
+			Intent:        IntentGreeting,
+			Confidence:    0.9,
+			SkipRetrieval: true,
+			Reason:        "命中问候关键词",
+		}
+	}
+
+	// 2. 身份/模型类
+	if isIdentity(lower) {
+		return IntentResult{
+			Intent:        IntentIdentity,
+			Confidence:    0.95,
+			SkipRetrieval: true,
+			Reason:        "询问助手身份或模型",
+		}
+	}
+
+	// 3. 元问题（能力/帮助/模式）
+	if isMeta(lower) {
+		return IntentResult{
+			Intent:        IntentMeta,
+			Confidence:    0.85,
+			SkipRetrieval: true,
+			Reason:        "询问能力、帮助或模式",
+		}
+	}
+
+	// 4. 闲聊/结束语/致谢
+	if isChitchat(lower) {
+		return IntentResult{
+			Intent:        IntentChitchat,
+			Confidence:    0.85,
+			SkipRetrieval: true,
+			Reason:        "闲聊、致谢或结束语",
+		}
+	}
+
+	// 5. 列表/元数据查询（快速模式建议切深度模式）
+	if isListQuery(lower) {
+		return IntentResult{
+			Intent:        IntentListQuery,
+			Confidence:    0.8,
+			SkipRetrieval: true,
+			Reason:        "查询列表/元数据，快速模式无法完成",
+		}
+	}
+
+	// 默认按问答处理
+	return IntentResult{
+		Intent:        IntentQuestion,
+		Confidence:    0.7,
+		SkipRetrieval: false,
+		Reason:        "未命中特殊意图，按知识库问答处理",
+	}
+}
+
+func isGreeting(q string) bool {
+	greetings := []string{
+		"你好", "您好", "嗨", "hello", "hi", "hey",
+		"早上好", "上午好", "中午好", "下午好", "晚上好",
+		"好久不见", "在吗", "在不在", "在么",
+	}
+	for _, g := range greetings {
+		if q == g || strings.HasPrefix(q, g) {
+			return true
+		}
+	}
+	return false
+}
+
+func isIdentity(q string) bool {
+	patterns := []string{
+		"你是谁", "你是什么", "你叫", "你是哪个",
+		"什么模型", "哪个模型", "你是gpt", "你是chatgpt",
+		"你是claude", "你是通义", "你是千问", "你是deepseek",
+		"你是kimi", "你是豆包", "who are you", "what are you",
+		"what model", "which model", "your name",
+	}
+	for _, p := range patterns {
+		if strings.Contains(q, p) {
+			return true
+		}
+	}
+	return false
+}
+
+func isMeta(q string) bool {
+	patterns := []string{
+		"你能做什么", "你能干嘛", "你会什么", "你有什么用",
+		"你能帮我", "你可以帮我", "你可以做什么", "你有什么能力",
+		"怎么使用", "如何使用", "使用说明", "使用帮助",
+		"帮助", "help", "怎么切换", "如何切换",
+		"深度模式", "快速模式", "切换模式", "smart-reasoning",
+	}
+	for _, p := range patterns {
+		if strings.Contains(q, p) {
+			return true
+		}
+	}
+	return false
+}
+
+func isChitchat(q string) bool {
+	// 纯短句结束语/致谢
+	phrases := []string{
+		"谢谢", "感谢", "多谢", "谢了",
+		"再见", "拜拜", "拜", "bye", "goodbye",
+		"好的", "OK", "ok", "知道了", "明白了", "清楚了",
+		"辛苦了", "牛", "赞", "厉害",
+	}
+	for _, p := range phrases {
+		if q == p || strings.HasPrefix(q, p+" ") || strings.HasPrefix(q, p+"。") {
+			return true
+		}
+	}
+	// 只有一个表情或极短无意义内容
+	if utf8.RuneCountInString(q) <= 2 && (strings.ContainsAny(q, "👍😊😀🙏🎉👋") || q == "。" || q == "。。") {
+		return true
+	}
+	return false
+}
+
+func isListQuery(q string) bool {
+	patterns := []string{
+		"有哪些知识库", "知识库有哪些", "有什么知识库",
+		"有哪些文档", "文档有哪些", "有什么文档",
+		"有哪些文件", "文件有哪些", "上传了哪些",
+		"列出", "列举", "列表", "清单",
+	}
+	for _, p := range patterns {
+		if strings.Contains(q, p) {
+			return true
+		}
+	}
+	return false
+}