feat: support semantic search in AI chat and embedding ability

internal/base/constant/ai_config.go

@@ -33,6 +33,7 @@ const (
 - get_tags: 搜索标签信息
 - get_tag_detail: 获取特定标签的详细信息
 - get_user: 搜索用户信息
+- semantic_search: 通过语义相似度搜索问题和答案。当用户的问题与现有内容概念相关但可能不匹配确切关键词时使用此工具。当 get_questions 关键词搜索返回较差结果时，请使用 semantic_search。
 
 请根据用户的问题智能地使用这些工具来提供准确的答案。如果需要查询系统信息，请先使用相应的工具获取数据。`
 	DefaultAIPromptConfigEnUS = `You are an intelligent assistant that can help users query information in the system. User question: %s
@@ -44,6 +45,7 @@ You can use the following tools to query system information:
 - get_tags: Search for tag information
 - get_tag_detail: Get detailed information about a specific tag
 - get_user: Search for user information
+- semantic_search: Search questions and answers by semantic meaning. Use this when the user's question relates conceptually to existing content but may not match exact keywords. When get_questions keyword search returns poor results, use semantic_search instead.
 
 Please intelligently use these tools based on the user's question to provide accurate answers. If you need to query system information, please use the appropriate tools to get the data first.`
 )

internal/controller/ai_controller.go

@@ -446,6 +446,7 @@ func (c *AIController) handleAIConversation(ctx *gin.Context, w http.ResponseWri
 		toolCalls, newMessages, finished, aiResponse := c.processAIStream(ctx, w, id, conversationCtx.Model, client, aiReq, messages)
 		messages = newMessages
 
+		log.Debugf("Round %d: toolCalls=%v", round+1, toolCalls)
 		if aiResponse != "" {
 			conversationCtx.Messages = append(conversationCtx.Messages, &ai_conversation.ConversationMessage{
 				Role:    "assistant",
@@ -497,6 +498,10 @@ func (c *AIController) processAIStream(
 			break
 		}
 
+		if len(response.Choices) == 0 {
+			continue
+		}
+
 		choice := response.Choices[0]
 
 		if len(choice.Delta.ToolCalls) > 0 {
@@ -735,6 +740,8 @@ func (c *AIController) callMCPTool(ctx context.Context, toolName string, argumen
 		result, err = c.mcpController.MCPTagDetailsHandler()(ctx, request)
 	case "get_user":
 		result, err = c.mcpController.MCPUserDetailsHandler()(ctx, request)
+	case "semantic_search":
+		result, err = c.mcpController.MCPSemanticSearchHandler()(ctx, request)
 	default:
 		return "", fmt.Errorf("unknown tool: %s", toolName)
 	}

internal/controller/mcp_controller.go

@@ -31,11 +31,13 @@ import (
 	answercommon "github.com/apache/answer/internal/service/answer_common"
 	"github.com/apache/answer/internal/service/comment"
 	"github.com/apache/answer/internal/service/content"
+	"github.com/apache/answer/internal/service/embedding"
 	"github.com/apache/answer/internal/service/feature_toggle"
 	questioncommon "github.com/apache/answer/internal/service/question_common"
 	"github.com/apache/answer/internal/service/siteinfo_common"
 	tagcommonser "github.com/apache/answer/internal/service/tag_common"
 	usercommon "github.com/apache/answer/internal/service/user_common"
+	"github.com/apache/answer/plugin"
 	"github.com/mark3labs/mcp-go/mcp"
 	"github.com/segmentfault/pacman/log"
 )
@@ -49,6 +51,7 @@ type MCPController struct {
 	userCommon       *usercommon.UserCommon
 	answerRepo       answercommon.AnswerRepo
 	featureToggleSvc *feature_toggle.FeatureToggleService
+	embeddingService *embedding.EmbeddingService
 }
 
 // NewMCPController new site info controller.
@@ -61,6 +64,7 @@ func NewMCPController(
 	userCommon *usercommon.UserCommon,
 	answerRepo answercommon.AnswerRepo,
 	featureToggleSvc *feature_toggle.FeatureToggleService,
+	embeddingService *embedding.EmbeddingService,
 ) *MCPController {
 	return &MCPController{
 		searchService:    searchService,
@@ -71,6 +75,7 @@ func NewMCPController(
 		userCommon:       userCommon,
 		answerRepo:       answerRepo,
 		featureToggleSvc: featureToggleSvc,
+		embeddingService: embeddingService,
 	}
 }
 
@@ -349,3 +354,131 @@ func (c *MCPController) MCPUserDetailsHandler() func(ctx context.Context, reques
 		return mcp.NewToolResultText(string(res)), nil
 	}
 }
+
+func (c *MCPController) MCPSemanticSearchHandler() func(ctx context.Context, request mcp.CallToolRequest) (*mcp.CallToolResult, error) {
+	return func(ctx context.Context, request mcp.CallToolRequest) (*mcp.CallToolResult, error) {
+		if err := c.ensureMCPEnabled(ctx); err != nil {
+			return nil, err
+		}
+		cond := schema.NewMCPSemanticSearchCond(request)
+		if len(cond.Query) == 0 {
+			return mcp.NewToolResultText("Query is required for semantic search."), nil
+		}
+
+		siteGeneral, err := c.siteInfoService.GetSiteGeneral(ctx)
+		if err != nil {
+			log.Errorf("get site general info failed: %v", err)
+			return nil, err
+		}
+
+		results, err := c.embeddingService.SearchSimilar(ctx, cond.Query, cond.TopK)
+		if err != nil {
+			log.Errorf("semantic search failed: %v", err)
+			return mcp.NewToolResultText("Semantic search is not available. Embedding may not be configured."), nil
+		}
+		if len(results) == 0 {
+			return mcp.NewToolResultText("No semantically similar content found."), nil
+		}
+
+		resp := make([]*schema.MCPSemanticSearchResp, 0, len(results))
+		for _, r := range results {
+			var meta plugin.VectorSearchMetadata
+			_ = json.Unmarshal([]byte(r.Metadata), &meta)
+
+			item := &schema.MCPSemanticSearchResp{
+				ObjectID:   r.ObjectID,
+				ObjectType: r.ObjectType,
+				Score:      r.Score,
+			}
+
+			// Compose link from metadata
+			if r.ObjectType == "answer" && meta.AnswerID != "" {
+				item.Link = fmt.Sprintf("%s/questions/%s/%s", siteGeneral.SiteUrl, meta.QuestionID, meta.AnswerID)
+			} else {
+				item.Link = fmt.Sprintf("%s/questions/%s", siteGeneral.SiteUrl, meta.QuestionID)
+			}
+
+			// Query content from DB using IDs stored in metadata
+			if r.ObjectType == "question" {
+				question, qErr := c.questioncommon.Info(ctx, meta.QuestionID, "")
+				if qErr != nil {
+					log.Warnf("get question %s for semantic search failed: %v", meta.QuestionID, qErr)
+				} else {
+					item.Title = question.Title
+					item.Content = question.Content
+				}
+
+				// Fetch answers by ID from metadata
+				for _, a := range meta.Answers {
+					answerEntity, exist, aErr := c.answerRepo.GetAnswer(ctx, a.AnswerID)
+					if aErr != nil || !exist {
+						continue
+					}
+					answerItem := &schema.MCPSemanticSearchAnswer{
+						AnswerID: a.AnswerID,
+						Content:  answerEntity.OriginalText,
+					}
+					// Fetch comments on this answer from DB
+					for _, ac := range a.Comments {
+						cmt, cExist, cErr := c.commentRepo.GetComment(ctx, ac.CommentID)
+						if cErr == nil && cExist {
+							answerItem.Comments = append(answerItem.Comments, &schema.MCPSemanticSearchComment{
+								CommentID: ac.CommentID,
+								Content:   cmt.OriginalText,
+							})
+						}
+					}
+					item.Answers = append(item.Answers, answerItem)
+				}
+
+				// Fetch question comments from DB
+				for _, qc := range meta.Comments {
+					cmt, cExist, cErr := c.commentRepo.GetComment(ctx, qc.CommentID)
+					if cErr == nil && cExist {
+						item.Comments = append(item.Comments, &schema.MCPSemanticSearchComment{
+							CommentID: qc.CommentID,
+							Content:   cmt.OriginalText,
+						})
+					}
+				}
+			} else if r.ObjectType == "answer" {
+				// Fetch question title for context
+				question, qErr := c.questioncommon.Info(ctx, meta.QuestionID, "")
+				if qErr == nil {
+					item.Title = question.Title
+				}
+
+				// Fetch answer content from DB
+				if meta.AnswerID != "" {
+					answerEntity, exist, aErr := c.answerRepo.GetAnswer(ctx, meta.AnswerID)
+					if aErr == nil && exist {
+						item.Content = answerEntity.OriginalText
+					}
+				} else if len(meta.Answers) > 0 {
+					answerEntity, exist, aErr := c.answerRepo.GetAnswer(ctx, meta.Answers[0].AnswerID)
+					if aErr == nil && exist {
+						item.Content = answerEntity.OriginalText
+					}
+				}
+
+				// Fetch answer comments from DB
+				if len(meta.Answers) > 0 {
+					for _, ac := range meta.Answers[0].Comments {
+						cmt, cExist, cErr := c.commentRepo.GetComment(ctx, ac.CommentID)
+						if cErr == nil && cExist {
+							item.Comments = append(item.Comments, &schema.MCPSemanticSearchComment{
+								CommentID: ac.CommentID,
+								Content:   cmt.OriginalText,
+							})
+						}
+					}
+				}
+			}
+
+			resp = append(resp, item)
+		}
+
+		data, _ := json.Marshal(resp)
+		return mcp.NewToolResultText(string(data)), nil
+	}
+}