feat: add knowledge management functionality with CRUD operations and database schema

- Implemented KnowledgeHandler for managing knowledge groups and items, including listing, creating, updating, and deleting operations.
- Added database migration scripts to create necessary tables for knowledge management, including knowledge_groups, knowledge_items, knowledge_parse_tasks, and knowledge_chunks_meta.
- Introduced prompt_rule_knowledge_groups table to associate prompt rules with knowledge groups.

server/internal/tenant/app/template_service.go

@@ -22,6 +22,7 @@ type TemplateService struct {
 	pool            *pgxpool.Pool
 	templates       repository.TemplateRepository
 	llm             llm.Client
+	knowledge       *KnowledgeService
 	streams         *stream.GenerationHub
 	streamEnabled   bool
 	articleTimeout  time.Duration
@@ -48,6 +49,7 @@ func NewTemplateService(
 	pool *pgxpool.Pool,
 	templates repository.TemplateRepository,
 	llmClient llm.Client,
+	knowledge *KnowledgeService,
 	streams *stream.GenerationHub,
 	cfg config.GenerationConfig,
 	llmMaxOutputTokens int64,
@@ -71,6 +73,7 @@ func NewTemplateService(
 		pool:            pool,
 		templates:       templates,
 		llm:             llmClient,
+		knowledge:       knowledge,
 		streams:         streams,
 		streamEnabled:   cfg.StreamEnabled,
 		articleTimeout:  articleTimeout,
@@ -140,7 +143,7 @@ func (s *TemplateService) Detail(ctx context.Context, id int64) (*TemplateDetail
 		return nil, response.ErrNotFound(40410, "template_not_found", "template not found")
 	}
 
-		detail := &TemplateDetail{
+	detail := &TemplateDetail{
 		TemplateListItem: TemplateListItem{
 			ID:               record.ID,
 			Scope:            record.Scope,
@@ -454,7 +457,26 @@ func (s *TemplateService) executeGeneration(ctx context.Context, job generationJ
 		StartedAt: &now,
 	})
 
-	prompt := buildGenerationPrompt(job.TemplateKey, job.TemplateName, job.PromptTemplate, job.Params)
+	knowledgePrompt := ""
+	if knowledgeGroupIDs := extractKnowledgeGroupIDs(job.Params["knowledge_group_ids"]); len(knowledgeGroupIDs) > 0 {
+		if s.knowledge == nil {
+			s.failGeneration(ctx, job, title, "knowledge_resolve", fmt.Errorf("knowledge service is not configured"))
+			return
+		}
+		knowledgeContext, resolveErr := s.knowledge.ResolveContext(
+			ctx,
+			job.TenantID,
+			knowledgeGroupIDs,
+			buildGenerationKnowledgeQuery(job.Params),
+		)
+		if resolveErr != nil {
+			s.failGeneration(ctx, job, title, "knowledge_resolve", resolveErr)
+			return
+		}
+		knowledgePrompt = s.knowledge.RenderPromptSection(knowledgeContext)
+	}
+
+	prompt := buildGenerationPrompt(job.TemplateKey, job.TemplateName, job.PromptTemplate, job.Params, knowledgePrompt)
 	generateReq := llm.GenerateRequest{
 		Prompt:          prompt,
 		Timeout:         s.articleTimeout,
@@ -604,6 +626,8 @@ func generationFailureStageLabel(stage string) string {
 		return "任务入队失败"
 	case "llm_generate":
 		return "AI 正文生成失败"
+	case "knowledge_resolve":
+		return "知识库检索失败"
 	case "persist_begin_tx":
 		return "写入生成结果事务启动失败"
 	case "persist_create_version":
@@ -684,3 +708,29 @@ func nullableJSONString(value []byte) *string {
 	text := string(value)
 	return &text
 }
+
+func extractKnowledgeGroupIDs(value interface{}) []int64 {
+	switch typed := value.(type) {
+	case []int64:
+		return normalizeInt64IDs(typed)
+	case []interface{}:
+		ids := make([]int64, 0, len(typed))
+		for _, item := range typed {
+			switch raw := item.(type) {
+			case int64:
+				ids = append(ids, raw)
+			case int32:
+				ids = append(ids, int64(raw))
+			case int:
+				ids = append(ids, int64(raw))
+			case float64:
+				ids = append(ids, int64(raw))
+			case float32:
+				ids = append(ids, int64(raw))
+			}
+		}
+		return normalizeInt64IDs(ids)
+	default:
+		return nil
+	}
+}