e147209e77
This commit introduces the complete wiki feature for WeKnora, enabling AI-powered wiki page generation and management. The implementation includes: **Backend Changes:** - Wiki data model: WikiPage type with support for multiple page types (Summary, Entity, Concept, Index, Log) - Database schema: wiki_pages table with full migration support - WikiPageService: CRUD operations and page management - WikiPageRepository: GORM-based persistence layer - Wiki ingest pipeline: Automated generation of wiki pages from knowledge documents * Summary page generation using LLM * Entity and concept extraction in a single LLM call * Synthesis opportunity detection * Index page rebuilding * Log page maintenance - Wiki boost feature: Enhance chat retrieval with wiki context - Wiki linting: Maintenance and validation utilities - Agent wiki tools: Enable agents to query and interact with wiki pages - Wiki prompts: Comprehensive LLM prompt templates for all wiki generation tasks - Language support: Reuse existing middleware language infrastructure for LLM prompts **Frontend Changes:** - Wiki browser UI: View all wiki pages with filtering and search - Wiki API client: Knowledge base wiki management endpoints - Knowledge base editor: Configure wiki settings (language, auto-ingest, synthesis model) - i18n updates: Support for English, Korean, Russian, and Chinese interfaces **Configuration:** - Container DI: Wire up all wiki services - Router: Register wiki API endpoints - Task handling: Support async wiki ingest tasks **Testing:** - Unit tests for wiki page types - Service layer tests - Endpoint tests for wiki operations - Integration tests with LLM mocking **Documentation:** - Language refactoring analysis and guides - Implementation completion reports - Quick reference guides for developers **Key Features:** ✅ LLM-powered wiki page generation from documents ✅ Multi-language support (9+ languages) ✅ Automatic extraction of entities and concepts ✅ Synthesis opportunity detection ✅ Index and log page maintenance ✅ Progressive wiki building across multiple documents ✅ Agent-based wiki interaction ✅ Chat retrieval enhancement with wiki context ✅ Full frontend UI for wiki browsing Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
188 lines
6.7 KiB
Go
188 lines
6.7 KiB
Go
package service
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import (
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"context"
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"encoding/json"
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"fmt"
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"time"
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"github.com/Tencent/WeKnora/internal/logger"
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"github.com/Tencent/WeKnora/internal/types"
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"github.com/Tencent/WeKnora/internal/types/interfaces"
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"github.com/hibiken/asynq"
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)
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// KnowledgePostProcessService acts as an orchestrator for all post-processing tasks
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// after a document has been parsed and split into chunks (including multimodal OCR/Caption).
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type KnowledgePostProcessService struct {
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knowledgeRepo interfaces.KnowledgeRepository
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kbService interfaces.KnowledgeBaseService
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chunkService interfaces.ChunkService
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taskEnqueuer interfaces.TaskEnqueuer
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}
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func NewKnowledgePostProcessService(
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knowledgeRepo interfaces.KnowledgeRepository,
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kbService interfaces.KnowledgeBaseService,
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chunkService interfaces.ChunkService,
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taskEnqueuer interfaces.TaskEnqueuer,
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) interfaces.TaskHandler {
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return &KnowledgePostProcessService{
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knowledgeRepo: knowledgeRepo,
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kbService: kbService,
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chunkService: chunkService,
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taskEnqueuer: taskEnqueuer,
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}
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}
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// Handle implements asynq handler for TypeKnowledgePostProcess.
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func (s *KnowledgePostProcessService) Handle(ctx context.Context, task *asynq.Task) error {
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var payload types.KnowledgePostProcessPayload
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if err := json.Unmarshal(task.Payload(), &payload); err != nil {
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return fmt.Errorf("unmarshal knowledge post process payload: %w", err)
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}
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logger.Infof(ctx, "[KnowledgePostProcess] Orchestrating post processing for knowledge: %s", payload.KnowledgeID)
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ctx = context.WithValue(ctx, types.TenantIDContextKey, payload.TenantID)
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if payload.Language != "" {
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ctx = context.WithValue(ctx, types.LanguageContextKey, payload.Language)
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}
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// 1. Fetch Knowledge and KB
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knowledge, err := s.knowledgeRepo.GetKnowledgeByIDOnly(ctx, payload.KnowledgeID)
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if err != nil {
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return fmt.Errorf("get knowledge %s: %w", payload.KnowledgeID, err)
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}
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if knowledge == nil {
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logger.Warnf(ctx, "[KnowledgePostProcess] Knowledge %s not found, aborting.", payload.KnowledgeID)
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return nil
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}
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kb, err := s.kbService.GetKnowledgeBaseByIDOnly(ctx, payload.KnowledgeBaseID)
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if err != nil || kb == nil {
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return fmt.Errorf("get knowledge base %s: %w", payload.KnowledgeBaseID, err)
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}
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// 2. Fetch all chunks
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chunks, err := s.chunkService.ListChunksByKnowledgeID(ctx, payload.KnowledgeID)
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if err != nil {
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return fmt.Errorf("list chunks for knowledge %s: %w", payload.KnowledgeID, err)
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}
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// Gather all text-like chunks (including newly added OCR and Caption from multimodal tasks)
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var textChunks []*types.Chunk
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for _, c := range chunks {
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if c.ChunkType == types.ChunkTypeText || c.ChunkType == types.ChunkTypeImageOCR || c.ChunkType == types.ChunkTypeImageCaption {
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textChunks = append(textChunks, c)
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}
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}
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// 3. Update ParseStatus to Completed
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// (Except if it's already completed or if it was marked as failed/deleting, but we'll just set it to completed if it's processing)
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if knowledge.ParseStatus == types.ParseStatusProcessing {
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knowledge.ParseStatus = types.ParseStatusCompleted
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knowledge.UpdatedAt = time.Now()
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// Setup summary status
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if len(textChunks) > 0 {
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knowledge.SummaryStatus = types.SummaryStatusPending
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} else {
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knowledge.SummaryStatus = types.SummaryStatusNone
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}
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if err := s.knowledgeRepo.UpdateKnowledge(ctx, knowledge); err != nil {
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logger.Warnf(ctx, "[KnowledgePostProcess] Failed to update knowledge status to completed: %v", err)
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} else {
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logger.Infof(ctx, "[KnowledgePostProcess] Knowledge %s marked as completed.", payload.KnowledgeID)
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}
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}
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// 4. Spawn Summary and Question Tasks
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if len(textChunks) > 0 {
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s.enqueueSummaryGenerationTask(ctx, payload)
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s.enqueueQuestionGenerationIfEnabled(ctx, payload, kb)
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}
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// 5. Spawn Graph RAG Tasks
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if kb.ExtractConfig != nil && kb.ExtractConfig.Enabled {
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logger.Infof(ctx, "[KnowledgePostProcess] Spawning Graph RAG extract tasks for %d text-like chunks", len(textChunks))
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for _, chunk := range textChunks {
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err := NewChunkExtractTask(ctx, s.taskEnqueuer, payload.TenantID, chunk.ID, kb.SummaryModelID)
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if err != nil {
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logger.Errorf(ctx, "[KnowledgePostProcess] Failed to create chunk extract task for %s: %v", chunk.ID, err)
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}
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}
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}
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// 6. Spawn Wiki Ingest Task for wiki-type knowledge bases
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if kb.Type == types.KnowledgeBaseTypeWiki && len(textChunks) > 0 {
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EnqueueWikiIngest(ctx, s.taskEnqueuer, payload.TenantID, payload.KnowledgeBaseID, payload.KnowledgeID)
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logger.Infof(ctx, "[KnowledgePostProcess] Enqueued wiki ingest task for %s", payload.KnowledgeID)
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}
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return nil
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}
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func (s *KnowledgePostProcessService) enqueueSummaryGenerationTask(ctx context.Context, payload types.KnowledgePostProcessPayload) {
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if s.taskEnqueuer == nil {
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return
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}
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taskPayload := types.SummaryGenerationPayload{
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TenantID: payload.TenantID,
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KnowledgeBaseID: payload.KnowledgeBaseID,
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KnowledgeID: payload.KnowledgeID,
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Language: payload.Language,
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}
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payloadBytes, err := json.Marshal(taskPayload)
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if err != nil {
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logger.Warnf(ctx, "[KnowledgePostProcess] Failed to marshal summary generation payload: %v", err)
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return
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}
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task := asynq.NewTask(types.TypeSummaryGeneration, payloadBytes, asynq.Queue("low"), asynq.MaxRetry(3))
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if _, err := s.taskEnqueuer.Enqueue(task); err != nil {
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logger.Warnf(ctx, "[KnowledgePostProcess] Failed to enqueue summary generation for %s: %v", payload.KnowledgeID, err)
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} else {
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logger.Infof(ctx, "[KnowledgePostProcess] Enqueued summary generation task for %s", payload.KnowledgeID)
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}
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}
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func (s *KnowledgePostProcessService) enqueueQuestionGenerationIfEnabled(ctx context.Context, payload types.KnowledgePostProcessPayload, kb *types.KnowledgeBase) {
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if s.taskEnqueuer == nil {
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return
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}
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if kb.QuestionGenerationConfig == nil || !kb.QuestionGenerationConfig.Enabled {
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return
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}
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questionCount := kb.QuestionGenerationConfig.QuestionCount
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if questionCount <= 0 {
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questionCount = 3
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}
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if questionCount > 10 {
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questionCount = 10
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}
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taskPayload := types.QuestionGenerationPayload{
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TenantID: payload.TenantID,
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KnowledgeBaseID: payload.KnowledgeBaseID,
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KnowledgeID: payload.KnowledgeID,
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QuestionCount: questionCount,
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Language: payload.Language,
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}
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payloadBytes, err := json.Marshal(taskPayload)
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if err != nil {
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logger.Warnf(ctx, "[KnowledgePostProcess] Failed to marshal question generation payload: %v", err)
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return
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}
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task := asynq.NewTask(types.TypeQuestionGeneration, payloadBytes, asynq.Queue("low"), asynq.MaxRetry(3))
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if _, err := s.taskEnqueuer.Enqueue(task); err != nil {
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logger.Warnf(ctx, "[KnowledgePostProcess] Failed to enqueue question generation for %s: %v", payload.KnowledgeID, err)
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} else {
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logger.Infof(ctx, "[KnowledgePostProcess] Enqueued question generation task for %s (count=%d)", payload.KnowledgeID, questionCount)
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}
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}
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