Files
Enterprise-Knowledge-Base/internal/application/service/knowledge_post_process.go
T
wizardchen beca2b89a3 feat(observability): extend Langfuse tracing across asynq pipeline
Previously the Langfuse integration only traced in-process HTTP requests
(chat / search / eval), so file uploads and every downstream asynq task
(document parse, chunk embedding, OCR/VLM, summary / question gen, wiki
ingest, datasource sync, etc.) produced either disconnected shallow
traces or no observation at all.

This change threads one trace end-to-end:

- tracer: add SPAN observation type and StartSpan; add ResumeTrace so a
  worker can attach to an upstream trace without emitting a duplicate
  trace-create; StartGeneration now auto-picks parentObservationId from
  ctx so nested trace -> span -> generation trees render correctly.
- types.TracingContext + LangfuseTracingCarrier: embed on all 17 asynq
  payloads so trace_id / parent_obs_id / user_id / session_id serialise
  into every job.
- langfuse.InjectTracing: injected at 28 enqueue sites before json.Marshal
  so the HTTP-layer trace survives the Redis hop.
- langfuse.AsynqMiddleware: mux.Use hook that peeks the payload, either
  resumes the upstream trace or opens a standalone asynq.<type> trace
  for scheduled jobs, and wraps the handler in a SPAN with task metadata
  (id / queue / retry / payload_bytes) plus ERROR level on failure.
- GinMiddleware.shouldTrace: whitelist ingestion / knowledge-mutation /
  FAQ / wiki / datasource endpoints so the root trace actually starts.
- Tests: tracer_test.go covers span nesting, error status, and
  ResumeTrace no-trace-create guarantee; asynq_test.go covers
  InjectTracing round-trip, middleware resume path, and standalone
  trace fallback.
- Docs: docs/Langfuse\u96c6\u6210.md now lists the covered task types
  and documents the cross-process propagation model.

No behavioural change when Langfuse is disabled (all new code paths are
no-ops and carriers serialise to empty strings with omitempty).
2026-04-24 13:16:47 +08:00

199 lines
7.2 KiB
Go

package service
import (
"context"
"encoding/json"
"fmt"
"time"
"github.com/Tencent/WeKnora/internal/logger"
"github.com/Tencent/WeKnora/internal/tracing/langfuse"
"github.com/Tencent/WeKnora/internal/types"
"github.com/Tencent/WeKnora/internal/types/interfaces"
"github.com/hibiken/asynq"
"github.com/redis/go-redis/v9"
)
// KnowledgePostProcessService acts as an orchestrator for all post-processing tasks
// after a document has been parsed and split into chunks (including multimodal OCR/Caption).
type KnowledgePostProcessService struct {
knowledgeRepo interfaces.KnowledgeRepository
kbService interfaces.KnowledgeBaseService
chunkService interfaces.ChunkService
taskEnqueuer interfaces.TaskEnqueuer
redisClient *redis.Client
}
func NewKnowledgePostProcessService(
knowledgeRepo interfaces.KnowledgeRepository,
kbService interfaces.KnowledgeBaseService,
chunkService interfaces.ChunkService,
taskEnqueuer interfaces.TaskEnqueuer,
redisClient *redis.Client,
) interfaces.TaskHandler {
return &KnowledgePostProcessService{
knowledgeRepo: knowledgeRepo,
kbService: kbService,
chunkService: chunkService,
taskEnqueuer: taskEnqueuer,
redisClient: redisClient,
}
}
// Handle implements asynq handler for TypeKnowledgePostProcess.
func (s *KnowledgePostProcessService) Handle(ctx context.Context, task *asynq.Task) error {
var payload types.KnowledgePostProcessPayload
if err := json.Unmarshal(task.Payload(), &payload); err != nil {
return fmt.Errorf("unmarshal knowledge post process payload: %w", err)
}
logger.Infof(ctx, "[KnowledgePostProcess] Orchestrating post processing for knowledge: %s", payload.KnowledgeID)
ctx = context.WithValue(ctx, types.TenantIDContextKey, payload.TenantID)
if payload.Language != "" {
ctx = context.WithValue(ctx, types.LanguageContextKey, payload.Language)
}
// 1. Fetch Knowledge and KB
knowledge, err := s.knowledgeRepo.GetKnowledgeByIDOnly(ctx, payload.KnowledgeID)
if err != nil {
return fmt.Errorf("get knowledge %s: %w", payload.KnowledgeID, err)
}
if knowledge == nil {
logger.Warnf(ctx, "[KnowledgePostProcess] Knowledge %s not found, aborting.", payload.KnowledgeID)
return nil
}
kb, err := s.kbService.GetKnowledgeBaseByIDOnly(ctx, payload.KnowledgeBaseID)
if err != nil || kb == nil {
return fmt.Errorf("get knowledge base %s: %w", payload.KnowledgeBaseID, err)
}
// 2. Fetch all chunks
chunks, err := s.chunkService.ListChunksByKnowledgeID(ctx, payload.KnowledgeID)
if err != nil {
return fmt.Errorf("list chunks for knowledge %s: %w", payload.KnowledgeID, err)
}
// Gather all text-like chunks (including newly added OCR and Caption from multimodal tasks)
var textChunks []*types.Chunk
for _, c := range chunks {
if c.ChunkType == types.ChunkTypeText || c.ChunkType == types.ChunkTypeImageOCR || c.ChunkType == types.ChunkTypeImageCaption {
textChunks = append(textChunks, c)
}
}
// 3. Update ParseStatus to Completed
// (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)
if knowledge.ParseStatus == types.ParseStatusProcessing {
knowledge.ParseStatus = types.ParseStatusCompleted
knowledge.UpdatedAt = time.Now()
// Setup summary status
if len(textChunks) > 0 {
knowledge.SummaryStatus = types.SummaryStatusPending
} else {
knowledge.SummaryStatus = types.SummaryStatusNone
}
if err := s.knowledgeRepo.UpdateKnowledge(ctx, knowledge); err != nil {
logger.Warnf(ctx, "[KnowledgePostProcess] Failed to update knowledge status to completed: %v", err)
} else {
logger.Infof(ctx, "[KnowledgePostProcess] Knowledge %s marked as completed.", payload.KnowledgeID)
}
}
// 4. Spawn Summary and Question Tasks
if len(textChunks) > 0 {
s.enqueueSummaryGenerationTask(ctx, payload)
// Question generation only makes sense for RAG indexing (improves chunk recall).
// Skip when only Wiki/Graph is enabled without vector/keyword search.
if kb.NeedsEmbeddingModel() {
s.enqueueQuestionGenerationIfEnabled(ctx, payload, kb)
}
}
// 5. Spawn Graph RAG Tasks — only when graph indexing is enabled in IndexingStrategy
if kb.IsGraphEnabled() {
logger.Infof(ctx, "[KnowledgePostProcess] Spawning Graph RAG extract tasks for %d text-like chunks", len(textChunks))
for _, chunk := range textChunks {
err := NewChunkExtractTask(ctx, s.taskEnqueuer, payload.TenantID, chunk.ID, kb.SummaryModelID)
if err != nil {
logger.Errorf(ctx, "[KnowledgePostProcess] Failed to create chunk extract task for %s: %v", chunk.ID, err)
}
}
}
// 6. Spawn Wiki Ingest Task if wiki indexing is enabled in IndexingStrategy
if kb.IndexingStrategy.WikiEnabled && len(textChunks) > 0 {
EnqueueWikiIngest(ctx, s.taskEnqueuer, s.redisClient, payload.TenantID, payload.KnowledgeBaseID, payload.KnowledgeID)
logger.Infof(ctx, "[KnowledgePostProcess] Enqueued wiki ingest task for %s", payload.KnowledgeID)
}
return nil
}
func (s *KnowledgePostProcessService) enqueueSummaryGenerationTask(ctx context.Context, payload types.KnowledgePostProcessPayload) {
if s.taskEnqueuer == nil {
return
}
taskPayload := types.SummaryGenerationPayload{
TenantID: payload.TenantID,
KnowledgeBaseID: payload.KnowledgeBaseID,
KnowledgeID: payload.KnowledgeID,
Language: payload.Language,
}
langfuse.InjectTracing(ctx, &taskPayload)
payloadBytes, err := json.Marshal(taskPayload)
if err != nil {
logger.Warnf(ctx, "[KnowledgePostProcess] Failed to marshal summary generation payload: %v", err)
return
}
task := asynq.NewTask(types.TypeSummaryGeneration, payloadBytes, asynq.Queue("low"), asynq.MaxRetry(3))
if _, err := s.taskEnqueuer.Enqueue(task); err != nil {
logger.Warnf(ctx, "[KnowledgePostProcess] Failed to enqueue summary generation for %s: %v", payload.KnowledgeID, err)
} else {
logger.Infof(ctx, "[KnowledgePostProcess] Enqueued summary generation task for %s", payload.KnowledgeID)
}
}
func (s *KnowledgePostProcessService) enqueueQuestionGenerationIfEnabled(ctx context.Context, payload types.KnowledgePostProcessPayload, kb *types.KnowledgeBase) {
if s.taskEnqueuer == nil {
return
}
if kb.QuestionGenerationConfig == nil || !kb.QuestionGenerationConfig.Enabled {
return
}
questionCount := kb.QuestionGenerationConfig.QuestionCount
if questionCount <= 0 {
questionCount = 3
}
if questionCount > 10 {
questionCount = 10
}
taskPayload := types.QuestionGenerationPayload{
TenantID: payload.TenantID,
KnowledgeBaseID: payload.KnowledgeBaseID,
KnowledgeID: payload.KnowledgeID,
QuestionCount: questionCount,
Language: payload.Language,
}
langfuse.InjectTracing(ctx, &taskPayload)
payloadBytes, err := json.Marshal(taskPayload)
if err != nil {
logger.Warnf(ctx, "[KnowledgePostProcess] Failed to marshal question generation payload: %v", err)
return
}
task := asynq.NewTask(types.TypeQuestionGeneration, payloadBytes, asynq.Queue("low"), asynq.MaxRetry(3))
if _, err := s.taskEnqueuer.Enqueue(task); err != nil {
logger.Warnf(ctx, "[KnowledgePostProcess] Failed to enqueue question generation for %s: %v", payload.KnowledgeID, err)
} else {
logger.Infof(ctx, "[KnowledgePostProcess] Enqueued question generation task for %s (count=%d)", payload.KnowledgeID, questionCount)
}
}