Bugfixes

internal/engine/article.go

@@ -55,7 +55,8 @@ func (e *Engine) synthesizeKnowledgeArticle(ctx context.Context, trigger string,
 	// Previously accepted full-text evidence is already learned knowledge. It must
 	// influence the create/update/merge decision, otherwise a later cycle could
 	// skip before it ever sees the external facts it learned in an earlier cycle.
-	planningResearch := uniqueResearchEvidence(append(filterUsableResearchEvidence(initialResearch), e.researchEvidenceForSources(sources)...))
+	initialResearch = e.filterResearchEvidenceForThinking(filterUsableResearchEvidence(initialResearch), categoriesFromArticleSources(sources))
+	planningResearch := uniqueResearchEvidence(append(initialResearch, e.researchEvidenceForSources(sources)...))
 	e.Broker.Publish(model.Activity{Type: "article.plan.started", Source: "brain", Phase: "knowledge-planning", NodeIDs: nodeIDsFromArticleSources(sources), Message: fmt.Sprintf("%d Quellen werden auf einen echten Wissensmehrwert geprüft", len(sources)), Strength: .84, Metadata: map[string]any{"trigger": trigger, "productive_sources": productionCount, "ai_sources": aiCount, "production_ratio": productionRatio, "generation_depth": generationDepth, "model": e.Cfg.ChatModel, "learned_research_sources": len(planningResearch)}})
 
 	var plan model.ArticlePlanDecision
@@ -85,7 +86,7 @@ func (e *Engine) synthesizeKnowledgeArticle(ctx context.Context, trigger string,
 		return articleSynthesisOutcome{Skipped: true, Reason: "equivalent_staging_draft", Action: plan.Action}, nil
 	}
 
-	newResearchResults := filterUsableResearchEvidence(initialResearch)
+	newResearchResults := initialResearch
 	if len(newResearchResults) > 0 {
 		e.addResearchToSources(selected, newResearchResults)
 		e.learnResearchEvidence(ctx, newResearchResults)
@@ -184,13 +185,13 @@ func (e *Engine) selectArticleSources(seeds []model.Node) []articleSource {
 			direct[edge.Source] += math.Max(.2, math.Max(edge.Confidence, edge.Weight))
 		}
 	}
-	filters := e.thinkingCategories()
+	filter := e.effectiveThinkingFilter()
 	var production, ai []articleSource
 	for _, node := range snapshot.Nodes {
 		if node.Kind != "knowledge" && node.Kind != "ai-think" {
 			continue
 		}
-		if !matchesCategories(node, filters) {
+		if !filter.Matches(node) {
 			continue
 		}
 		depth := nodeGenerationDepth(node)
@@ -1093,7 +1094,7 @@ func (e *Engine) addRuntimeArticleNode(articleID string, sources []articleSource
 		ID: nodeID, Kind: "ai-think", Label: draft.Title, Summary: clamp(strings.TrimSpace(draft.Text)+"\n\n"+formatArticleAnswer(draft), 1400),
 		Status: "staging", Origin: "knowledge-staging", ExternalID: articleID, URI: "brain://article/" + articleID,
 		Categories: unique(append([]string{"AI-THINK", "AI-Staging", "AI-Synthesis"}, draft.Categories...)), Keywords: unique(draft.Keywords), Weight: 1.45,
-		Metadata: map[string]any{"subtype": "knowledge_synthesis", "action": plan.Action, "target_node_id": plan.TargetArticleID, "generation_depth": generationDepth, "confidence": draft.Confidence, "source_node_ids": nodeIDsFromArticleSources(sources), "productive_source_count": productionCount, "ai_source_count": aiCount, "production_ratio": productionRatio}, UpdatedAt: now,
+		Metadata: map[string]any{"subtype": "knowledge_synthesis", "action": plan.Action, "target_node_id": plan.TargetArticleID, "generation_depth": generationDepth, "confidence": draft.Confidence, "source_node_ids": nodeIDsFromArticleSources(sources), "productive_source_count": productionCount, "ai_source_count": aiCount, "production_ratio": productionRatio, "source": "Neural Brain / " + e.Cfg.ChatModel + " (Knowledge Synthesis)"}, UpdatedAt: now,
 	}
 	e.Graph.UpsertNode(node)
 	for _, source := range sources {
@@ -1116,7 +1117,7 @@ func (e *Engine) learnRuntimeArticle(ctx context.Context, articleID string) {
 	}
 	nodeID := graph.ID("knowledge", articleID)
 	node, ok := e.Graph.GetNode(nodeID)
-	if !ok || !matchesCategories(node, e.learningCategories()) {
+	if !ok || !e.effectiveLearningFilter().Matches(node) {
 		return
 	}
 	text := embeddingText(node)
@@ -1208,6 +1209,18 @@ func researchResultNode(id string, result model.ResearchResult, evidencePath, co
 	return model.Node{ID: id, Kind: "external", Label: result.Title, Summary: clamp(content, 1800), Status: "research", Origin: "research", ExternalID: result.URL, URI: result.URL, Categories: unique(categories), Weight: weight, Metadata: metadata, UpdatedAt: time.Now().UTC()}
 }
 
+func (e *Engine) filterResearchEvidenceForThinking(results []model.ResearchResult, categories []string) []model.ResearchResult {
+	filter := e.effectiveThinkingFilter()
+	out := make([]model.ResearchResult, 0, len(results))
+	for _, result := range results {
+		node := model.Node{Kind: "external", Origin: "research", URI: result.URL, ExternalID: result.URL, Categories: categories}
+		if filter.Matches(node) {
+			out = append(out, result)
+		}
+	}
+	return out
+}
+
 func formatArticleAnswer(draft model.KnowledgeArticleDraft) string {
 	var b strings.Builder
 	b.WriteString(strings.TrimSpace(draft.Answer))
@@ -1432,25 +1445,7 @@ func categoryAffinity(node model.Node, seeds []model.Node) float64 {
 }
 
 func matchesCategories(node model.Node, filters []string) bool {
-	if len(filters) == 0 {
-		return true
-	}
-	wanted := map[string]bool{}
-	for _, filter := range filters {
-		wanted[strings.ToLower(strings.TrimSpace(filter))] = true
-	}
-	if wanted["*"] {
-		return true
-	}
-	if len(node.Categories) == 0 {
-		return wanted["__uncategorized__"]
-	}
-	for _, category := range node.Categories {
-		if wanted[strings.ToLower(strings.TrimSpace(category))] {
-			return true
-		}
-	}
-	return false
+	return (graph.NodeFilter{Categories: filters}).Matches(node)
 }
 
 func metadataString(metadata map[string]any, key string) string {