From a10225d74cb3aa4629d76c3061925ed770b8fe92 Mon Sep 17 00:00:00 2001
From: groot <git@send.nrw>
Date: Wed, 29 Jul 2026 14:53:12 +0200
Subject: [PATCH] =?UTF-8?q?AI-Label=20hinzugef=C3=BCgt?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 README.md                             |  6 ++++
 UPGRADE.md                            |  5 +++
 internal/agent/agent.go               |  2 +-
 internal/agent/agent_test.go          |  2 +-
 internal/agent/policy.go              | 43 +++++++++++++++++++++++--
 internal/agent/policy_test.go         | 45 ++++++++++++++++++++++++---
 internal/config/config.go             | 21 +++++++++----
 internal/config/config_test.go        | 19 +++++++++++
 internal/web/server.go                |  2 +-
 internal/web/templates/dashboard.html |  2 +-
 10 files changed, 129 insertions(+), 18 deletions(-)

diff --git a/README.md b/README.md
index 3eeee85..7ef6236 100644
--- a/README.md
+++ b/README.md
@@ -225,6 +225,7 @@ COMMUNICATION_STYLE=formal
 COMMUNICATION_SALUTATION=Guten Tag,
 COMMUNICATION_CLOSING=Mit freundlichen Grüßen
 COMMUNICATION_SIGNATURE=IT-Service
+AI_CONTENT_LABEL_ENABLED=true
 ```
 
 Ein Auto-Reply ist nur erlaubt, wenn `language` und `communication_style` des freigegebenen Knowledge-Dokuments exakt zur aktiven Policy passen. Das Feld `answer` enthält nur den fachlich freigegebenen Nachrichtentext; Anrede, Grußformel und Signatur werden von der Go-Policy zentral ergänzt. Damit kann das Modell diese Kommunikationsvorgaben nicht überschreiben.
@@ -538,3 +539,8 @@ Index-Modi:
 `/api/status` und das Dashboard zeigen unter anderem Snapshot-Zeitpunkt, letzten Delta-Scan, geänderte/gelöschte Dateien, wiederverwendete Vektoren, Embedding-Batchgröße und Scanintervall. Das komplette Vektorindex-Map wird bei einer Suche nicht mehr pro Ticket kopiert; Suchläufe lesen den warmen Index direkt unter einem Read-Lock.
 
 Beim allerersten Aufbau ohne Snapshot startet das Dashboard weiterhin sofort und zeigt Scan-/Embedding-Fortschritt. Die Ticketverarbeitung wartet in diesem Fall, bis der erste konsistente Index fertig ist.
+
+
+### KI-Kennzeichnung automatischer Antworten
+
+Mit `AI_CONTENT_LABEL_ENABLED=true` wird der konfigurierte TrustedNet-Kennzeichnungsblock unveraendert an den Anfang jeder automatisch vom Agenten ausgewaehlten Antwort gesetzt. Da der Badge HTML verwendet, werden auch Plaintext-KB-Antworten fuer den Versand sicher nach HTML escaped.
diff --git a/UPGRADE.md b/UPGRADE.md
index 5bb4591..9c05272 100644
--- a/UPGRADE.md
+++ b/UPGRADE.md
@@ -182,3 +182,8 @@ Normaler Neustart in `incremental`:
 6. Geänderten Snapshot atomar ersetzen.
 
 `KNOWLEDGE_INDEX_MODE=rebuild` erzwingt einen vollständigen Quellen-Scan. `readonly` verwendet ausschließlich den vorhandenen Snapshot und führt keine lokalen Delta-Scans aus.
+
+
+## KI-Kennzeichnung
+
+Automatische Antworten tragen standardmaessig den TrustedNet-Kennzeichnungsblock am Anfang. Zum expliziten Aktivieren/Deaktivieren: `AI_CONTENT_LABEL_ENABLED=true|false`.
diff --git a/internal/agent/agent.go b/internal/agent/agent.go
index a8034f9..a04f485 100644
--- a/internal/agent/agent.go
+++ b/internal/agent/agent.go
@@ -56,7 +56,7 @@ type Service struct {
 }
 
 func New(cfg config.Config, g GLPI, ai AI, k *knowledge.Store, l *learning.Store, s *state.Store, q *queue.Queue, m *metrics.Metrics, contextCollector ContextCollector) *Service {
-	return &Service{cfg: cfg, glpi: g, ai: ai, knowledge: k, learning: l, state: s, q: q, metrics: m, context: contextCollector, policy: NewPolicy(cfg.AutoCategory, cfg.AutoReply, cfg.CategoryConfidence, cfg.ReplyConfidence, cfg.KnowledgeMinScore, cfg.KnowledgeRetrievalFloor, cfg.KnowledgeEvidenceRetrievalWeight, cfg.KnowledgeEvidenceAIWeight, cfg.KnowledgeEvidenceCategoryWeight, cfg.KnowledgeAllowedSources, cfg.KnowledgeAutoReplySources, cfg.CommunicationLanguage, cfg.CommunicationStyle, cfg.CommunicationSalutation, cfg.CommunicationClosing, cfg.CommunicationSignature, cfg.ContextBlockReplyOnError, cfg.ContextBlockReplyOnIncident, cfg.ContextRelevanceMinScore)}
+	return &Service{cfg: cfg, glpi: g, ai: ai, knowledge: k, learning: l, state: s, q: q, metrics: m, context: contextCollector, policy: NewPolicy(cfg.AutoCategory, cfg.AutoReply, cfg.CategoryConfidence, cfg.ReplyConfidence, cfg.KnowledgeMinScore, cfg.KnowledgeRetrievalFloor, cfg.KnowledgeEvidenceRetrievalWeight, cfg.KnowledgeEvidenceAIWeight, cfg.KnowledgeEvidenceCategoryWeight, cfg.KnowledgeAllowedSources, cfg.KnowledgeAutoReplySources, cfg.CommunicationLanguage, cfg.CommunicationStyle, cfg.CommunicationSalutation, cfg.CommunicationClosing, cfg.CommunicationSignature, cfg.AIContentLabelEnabled, cfg.ContextBlockReplyOnError, cfg.ContextBlockReplyOnIncident, cfg.ContextRelevanceMinScore)}
 }
 func (s *Service) Queue() *queue.Queue { return s.q }
 func (s *Service) Start(ctx context.Context) {
diff --git a/internal/agent/agent_test.go b/internal/agent/agent_test.go
index 3d540a4..67ea357 100644
--- a/internal/agent/agent_test.go
+++ b/internal/agent/agent_test.go
@@ -81,7 +81,7 @@ func newTestService(t *testing.T, g *fakeGLPI, d model.Decision, autoReply bool)
 	if err != nil {
 		t.Fatal(err)
 	}
-	cfg := config.Config{DryRun: false, AutoCategory: true, AutoReply: autoReply, CategoryConfidence: .9, ReplyConfidence: .9, KnowledgeMinScore: 0, KnowledgeTopK: 1, CategoryPromptLimit: 20, Workers: 1, GLPIAllowedStatusIDs: []int64{1}, KnowledgeAllowedSources: []string{"internal-kb"}, KnowledgeAutoReplySources: []string{"internal-kb"}, CommunicationLanguage: "de-DE", CommunicationStyle: "formal", CommunicationSalutation: "Guten Tag,", CommunicationClosing: "Mit freundlichen Grüßen", CommunicationSignature: "IT-Service"}
+	cfg := config.Config{DryRun: false, AutoCategory: true, AutoReply: autoReply, CategoryConfidence: .9, ReplyConfidence: .9, KnowledgeMinScore: 0, KnowledgeTopK: 1, CategoryPromptLimit: 20, Workers: 1, GLPIAllowedStatusIDs: []int64{1}, KnowledgeAllowedSources: []string{"internal-kb"}, KnowledgeAutoReplySources: []string{"internal-kb"}, CommunicationLanguage: "de-DE", CommunicationStyle: "formal", CommunicationSalutation: "Guten Tag,", CommunicationClosing: "Mit freundlichen Grüßen", CommunicationSignature: "IT-Service", AIContentLabelEnabled: true}
 	return New(cfg, g, fakeAI{d: d}, k, nil, st, queue.New(8), metrics.New(), nil)
 }
 
diff --git a/internal/agent/policy.go b/internal/agent/policy.go
index 1dfa07c..31d896e 100644
--- a/internal/agent/policy.go
+++ b/internal/agent/policy.go
@@ -7,6 +7,8 @@ import (
 	"github.com/example/glpi-ai-agent/internal/model"
 )
 
+const AIContentLabelHTML = `<a href="https://ai.trustednet.eu/declaration?preset=full&component=text&extent=full&activities=generation&review=expert&lang=de&assurance=selfDeclared&subject=https%3A%2F%2Fglpi.hilden.de&substantialHumanReview=true&editorialResponsibilityConfirmed=true&responsible=Stadt+Hilden&responsibleUrl=https%3A%2F%2Fwww.hilden.de%2Fde%2Fservice%2Fimpressum-datenschutz&customDescription=Die+KI+hat+den+Inhalt+auf+Basis+des+Ticket-Inhaltes+ausgew%C3%A4hlt.+Der+Inhalt+wurde+sachlich+und+fachlich+von+einem+Menschen+erzeugt.&badgeLabel=KI-Beitrag&badgeMessage=Die+KI+hat+die+Antwort+ausgew%C3%A4hlt%2C+jedoch+nicht+verfasst.&leftColor=%23036715&rightColor=%23535454"><img src="https://ai.trustednet.eu/v1/badge.svg?preset=full&component=text&extent=full&activities=generation&review=expert&lang=de&assurance=selfDeclared&subject=https%3A%2F%2Fglpi.hilden.de&substantialHumanReview=true&editorialResponsibilityConfirmed=true&responsible=Stadt+Hilden&responsibleUrl=https%3A%2F%2Fwww.hilden.de%2Fde%2Fservice%2Fimpressum-datenschutz&customDescription=Die+KI+hat+den+Inhalt+auf+Basis+des+Ticket-Inhaltes+ausgew%C3%A4hlt.+Der+Inhalt+wurde+sachlich+und+fachlich+von+einem+Menschen+erzeugt.&badgeLabel=KI-Beitrag&badgeMessage=Die+KI+hat+die+Antwort+ausgew%C3%A4hlt%2C+jedoch+nicht+verfasst.&leftColor=%23036715&rightColor=%23535454&theme=color&link=https%3A%2F%2Fai.trustednet.eu%2Fdeclaration%3Fpreset%3Dfull%26component%3Dtext%26extent%3Dfull%26activities%3Dgeneration%26review%3Dexpert%26lang%3Dde%26assurance%3DselfDeclared%26subject%3Dhttps%253A%252F%252Fglpi.hilden.de%26substantialHumanReview%3Dtrue%26editorialResponsibilityConfirmed%3Dtrue%26responsible%3DStadt%2BHilden%26responsibleUrl%3Dhttps%253A%252F%252Fwww.hilden.de%252Fde%252Fservice%252Fimpressum-datenschutz%26customDescription%3DDie%2BKI%2Bhat%2Bden%2BInhalt%2Bauf%2BBasis%2Bdes%2BTicket-Inhaltes%2Bausgew%25C3%25A4hlt.%2BDer%2BInhalt%2Bwurde%2Bsachlich%2Bund%2Bfachlich%2Bvon%2Beinem%2BMenschen%2Berzeugt.%26badgeLabel%3DKI-Beitrag%26badgeMessage%3DDie%2BKI%2Bhat%2Bdie%2BAntwort%2Bausgew%25C3%25A4hlt%252C%2Bjedoch%2Bnicht%2Bverfasst.%26leftColor%3D%2523036715%26rightColor%3D%2523535454" alt="UCNG"></a>`
+
 type Policy struct {
 	AutoCategory, AutoReply                                                                      bool
 	CategoryConfidence, ReplyConfidence, KnowledgeMinScore                                       float64
@@ -18,9 +20,10 @@ type Policy struct {
 	CommunicationSignature                                                                       string
 	BlockReplyOnContextError, BlockReplyOnIncident                                               bool
 	ContextRelevanceMinScore                                                                     float64
+	AIContentLabelEnabled                                                                        bool
 }
 
-func NewPolicy(autoCategory, autoReply bool, categoryConfidence, replyConfidence, knowledgeMinScore, knowledgeRetrievalFloor, evidenceRetrievalWeight, evidenceAIWeight, evidenceCategoryWeight float64, allowedSources, autoReplySources []string, language, style, salutation, closing, signature string, blockReplyOnContextError, blockReplyOnIncident bool, contextRelevanceMinScore float64) Policy {
+func NewPolicy(autoCategory, autoReply bool, categoryConfidence, replyConfidence, knowledgeMinScore, knowledgeRetrievalFloor, evidenceRetrievalWeight, evidenceAIWeight, evidenceCategoryWeight float64, allowedSources, autoReplySources []string, language, style, salutation, closing, signature string, aiContentLabelEnabled, blockReplyOnContextError, blockReplyOnIncident bool, contextRelevanceMinScore float64) Policy {
 	if evidenceRetrievalWeight+evidenceAIWeight+evidenceCategoryWeight <= 0 {
 		evidenceRetrievalWeight, evidenceAIWeight, evidenceCategoryWeight = .45, .35, .20
 	}
@@ -42,6 +45,7 @@ func NewPolicy(autoCategory, autoReply bool, categoryConfidence, replyConfidence
 		CommunicationSalutation:          strings.TrimSpace(salutation),
 		CommunicationClosing:             strings.TrimSpace(closing),
 		CommunicationSignature:           strings.TrimSpace(signature),
+		AIContentLabelEnabled:            aiContentLabelEnabled,
 		BlockReplyOnContextError:         blockReplyOnContextError,
 		BlockReplyOnIncident:             blockReplyOnIncident,
 		ContextRelevanceMinScore:         contextRelevanceMinScore,
@@ -202,7 +206,16 @@ func (p Policy) Evaluate(t model.Ticket, d model.Decision, categories []model.Ca
 		}
 	}
 	res.Reply = true
-	if strings.TrimSpace(hit.Doc.AnswerHTML) != "" {
+	if p.AIContentLabelEnabled {
+		// The disclosure is HTML, therefore every AI-selected automatic reply is
+		// sent as HTML. Plain-text KB answers are escaped before wrapping.
+		if strings.TrimSpace(hit.Doc.AnswerHTML) != "" {
+			res.ReplyText = p.formatRichReply(hit.Doc.AnswerHTML)
+		} else {
+			res.ReplyText = p.formatRichReply(p.plainTextToHTML(hit.Doc.Answer))
+		}
+		res.ReplyIsHTML = true
+	} else if strings.TrimSpace(hit.Doc.AnswerHTML) != "" {
 		res.ReplyText = p.formatRichReply(hit.Doc.AnswerHTML)
 		res.ReplyIsHTML = true
 	} else {
@@ -244,7 +257,12 @@ func (p Policy) formatReply(body string) string {
 }
 
 func (p Policy) formatRichReply(bodyHTML string) string {
-	parts := make([]string, 0, 3)
+	parts := make([]string, 0, 4)
+	if p.AIContentLabelEnabled {
+		// Keep this block byte-for-byte unchanged. It is the externally defined
+		// declaration that must be the first content in every AI-selected reply.
+		parts = append(parts, AIContentLabelHTML)
+	}
 	if strings.TrimSpace(p.CommunicationSalutation) != "" {
 		parts = append(parts, "<p>"+html.EscapeString(strings.TrimSpace(p.CommunicationSalutation))+"</p>")
 	}
@@ -260,6 +278,25 @@ func (p Policy) formatRichReply(bodyHTML string) string {
 	return strings.Join(parts, "\n")
 }
 
+func (p Policy) plainTextToHTML(body string) string {
+	normalized := strings.ReplaceAll(strings.ReplaceAll(strings.TrimSpace(body), "\r\n", "\n"), "\r", "\n")
+	if normalized == "" {
+		return ""
+	}
+	paragraphs := strings.Split(normalized, "\\n\\n")
+	out := make([]string, 0, len(paragraphs))
+	for _, paragraph := range paragraphs {
+		paragraph = strings.TrimSpace(paragraph)
+		if paragraph == "" {
+			continue
+		}
+		escaped := html.EscapeString(paragraph)
+		escaped = strings.ReplaceAll(escaped, "\n", "<br>")
+		out = append(out, "<p>"+escaped+"</p>")
+	}
+	return strings.Join(out, "\n")
+}
+
 func sourceSet(values []string) map[string]struct{} {
 	out := make(map[string]struct{}, len(values))
 	for _, v := range values {
diff --git a/internal/agent/policy_test.go b/internal/agent/policy_test.go
index fc16f53..1b2a35a 100644
--- a/internal/agent/policy_test.go
+++ b/internal/agent/policy_test.go
@@ -8,7 +8,7 @@ import (
 )
 
 func productionTestPolicy() Policy {
-	return NewPolicy(true, true, .9, .97, .88, .30, .45, .35, .20, []string{"internal-kb", "vendor-docs"}, []string{"internal-kb"}, "de-DE", "formal", "Guten Tag,", "Mit freundlichen Grüßen", "IT-Service", true, true, .2)
+	return NewPolicy(true, true, .9, .97, .88, .30, .45, .35, .20, []string{"internal-kb", "vendor-docs"}, []string{"internal-kb"}, "de-DE", "formal", "Guten Tag,", "Mit freundlichen Grüßen", "IT-Service", true, true, true, .2)
 }
 
 func approvedHit(source, language, style string) []model.KnowledgeHit {
@@ -33,6 +33,12 @@ func TestPolicyAutoReplyUsesApprovedKnowledge(t *testing.T) {
 	if !r.Reply || !r.ChangeCategory {
 		t.Fatalf("unexpected result: %+v", r)
 	}
+	if !r.ReplyIsHTML {
+		t.Fatalf("AI-labelled reply must be HTML: %+v", r)
+	}
+	if !strings.HasPrefix(r.ReplyText, AIContentLabelHTML) {
+		t.Fatalf("AI content label is not the exact first content: %s", r.ReplyText)
+	}
 	for _, expected := range []string{"Guten Tag,", "Bitte starten Sie", "Mit freundlichen Grüßen", "IT-Service"} {
 		if !strings.Contains(r.ReplyText, expected) {
 			t.Fatalf("reply missing %q: %q", expected, r.ReplyText)
@@ -92,7 +98,7 @@ func TestPolicyRejectsUnknownCategoryWithoutFailingRun(t *testing.T) {
 	var d model.Decision
 	d.Category.ID = 99
 	d.Category.Confidence = 1
-	p := NewPolicy(true, false, .9, .9, .8, .30, .45, .35, .20, []string{"internal-kb"}, nil, "de-DE", "formal", "", "", "", true, true, .2)
+	p := NewPolicy(true, false, .9, .9, .8, .30, .45, .35, .20, []string{"internal-kb"}, nil, "de-DE", "formal", "", "", "", true, true, true, .2)
 	r, err := p.Evaluate(model.Ticket{CategoryID: 1}, d, []model.Category{{ID: 1}}, nil, model.ContextSnapshot{})
 	if err != nil {
 		t.Fatal(err)
@@ -103,7 +109,7 @@ func TestPolicyRejectsUnknownCategoryWithoutFailingRun(t *testing.T) {
 }
 
 func TestPolicyCategoryDecisionIsDeterministic(t *testing.T) {
-	p := NewPolicy(true, false, .9, .9, .8, .30, .45, .35, .20, []string{"internal-kb"}, nil, "de-DE", "formal", "", "", "", true, true, .2)
+	p := NewPolicy(true, false, .9, .9, .8, .30, .45, .35, .20, []string{"internal-kb"}, nil, "de-DE", "formal", "", "", "", true, true, true, .2)
 	var d model.Decision
 	d.Category.ID = 2
 	d.Category.Confidence = .89
@@ -148,7 +154,7 @@ func TestPolicyBlocksAutoReplyOnIncompleteContext(t *testing.T) {
 
 func TestPolicyUsesTwoStageEvidenceForShortButUnambiguousTicket(t *testing.T) {
 	p := NewPolicy(true, true, .70, .70, .70, .30, .45, .35, .20,
-		[]string{"internal-kb"}, []string{"internal-kb"}, "de-DE", "formal", "", "", "", true, true, .2)
+		[]string{"internal-kb"}, []string{"internal-kb"}, "de-DE", "formal", "", "", "", true, true, true, .2)
 	d := replyDecision()
 	d.Reply.Confidence = .95
 	hits := []model.KnowledgeHit{{
@@ -170,7 +176,7 @@ func TestPolicyUsesTwoStageEvidenceForShortButUnambiguousTicket(t *testing.T) {
 
 func TestPolicyStillRejectsWeakRetrievalEvenWithHighAIConfidence(t *testing.T) {
 	p := NewPolicy(true, true, .70, .70, .70, .30, .45, .35, .20,
-		[]string{"internal-kb"}, []string{"internal-kb"}, "de-DE", "formal", "", "", "", true, true, .2)
+		[]string{"internal-kb"}, []string{"internal-kb"}, "de-DE", "formal", "", "", "", true, true, true, .2)
 	d := replyDecision()
 	d.Reply.Confidence = .99
 	hits := []model.KnowledgeHit{{
@@ -185,3 +191,32 @@ func TestPolicyStillRejectsWeakRetrievalEvenWithHighAIConfidence(t *testing.T) {
 		t.Fatalf("weak retrieval must remain blocked: %+v", r)
 	}
 }
+
+func TestPolicyAIContentLabelEscapesPlainTextKnowledge(t *testing.T) {
+	p := productionTestPolicy()
+	d := replyDecision()
+	hits := approvedHit("internal-kb", "de-DE", "formal")
+	hits[0].Doc.Answer = "Bitte <script>alert('x')</script> prüfen.\\nZweite Zeile."
+	r, err := p.Evaluate(model.Ticket{CategoryID: 2}, d, []model.Category{{ID: 2}}, hits, model.ContextSnapshot{})
+	if err != nil {
+		t.Fatal(err)
+	}
+	if !r.Reply || !r.ReplyIsHTML || !strings.HasPrefix(r.ReplyText, AIContentLabelHTML) {
+		t.Fatalf("unexpected labelled reply: %+v", r)
+	}
+	if strings.Contains(r.ReplyText, "<script>") || !strings.Contains(r.ReplyText, "&lt;script&gt;") {
+		t.Fatalf("plain-text KB was not safely escaped: %s", r.ReplyText)
+	}
+}
+
+func TestPolicyCanDisableAIContentLabel(t *testing.T) {
+	p := NewPolicy(true, true, .9, .97, .88, .30, .45, .35, .20,
+		[]string{"internal-kb"}, []string{"internal-kb"}, "de-DE", "formal", "Guten Tag,", "Mit freundlichen Grüßen", "IT-Service", false, true, true, .2)
+	r, err := p.Evaluate(model.Ticket{CategoryID: 1}, replyDecision(), []model.Category{{ID: 1}, {ID: 2}}, approvedHit("internal-kb", "de-DE", "formal"), model.ContextSnapshot{})
+	if err != nil {
+		t.Fatal(err)
+	}
+	if r.ReplyIsHTML || strings.Contains(r.ReplyText, AIContentLabelHTML) {
+		t.Fatalf("disabled AI content label must preserve plain reply behaviour: %+v", r)
+	}
+}
diff --git a/internal/config/config.go b/internal/config/config.go
index 8c807a4..ac56472 100644
--- a/internal/config/config.go
+++ b/internal/config/config.go
@@ -89,6 +89,7 @@ type Config struct {
 	CommunicationSalutation string
 	CommunicationClosing    string
 	CommunicationSignature  string
+	AIContentLabelEnabled   bool
 
 	AutoCategory                     bool
 	AutoReply                        bool
@@ -172,7 +173,7 @@ func Load() (Config, error) {
 		KnowledgeAllowedSources:          envStringList("KNOWLEDGE_ALLOWED_SOURCES", "internal-kb"),
 		KnowledgeAutoReplySources:        envStringList("KNOWLEDGE_AUTO_REPLY_SOURCES", "internal-kb"),
 		KnowledgeWebEditEnabled:          envBool("KNOWLEDGE_WEB_EDIT_ENABLED", false),
-		KnowledgeCategoryMode:            strings.ToLower(env("KNOWLEDGE_CATEGORY_MODE", "unscoped")),
+		KnowledgeCategoryMode:            envNormalizedLower("KNOWLEDGE_CATEGORY_MODE", "unscoped"),
 		KnowledgeCategoryMapFile:         strings.TrimSpace(os.Getenv("KNOWLEDGE_CATEGORY_MAP_FILE")),
 		KnowledgeIgnoreGlobs:             envStringListPreserveCase("KNOWLEDGE_IGNORE_GLOBS", ""),
 		KnowledgeSemanticWeight:          envFloat("KNOWLEDGE_WEIGHT_SEMANTIC", 0.45),
@@ -180,12 +181,12 @@ func Load() (Config, error) {
 		KnowledgeLexicalWeight:           envFloat("KNOWLEDGE_WEIGHT_LEXICAL", 0.20),
 		KnowledgeKeywordWeight:           envFloat("KNOWLEDGE_WEIGHT_KEYWORDS", 0.075),
 		KnowledgeCategoryWeight:          envFloat("KNOWLEDGE_WEIGHT_CATEGORY", 0.075),
-		KnowledgeEmbeddingProfile:        strings.ToLower(env("KNOWLEDGE_EMBEDDING_PROFILE", "auto")),
+		KnowledgeEmbeddingProfile:        envNormalizedLower("KNOWLEDGE_EMBEDDING_PROFILE", "auto"),
 		KnowledgeChunkWords:              envInt("KNOWLEDGE_CHUNK_WORDS", 160),
 		KnowledgeChunkOverlapWords:       envInt("KNOWLEDGE_CHUNK_OVERLAP_WORDS", 30),
 		KnowledgeMaxChunksPerDoc:         envInt("KNOWLEDGE_MAX_CHUNKS_PER_DOC", 24),
 		KnowledgeMaxQueryChunks:          envInt("KNOWLEDGE_MAX_QUERY_CHUNKS", 64),
-		KnowledgeIndexMode:               strings.ToLower(env("KNOWLEDGE_INDEX_MODE", "incremental")),
+		KnowledgeIndexMode:               envNormalizedLower("KNOWLEDGE_INDEX_MODE", "incremental"),
 		KnowledgeEmbedBatchSize:          envInt("KNOWLEDGE_EMBED_BATCH_SIZE", 64),
 		KnowledgeIndexScanInterval:       envDuration("KNOWLEDGE_INDEX_SCAN_INTERVAL", 5*time.Minute),
 		GLPIKBEnabled:                    envBool("GLPI_KB_ENABLED", false),
@@ -234,7 +235,7 @@ func Load() (Config, error) {
 		GLPIUserDeviceLimit:          envInt("GLPI_USER_DEVICE_LIMIT", 20),
 		UptimeKumaEnabled:            envBool("UPTIME_KUMA_ENABLED", false),
 		UptimeKumaURL:                strings.TrimRight(os.Getenv("UPTIME_KUMA_URL"), "/"),
-		UptimeKumaMode:               strings.ToLower(env("UPTIME_KUMA_MODE", "metrics")),
+		UptimeKumaMode:               envNormalizedLower("UPTIME_KUMA_MODE", "metrics"),
 		UptimeKumaAPIKey:             os.Getenv("UPTIME_KUMA_API_KEY"),
 		UptimeKumaStatusPages:        envStringListPreserveCase("UPTIME_KUMA_STATUS_PAGES", ""),
 		UptimeKumaTimeout:            envDuration("UPTIME_KUMA_TIMEOUT", 10*time.Second),
@@ -311,10 +312,10 @@ func (c Config) Validate() error {
 	if c.KnowledgeWebEditEnabled && c.WebAllowAnonymous {
 		return errors.New("KNOWLEDGE_WEB_EDIT_ENABLED requires authenticated dashboard access; WEB_ALLOW_ANONYMOUS must be false")
 	}
-	switch c.KnowledgeCategoryMode {
+	switch strings.ToLower(strings.TrimSpace(c.KnowledgeCategoryMode)) {
 	case "", "unscoped", "skip", "strict":
 	default:
-		return errors.New("KNOWLEDGE_CATEGORY_MODE must be one of: unscoped, skip, strict")
+		return fmt.Errorf("KNOWLEDGE_CATEGORY_MODE must be one of: unscoped, skip, strict (got %q)", c.KnowledgeCategoryMode)
 	}
 	for _, pattern := range c.KnowledgeIgnoreGlobs {
 		if _, err := filepath.Match(pattern, "probe.json"); err != nil {
@@ -530,6 +531,14 @@ func env(key, def string) string {
 	}
 	return def
 }
+
+func envNormalizedLower(key, def string) string {
+	v := strings.ToLower(strings.TrimSpace(os.Getenv(key)))
+	if v == "" {
+		return strings.ToLower(strings.TrimSpace(def))
+	}
+	return v
+}
 func isPlaceholder(v string) bool {
 	return strings.Contains(strings.ToUpper(strings.TrimSpace(v)), "CHANGE_ME")
 }
diff --git a/internal/config/config_test.go b/internal/config/config_test.go
index f437b57..c03a75d 100644
--- a/internal/config/config_test.go
+++ b/internal/config/config_test.go
@@ -173,3 +173,22 @@ func TestValidateRejectsInvalidKnowledgeScoringConfig(t *testing.T) {
 		t.Fatal("expected overlap >= chunk size to be rejected")
 	}
 }
+
+func TestValidateKnowledgeCategoryModeTrimsWhitespace(t *testing.T) {
+	c := validConfig()
+	c.KnowledgeCategoryMode = "  UNSCOPED  "
+	if err := c.Validate(); err != nil {
+		t.Fatalf("expected whitespace/case normalized category mode to validate: %v", err)
+	}
+}
+
+func TestEnvNormalizedLowerDefaultsBlankOrWhitespace(t *testing.T) {
+	t.Setenv("KNOWLEDGE_CATEGORY_MODE", "   ")
+	if got := envNormalizedLower("KNOWLEDGE_CATEGORY_MODE", "unscoped"); got != "unscoped" {
+		t.Fatalf("expected unscoped default, got %q", got)
+	}
+	t.Setenv("KNOWLEDGE_CATEGORY_MODE", "  STRICT ")
+	if got := envNormalizedLower("KNOWLEDGE_CATEGORY_MODE", "unscoped"); got != "strict" {
+		t.Fatalf("expected strict, got %q", got)
+	}
+}
diff --git a/internal/web/server.go b/internal/web/server.go
index 165771a..49d7474 100644
--- a/internal/web/server.go
+++ b/internal/web/server.go
@@ -121,7 +121,7 @@ func (s *Server) status(w http.ResponseWriter, r *http.Request) {
 		"glpi_ok": g, "ollama_ok": o, "knowledge_docs": s.metrics.KnowledgeDocs(), "last_poll": s.metrics.LastPoll(),
 		"knowledge_ready": s.knowledge.Ready(), "knowledge_init_state": initStatus.State, "knowledge_init_phase": initStatus.Phase, "knowledge_init_total_files": initStatus.TotalFiles, "knowledge_init_processed_files": initStatus.ProcessedFiles, "knowledge_init_loaded_docs": initStatus.LoadedDocs, "knowledge_init_indexed_docs": initStatus.IndexedDocs, "knowledge_init_cache_hits": initStatus.CacheHits, "knowledge_init_pending_embeddings": initStatus.PendingEmbeddings, "knowledge_init_started_at": initStatus.StartedAt, "knowledge_init_finished_at": initStatus.FinishedAt, "knowledge_init_error": initStatus.LastError,
 		"knowledge_index_mode": s.cfg.KnowledgeIndexMode, "knowledge_embed_batch_size": s.cfg.KnowledgeEmbedBatchSize, "knowledge_index_scan_interval": s.cfg.KnowledgeIndexScanInterval.String(), "knowledge_snapshot_loaded": initStatus.SnapshotLoaded, "knowledge_snapshot_path": initStatus.SnapshotPath, "knowledge_snapshot_saved_at": initStatus.SnapshotSavedAt, "knowledge_last_scan_at": initStatus.LastScanAt, "knowledge_last_scan_error": initStatus.LastScanError, "knowledge_changed_files": initStatus.ChangedFiles, "knowledge_deleted_files": initStatus.DeletedFiles, "knowledge_reused_files": initStatus.ReusedFiles,
-		"communication_language": s.cfg.CommunicationLanguage, "communication_style": s.cfg.CommunicationStyle, "knowledge_allowed_sources": s.cfg.KnowledgeAllowedSources, "knowledge_auto_reply_sources": s.cfg.KnowledgeAutoReplySources, "knowledge_category_mode": s.cfg.KnowledgeCategoryMode, "knowledge_category_map_configured": strings.TrimSpace(s.cfg.KnowledgeCategoryMapFile) != "", "knowledge_ignore_globs": s.cfg.KnowledgeIgnoreGlobs, "knowledge_ignored_files": loadStats.IgnoredFiles, "knowledge_unmapped_category_files": loadStats.UnmappedCategoryFiles, "knowledge_unmapped_categories": loadStats.UnmappedCategories,
+		"communication_language": s.cfg.CommunicationLanguage, "communication_style": s.cfg.CommunicationStyle, "ai_content_label_enabled": s.cfg.AIContentLabelEnabled, "knowledge_allowed_sources": s.cfg.KnowledgeAllowedSources, "knowledge_auto_reply_sources": s.cfg.KnowledgeAutoReplySources, "knowledge_category_mode": s.cfg.KnowledgeCategoryMode, "knowledge_category_map_configured": strings.TrimSpace(s.cfg.KnowledgeCategoryMapFile) != "", "knowledge_ignore_globs": s.cfg.KnowledgeIgnoreGlobs, "knowledge_ignored_files": loadStats.IgnoredFiles, "knowledge_unmapped_category_files": loadStats.UnmappedCategoryFiles, "knowledge_unmapped_categories": loadStats.UnmappedCategories,
 		"category_confidence": s.cfg.CategoryConfidence, "reply_confidence": s.cfg.ReplyConfidence, "knowledge_min_score": s.cfg.KnowledgeMinScore, "knowledge_retrieval_floor": s.cfg.KnowledgeRetrievalFloor, "knowledge_evidence_weight_retrieval": s.cfg.KnowledgeEvidenceRetrievalWeight, "knowledge_evidence_weight_ai": s.cfg.KnowledgeEvidenceAIWeight, "knowledge_evidence_weight_category": s.cfg.KnowledgeEvidenceCategoryWeight,
 		"knowledge_weight_semantic": s.cfg.KnowledgeSemanticWeight, "knowledge_weight_title": s.cfg.KnowledgeTitleWeight, "knowledge_weight_lexical": s.cfg.KnowledgeLexicalWeight, "knowledge_weight_keywords": s.cfg.KnowledgeKeywordWeight, "knowledge_weight_category": s.cfg.KnowledgeCategoryWeight, "knowledge_embedding_profile": s.cfg.KnowledgeEmbeddingProfile,
 		"knowledge_chunk_words": s.cfg.KnowledgeChunkWords, "knowledge_chunk_overlap_words": s.cfg.KnowledgeChunkOverlapWords, "knowledge_max_chunks_per_doc": s.cfg.KnowledgeMaxChunksPerDoc,
diff --git a/internal/web/templates/dashboard.html b/internal/web/templates/dashboard.html
index 373b427..9bcf45f 100644
--- a/internal/web/templates/dashboard.html
+++ b/internal/web/templates/dashboard.html
@@ -143,7 +143,7 @@ function renderKB(){const st=kbStatsData();$('#kbStats').innerHTML=st.map(x=>`<d
 function renderLearning(){const q=$('#learningSearch').value.trim().toLowerCase(),rows=learningRows.filter(x=>!q||[x.ticket_id,x.subject,x.text,x.category_name,x.category_id].join(' ').toLowerCase().includes(q));const corrections=learningRows.filter(x=>x.correction).length;$('#learningStats').innerHTML=[['Gesamt',learningRows.length,'bestätigte Beispiele'],['Korrekturen',corrections,'KI lag anders'],['Bestätigungen',learningRows.length-corrections,'KI wurde bestätigt']].map(x=>`<div class="stat"><div class="stat-label">${esc(x[0])}</div><div class="stat-value">${fmtNum(x[1])}</div><div class="stat-foot">${esc(x[2])}</div></div>`).join('');$('#learningTable').innerHTML=rows.length?rows.map(x=>`<tr><td><div class="ticket-title">#${esc(x.ticket_id)} ${esc(x.subject)}</div><div class="muted small">${esc((x.text||'').slice(0,220))}</div></td><td><strong>${esc(x.category_name)}</strong> (#${esc(x.category_id)})${x.ai_recommended_category_id?`<div class="muted small">KI: #${esc(x.ai_recommended_category_id)} · ${esc(pct(x.ai_confidence))}</div>`:''}</td><td>${x.correction?badge('Korrektur','warn'):badge('Bestätigung','good')}</td><td class="nowrap">${esc(fmtDate(x.created_at))}</td><td><button class="btn small danger" data-learning-delete="${esc(x.id)}">Löschen</button></td></tr>`).join(''):'<tr><td colspan="5" class="empty">Keine Lernbeispiele.</td></tr>'}
 function configCard(title,subtitle,rows){return `<div class="panel config-card"><div class="panel-head"><div><div class="panel-title">${esc(title)}</div><div class="panel-sub">${esc(subtitle)}</div></div></div><div class="config-list">${rows.map(([k,v])=>`<div class="config-row"><div class="config-key">${esc(k)}</div><div class="config-val">${v}</div></div>`).join('')}</div></div>`}
 function val(v){if(typeof v==='boolean')return v?badge('aktiv','good'):badge('aus','warn');if(Array.isArray(v))return esc(v.length?v.join(', '):'–');return esc(v??'–')}
-function renderConfig(){const s=statusData;const groups=[configCard('Agent & GLPI','Polling, Worker und Schreibmodus',[['Dry Run',val(s.dry_run)],['Auto-Kategorie',val(s.auto_category)],['Auto-Reply',val(s.auto_reply)],['Worker',val(s.workers)],['Queue-Größe',val(s.queue_size)],['API-Version',val(s.glpi_api_version)],['Poll-Intervall',val(s.glpi_poll_interval)],['Poll-Limit',val(s.glpi_poll_limit)],['Ticket-Filter gesetzt',val(s.glpi_ticket_filter_configured)],['Erlaubte Status',val(s.glpi_allowed_status_ids)],['GLPI-Timeout',val(s.glpi_timeout)]]),configCard('Ollama','Modelle und Inferenzbudget',[['Chat-Modell',val(s.ollama_model)],['Embedding-Modell',val(s.ollama_embedding_model)],['Embedding-Profil',val(s.knowledge_embedding_profile)],['Timeout',val(s.ollama_timeout)],['Num Predict',val(s.ollama_num_predict)],['Keep Alive',val(s.ollama_keep_alive)],['Thinking',val(s.ollama_think)],['Max. parallel',val(s.ollama_max_concurrent)],['JSON-Retries',val(s.ollama_json_retries)]]),configCard('Knowledge / RAG','Retrieval, Chunking und Ranking',[['RAG',val(s.rag_enabled)],['Index-Modus',val(s.knowledge_index_mode)],['Snapshot geladen',val(s.knowledge_snapshot_loaded)],['Snapshot gespeichert',val(fmtDate(s.knowledge_snapshot_saved_at))],['Letzter Delta-Scan',val(fmtDate(s.knowledge_last_scan_at))],['Letzter Scanfehler',val(s.knowledge_last_scan_error||'–')],['Geänderte Dateien',val(s.knowledge_changed_files)],['Gelöschte Dateien',val(s.knowledge_deleted_files)],['Wiederverwendete Vektoren',val(s.knowledge_reused_files)],['Embedding-Batch',val(s.knowledge_embed_batch_size)],['Scan-Intervall',val(s.knowledge_index_scan_interval)],['Knowledge bereit',val(s.knowledge_ready)],['Startup-Status',val(s.knowledge_init_state)],['Startup-Phase',val(s.knowledge_init_phase)],['Dateien verarbeitet',val(`${s.knowledge_init_processed_files||0} / ${s.knowledge_init_total_files||0}`)],['Dokumente geladen',val(s.knowledge_init_loaded_docs)],['Dokumente indexiert',val(s.knowledge_init_indexed_docs)],['Embedding-Cache-Treffer',val(s.knowledge_init_cache_hits)],['Offene Embeddings',val(s.knowledge_init_pending_embeddings)],['Startup-Fehler',val(s.knowledge_init_error||'–')],['Max. Kandidaten an KI',val(s.knowledge_top_k)],['Audit Top K',val(s.knowledge_audit_top_k)],['Max. Abstand zum Top-Treffer',pct(s.knowledge_candidate_max_gap)],['Finaler Evidenz-Schwellwert',`<strong>${pct(s.knowledge_min_score)}</strong>`],['Retrieval-Floor',`<strong>${pct(s.knowledge_retrieval_floor)}</strong>`],['Evidenzgewicht Retrieval',pct(s.knowledge_evidence_weight_retrieval)],['Evidenzgewicht KI',pct(s.knowledge_evidence_weight_ai)],['Evidenzgewicht Kategorie',pct(s.knowledge_evidence_weight_category)],['Retrieval: Semantik',pct(s.knowledge_weight_semantic)],['Retrieval: Titel',pct(s.knowledge_weight_title)],['Retrieval: Lexikalisch',pct(s.knowledge_weight_lexical)],['Retrieval: Keywords',pct(s.knowledge_weight_keywords)],['Retrieval: Kategorie/Lernen',pct(s.knowledge_weight_category)],['Chunk-Wörter',val(s.knowledge_chunk_words)],['Overlap-Wörter',val(s.knowledge_chunk_overlap_words)],['Max. KB-Chunks',val(s.knowledge_max_chunks_per_doc)],['Max. Ticket-Chunks',val(s.knowledge_max_query_chunks)],['Erlaubte Quellen',val(s.knowledge_allowed_sources)],['Auto-Reply-Quellen',val(s.knowledge_auto_reply_sources)],['Fremdkategorie-Modus',val(s.knowledge_category_mode)],['Kategorie-Mapping',val(s.knowledge_category_map_configured?'konfiguriert':'–')],['Ignore-Globs',val(s.knowledge_ignore_globs)],['Ignorierte Dateien',val(s.knowledge_ignored_files)],['KBs mit ungemappten Kategorien',val(s.knowledge_unmapped_category_files)],['Ungemappte Kategorien',val(s.knowledge_unmapped_categories)]]),configCard('GLPI Knowledge Base','Synchronisation der GLPI-Wissensdatenbank',[['Aktiv',val(s.glpi_kb_enabled)],['Sync OK',val(s.glpi_kb_ok)],['Dokumente',val(s.glpi_kb_documents)],['Letzter Sync',val(fmtDate(s.glpi_kb_last_sync))],['Intervall',val(s.glpi_kb_sync_interval)],['Pfad',val(s.glpi_kb_path)],['Filter gesetzt',val(s.glpi_kb_filter_configured)],['Limit',val(s.glpi_kb_limit)],['Auto-Reply',val(s.glpi_kb_auto_reply)],['Auto-Reply-Kategorien',val(s.glpi_kb_auto_reply_category_ids)],['Letzter Fehler',val(s.glpi_kb_last_error||'–')]]),configCard('Policy & Kommunikation','Entscheidungsschwellen und Sprache',[['Kategorie-Confidence',`<strong>${pct(s.category_confidence)}</strong>`],['Reply-Confidence',`<strong>${pct(s.reply_confidence)}</strong>`],['Sprache',val(s.communication_language)],['Stil',val(s.communication_style)],['KB-Webeditor',val(s.knowledge_edit_enabled)],['Lernen',val(s.learning_enabled)],['Max. Lernbeispiele',val(s.learning_max_examples)],['Beispiele/Kategorie',val(s.learning_examples_per_category)]]),configCard('Kontextquellen','Störungen, Changes, Incidents und Geräte',[['Kontext aktiv',val(s.context_enabled)],['Timeout',val(s.context_timeout)],['Relevanz-Minimum',pct(s.context_relevance_min_score)],['Fail-closed',val(s.context_fail_closed)],['Incident blockiert Reply',val(s.context_incident_block)],['Change Calendar',val(s.change_calendar_enabled)],['Lookback',val(s.change_lookback)],['Lookahead',val(s.change_lookahead)],['Major Incidents',val(s.major_incidents_enabled)],['Benutzer-Geräte',val(s.user_device_context_enabled)],['Uptime Kuma',val(s.uptime_kuma_enabled)],['Uptime-Modus',val(s.uptime_kuma_mode)]] )];$('#configGroups').innerHTML=groups.join('')}
+function renderConfig(){const s=statusData;const groups=[configCard('Agent & GLPI','Polling, Worker und Schreibmodus',[['Dry Run',val(s.dry_run)],['Auto-Kategorie',val(s.auto_category)],['Auto-Reply',val(s.auto_reply)],['Worker',val(s.workers)],['Queue-Größe',val(s.queue_size)],['API-Version',val(s.glpi_api_version)],['Poll-Intervall',val(s.glpi_poll_interval)],['Poll-Limit',val(s.glpi_poll_limit)],['Ticket-Filter gesetzt',val(s.glpi_ticket_filter_configured)],['Erlaubte Status',val(s.glpi_allowed_status_ids)],['GLPI-Timeout',val(s.glpi_timeout)]]),configCard('Ollama','Modelle und Inferenzbudget',[['Chat-Modell',val(s.ollama_model)],['Embedding-Modell',val(s.ollama_embedding_model)],['Embedding-Profil',val(s.knowledge_embedding_profile)],['Timeout',val(s.ollama_timeout)],['Num Predict',val(s.ollama_num_predict)],['Keep Alive',val(s.ollama_keep_alive)],['Thinking',val(s.ollama_think)],['Max. parallel',val(s.ollama_max_concurrent)],['JSON-Retries',val(s.ollama_json_retries)]]),configCard('Knowledge / RAG','Retrieval, Chunking und Ranking',[['RAG',val(s.rag_enabled)],['Index-Modus',val(s.knowledge_index_mode)],['Snapshot geladen',val(s.knowledge_snapshot_loaded)],['Snapshot gespeichert',val(fmtDate(s.knowledge_snapshot_saved_at))],['Letzter Delta-Scan',val(fmtDate(s.knowledge_last_scan_at))],['Letzter Scanfehler',val(s.knowledge_last_scan_error||'–')],['Geänderte Dateien',val(s.knowledge_changed_files)],['Gelöschte Dateien',val(s.knowledge_deleted_files)],['Wiederverwendete Vektoren',val(s.knowledge_reused_files)],['Embedding-Batch',val(s.knowledge_embed_batch_size)],['Scan-Intervall',val(s.knowledge_index_scan_interval)],['Knowledge bereit',val(s.knowledge_ready)],['Startup-Status',val(s.knowledge_init_state)],['Startup-Phase',val(s.knowledge_init_phase)],['Dateien verarbeitet',val(`${s.knowledge_init_processed_files||0} / ${s.knowledge_init_total_files||0}`)],['Dokumente geladen',val(s.knowledge_init_loaded_docs)],['Dokumente indexiert',val(s.knowledge_init_indexed_docs)],['Embedding-Cache-Treffer',val(s.knowledge_init_cache_hits)],['Offene Embeddings',val(s.knowledge_init_pending_embeddings)],['Startup-Fehler',val(s.knowledge_init_error||'–')],['Max. Kandidaten an KI',val(s.knowledge_top_k)],['Audit Top K',val(s.knowledge_audit_top_k)],['Max. Abstand zum Top-Treffer',pct(s.knowledge_candidate_max_gap)],['Finaler Evidenz-Schwellwert',`<strong>${pct(s.knowledge_min_score)}</strong>`],['Retrieval-Floor',`<strong>${pct(s.knowledge_retrieval_floor)}</strong>`],['Evidenzgewicht Retrieval',pct(s.knowledge_evidence_weight_retrieval)],['Evidenzgewicht KI',pct(s.knowledge_evidence_weight_ai)],['Evidenzgewicht Kategorie',pct(s.knowledge_evidence_weight_category)],['Retrieval: Semantik',pct(s.knowledge_weight_semantic)],['Retrieval: Titel',pct(s.knowledge_weight_title)],['Retrieval: Lexikalisch',pct(s.knowledge_weight_lexical)],['Retrieval: Keywords',pct(s.knowledge_weight_keywords)],['Retrieval: Kategorie/Lernen',pct(s.knowledge_weight_category)],['Chunk-Wörter',val(s.knowledge_chunk_words)],['Overlap-Wörter',val(s.knowledge_chunk_overlap_words)],['Max. KB-Chunks',val(s.knowledge_max_chunks_per_doc)],['Max. Ticket-Chunks',val(s.knowledge_max_query_chunks)],['Erlaubte Quellen',val(s.knowledge_allowed_sources)],['Auto-Reply-Quellen',val(s.knowledge_auto_reply_sources)],['Fremdkategorie-Modus',val(s.knowledge_category_mode)],['Kategorie-Mapping',val(s.knowledge_category_map_configured?'konfiguriert':'–')],['Ignore-Globs',val(s.knowledge_ignore_globs)],['Ignorierte Dateien',val(s.knowledge_ignored_files)],['KBs mit ungemappten Kategorien',val(s.knowledge_unmapped_category_files)],['Ungemappte Kategorien',val(s.knowledge_unmapped_categories)]]),configCard('GLPI Knowledge Base','Synchronisation der GLPI-Wissensdatenbank',[['Aktiv',val(s.glpi_kb_enabled)],['Sync OK',val(s.glpi_kb_ok)],['Dokumente',val(s.glpi_kb_documents)],['Letzter Sync',val(fmtDate(s.glpi_kb_last_sync))],['Intervall',val(s.glpi_kb_sync_interval)],['Pfad',val(s.glpi_kb_path)],['Filter gesetzt',val(s.glpi_kb_filter_configured)],['Limit',val(s.glpi_kb_limit)],['Auto-Reply',val(s.glpi_kb_auto_reply)],['Auto-Reply-Kategorien',val(s.glpi_kb_auto_reply_category_ids)],['Letzter Fehler',val(s.glpi_kb_last_error||'–')]]),configCard('Policy & Kommunikation','Entscheidungsschwellen und Sprache',[['Kategorie-Confidence',`<strong>${pct(s.category_confidence)}</strong>`],['Reply-Confidence',`<strong>${pct(s.reply_confidence)}</strong>`],['Sprache',val(s.communication_language)],['Stil',val(s.communication_style)],['KI-Kennzeichnung',val(s.ai_content_label_enabled)],['KB-Webeditor',val(s.knowledge_edit_enabled)],['Lernen',val(s.learning_enabled)],['Max. Lernbeispiele',val(s.learning_max_examples)],['Beispiele/Kategorie',val(s.learning_examples_per_category)]]),configCard('Kontextquellen','Störungen, Changes, Incidents und Geräte',[['Kontext aktiv',val(s.context_enabled)],['Timeout',val(s.context_timeout)],['Relevanz-Minimum',pct(s.context_relevance_min_score)],['Fail-closed',val(s.context_fail_closed)],['Incident blockiert Reply',val(s.context_incident_block)],['Change Calendar',val(s.change_calendar_enabled)],['Lookback',val(s.change_lookback)],['Lookahead',val(s.change_lookahead)],['Major Incidents',val(s.major_incidents_enabled)],['Benutzer-Geräte',val(s.user_device_context_enabled)],['Uptime Kuma',val(s.uptime_kuma_enabled)],['Uptime-Modus',val(s.uptime_kuma_mode)]] )];$('#configGroups').innerHTML=groups.join('')}
 function renderSourceOptions(){const filterOld=$('#kbSourceFilter').value,sourceOld=$('#kbSource').value;const sources=[...new Set(kbDocs.map(x=>x.source).filter(Boolean))].sort();$('#kbSourceFilter').innerHTML='<option value="">Alle Quellen</option>'+sources.map(x=>`<option value="${esc(x)}">${esc(x)}</option>`).join('');if([...$('#kbSourceFilter').options].some(o=>o.value===filterOld))$('#kbSourceFilter').value=filterOld;const allowed=statusData.knowledge_allowed_sources||[];$('#kbSource').innerHTML=allowed.map(x=>`<option value="${esc(x)}">${esc(x)}</option>`).join('');if([...$('#kbSource').options].some(o=>o.value===sourceOld))$('#kbSource').value=sourceOld;else if([...$('#kbSource').options].some(o=>o.value==='internal-kb'))$('#kbSource').value='internal-kb'}
 function renderCategoryPicker(filter=''){const q=filter.toLowerCase();$('#kbCategoryList').innerHTML=categories.filter(c=>!q||(c.completename||c.name||'').toLowerCase().includes(q)).map(c=>`<label class="category-item"><input type="checkbox" value="${Number(c.id)}" ${kbCategorySelection.has(Number(c.id))?'checked':''}><span>${esc(c.completename||c.name)} <span class="muted">#${Number(c.id)}</span></span></label>`).join('')||'<div class="muted small" style="padding:8px">Keine Kategorie gefunden.</div>'}
 function clearKbForm(){currentKbId='';kbCategorySelection=new Set();$('#kbForm').reset();$('#kbId').disabled=false;$('#kbId').value='';$('#kbLanguage').value=statusData.communication_language||'de-DE';$('#kbStyle').value=statusData.communication_style||'formal';$('#kbScore').value=Number(statusData.knowledge_min_score||.70).toFixed(2);if([...$('#kbSource').options].some(x=>x.value==='internal-kb'))$('#kbSource').value='internal-kb';$('#kbModalTitle').textContent='Neuen Artikel anlegen';$('#kbModalEyebrow').textContent='Interne Knowledge Base';$('#kbEditState').textContent='Neuer Artikel';$('#kbFormMessage').className='form-message';$('#kbCategorySearch').value='';renderCategoryPicker();updateCounts()}