.`)
+- Pfade enthalten Mandats- und Instanz-IDs (siehe Konzeptbeispiele)
+- Sortierung auf allen Ebenen über jeweiliges `order` (Mandat, Feature, Instanz, View)
+
+## RBAC-Integration
+
+- **`objectKey`** in Navigationsitems entspricht dem **`item`**-String im **UI-Kontext** der Access Rules (vollqualifiziert), z. B. `ui.feature.trustee.dashboard`.
+- Navigation-Endpoint wendet **Permission-Filter** an, bevor die Response gebaut wird — nur erlaubte Knoten sind enthalten.
+- Konventionen (Kontext UI): `ui.system.`, `ui.admin.`, `ui.feature..`. Für DATA/RESOURCE siehe übergreifendes RBAC-Dokument (`data.*`, `resource.*`).
+- **Inkonsistenz-Hinweis (Audit):** Template-Rollen dürfen keine Kurz-`item`-Namen (`dashboard`) nutzen, wenn `objectKey` vollqualifiziert ist — `item` und Navigation müssen übereinstimmen.
+
+## Schlüssel-Dateien
+
+| Schicht | Pfad / Artefakt |
+|---------|------------------|
+| Statische Sektionen (Gateway) | `mainSystem.py` — `NAVIGATION_SECTIONS` |
+| Navigation-Route | `routeSystem.py` — Endpoint-Evolution `/api/system/navigation` → `/api/navigation` |
+| Feature-Views / Template-Rollen | z. B. `mainTrustee.py`, `mainRealEstate.py` — `UI_OBJECTS`, `TEMPLATE_ROLES` |
+| Admin-Feature-Permission (Ist teils feature-spezifisch) | `routeAdminFeatures.py` — z. B. `_deriveViewPermissions` |
+| Frontend: Navigation | `MandateNavigation.tsx`, `useNavigation` |
+| Frontend: Registry (Ziel) | `frontend_nyla/src/config/pageRegistry.ts` — `PAGE_REGISTRY`, `FEATURE_REGISTRY` |
+| Legacy-Duplikate (Audit) | `mandate.ts` — `FEATURE_REGISTRY` / View-Definitionen parallel zum Backend |
+
+## Regeln / Invarianten
+
+- **Backend autoritativ:** Keine eigenständige Zusammenstellung der Navigationsstruktur im UI aus mehreren Quellen ohne Gateway-Abgleich (Zielzustand: ein Endpoint, ein Baum).
+- **Nur sichtbare Knoten:** Keine negativen Sichtbarkeitsflags in der Response.
+- **Sortierung:** ausschließlich vom Gateway; das UI sortiert empfangene Listen nicht erneut.
+- **`uiComponent`-Konventionen:** `page.system.`, `page.admin.`, `page.feature..`, Feature-Gruppe `feature.`.
+- **Drift sichtbar machen:** Unbekannte Codes im UI als Fehler anzeigen, nicht still ignorieren.
+- Vollständiges API-Konzept und Migrationsphasen: `wiki/concepts/Navigation-API-Konzept.md`.
diff --git a/b-reference/platform/neutralization.md b/b-reference/platform/neutralization.md
new file mode 100644
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--- /dev/null
+++ b/b-reference/platform/neutralization.md
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+
+
+
+
+# Neutralisierungs-System
+
+## Überblick
+
+Neutralisierung ersetzt mandantensensible Inhalte durch stabile Platzhalter, bevor Text an externe KI-Modelle geht oder dauerhaft im RAG landet. Rohdaten aus Tools werden nicht separat „nachgefiltert“: der Schutz liegt am **Content-Einstieg** (Indexierung, Extraktion, zentrales AI-Gate) und an vererbten Flags auf `FileItem` / Session / Feature-Konfiguration.
+
+## Architektur: Einzige zentrale Stelle
+
+**Für jeden AI-Modell-Call** gilt: Prompt, RAG-Kontext und Chat-Nachrichten werden **ausschließlich** in `mainServiceAi.py` geprüft und neutralisiert (`_shouldNeutralize`, `_neutralizeRequest`). Kein anderes Modul entscheidet parallel „stattdessen“ für dieselbe Modell-Schnittstelle.
+
+Orthogonal dazu (kein Ersatz des Gates, sondern Data-at-rest bzw. Workflow):
+
+- **RAG:** `mainServiceKnowledge.indexFile()` neutralisiert Chunks bei `FileItem.neutralize=True`.
+- **Agent:** DataSource- und FeatureDataSource-Flags setzen bzw. vererben Neutralisierungspflicht; Sub-Agent-Calls können `requireNeutralization=True` tragen.
+- **Workflows:** Aktion `neutralizeData` neutralisiert explizit extrahierte ContentParts (prüft u. a. `NeutralizationConfig.enabled`, nicht das Session-Flag).
+
+## Neutralisierungs-Trigger (Prioritätsreihenfolge)
+
+**Am AI-Gate (`_shouldNeutralize`)** (Auswertung in der dokumentierten Reihenfolge):
+
+1. **Pro Request:** `AiCallRequest.requireNeutralization` — expliziter Override auf dem Call.
+2. **Chat-/Session-Level:** `ServiceCenterContext.requireNeutralization` (z. B. Workspace, Automation).
+3. **Mandanten-/Feature-Konfiguration:** `NeutralizationConfig.enabled` (DataNeutraliser / Feature-Instanz).
+
+**Quellen gesamt (OR-Logik):** Ist irgendwo Neutralisierung erforderlich (Feature-Instanz, Workflow/Session, konkretes Objekt mit `FileItem.neutralize` / `DataSource.neutralize` / `FeatureDataSource.neutralize`), wird entsprechend verarbeitet. Dokumentierte Produktregel: **Kein `False` von einer Quelle hebt ein `True` einer anderen auf.**
+
+## Was neutralisiert wird
+
+Im zentralen AI-Gate (`_neutralizeRequest`):
+
+- `request.prompt`
+- `request.context` (RAG-Kontext)
+- `request.messages` (OpenAI-artige Nachrichten)
+
+**Engine** (`NeutralizationService`): `processText`, `processFile`, `processBinaryBytes` (synchron/asynchron); Rückübersetzung über `resolveText` / Mappings. Modell-Familien u. a. `NEUTRALIZATION_TEXT` / `NEUTRALIZATION_IMAGE` (Private-LLM-Plugin; externe Provider ohne diese Ratings werden für Neutralisierung nicht gewählt).
+
+**Nicht erneut neutralisieren:** Bereits neutral indexierte RAG-Chunks; Web-Suchergebnisse ohne Mandantendaten (laut Spezifikation).
+
+**Bekannter Ist-Stand Medien:** Bild-Binary wird in der Engine derzeit weitgehend durchgereicht bzw. übersprungen — dedizierter Bild-Neutralisierungspfad ist in der Fachdoku als Lücke / Soll beschrieben, nicht als abgeschlossene Implementierung ausgewiesen.
+
+## Failsafe-Kette
+
+1. **Toggle `FileItem.neutralize`:** Index und Chunks werden synchron gelöscht; Re-Index im Hintergrund verhindert Leaks bei Fehlern in der Nachindexierung.
+2. **Indexierung:** `indexFile()` neutralisiert Text-Chunks bei `FileItem.neutralize=True` → Data-at-rest abgesichert.
+3. **DataSource-Download:** `neutralize`-Flag wird auf erzeugte `FileItem`s vererbt.
+4. **FeatureDataSource:** `_queryFeatureInstance()` setzt bei `neutralize=True` u. a. `requireNeutralization=True` für Sub-Agent-AI-Calls.
+5. **AI-Call:** Bei erzwungener Neutralisierung (`requireNeutralization=True`) schlägt fehlgeschlagene Neutralisierung hart fehl (`RuntimeError` / Blockierung bzw. Entfernen betroffener Message-Teile — kein Durchleiten im Rohzustand).
+6. **`_rehydrateResponse()`:** Als Hilfsmethode vorhanden; automatische Rückübersetzung der Modellantwort ist nicht mehr der Standardpfad.
+
+**Engine-Failsafe (Spezifikation):** Neutralisierung verlangt, Engine nicht verfügbar → nicht weiterverarbeiten; Teilfehler → Teil entfernen, nicht roh weitergeben; fehlendes internes Medienmodell → Medien-Part entfernen.
+
+## NeutralizationPanel (Frontend)
+
+`frontend_nyla/src/pages/views/workspace/NeutralizationPanel.tsx` — Übersicht zu Dateien mit `neutralize`-Flag, Status und Platzhalter-Mappings. Datenbasis u. a. `GET /api/workspace/{instanceId}/files` → `{ files: [...] }`.
+
+## Schlüssel-Dateien
+
+| Bereich | Pfad |
+|--------|------|
+| **Zentrales AI-Gate** | `serviceCenter/services/serviceAi/mainServiceAi.py` |
+| **Neutralisierungs-Engine** | `features/neutralization/serviceNeutralization/mainServiceNeutralization.py` (+ `subProcess*.py`) |
+| **Feature-Config / DB** | `features/neutralization/datamodelFeatureNeutralizer.py`, `interfaceFeatureNeutralizer.py` |
+| **RAG-Index** | `serviceCenter/services/serviceKnowledge/mainServiceKnowledge.py` |
+| **Agent / Quellen** | `serviceCenter/services/serviceAgent/mainServiceAgent.py` (`_resolveDataSource`, `_downloadFromDataSource`, `_queryFeatureInstance`) |
+| **Datei-Toggle / Index** | `routes/routeDataFiles.py` — `PATCH /{fileId}/neutralize` |
+| **Workflow-Aktion** | `workflows/methods/methodContext/actions/neutralizeData.py` |
+| **Kontext** | `serviceCenter/context.py` — `requireNeutralization` |
+| **Flags (Modelle)** | `datamodels/datamodelFiles.py` (`FileItem.neutralize`), `datamodelDataSource.py`, `datamodelFeatureDataSource.py` |
+| **AI-Operationen / Enums** | `datamodels/datamodelAi.py`, `aicore/aicorePluginPrivateLlm.py` |
+
+## Regeln / Invarianten
+
+- **Ein Gate pro Modell-Call:** Sämtlicher Text in Richtung externes LLM für diesen Call läuft über `mainServiceAi` — keine parallele „zweite“ Neutralisierungstelle für dieselbe Schnittstelle.
+- **Hard-Mode:** `requireNeutralization=True` und Neutralisierung scheitert → Call blockieren bzw. Inhalt nicht im Klartext an das Modell geben.
+- **Kein stilles Weiterreichen** sensibler Inhalte bei Pflicht zur Neutralisierung.
+- **Platzhalter:** Mapping `[typ.uuid]` in der DB; `resolveText` für kontrollierte Rückübersetzung.
+- Detaillierte Compliance- und Prozessbeschreibung: `wiki/compliance/Neutralisierung.md`.
diff --git a/b-reference/platform/rbac.md b/b-reference/platform/rbac.md
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+++ b/b-reference/platform/rbac.md
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+
+
+
+
+# RBAC-System
+
+## Überblick
+
+Das Role-Based Access Control bündelt Berechtigungen in **Access Rules** pro Rollenlabel und **Kontext** (DATA, UI, RESOURCE). Auswertung erfolgt zentral über `interfaceRbac.py`; Zielbild laut Architekturdokumentation: möglichst **filternd in der Datenbank** statt voller Tabellen-Scans in Python. Nutzer können **mehrere Rollenlabels** gleichzeitig tragen; die effektive Berechtigung entsteht aus **Öffnungslogik (Union)** über alle Rollen.
+
+## Zwei getrennte Rollensysteme
+
+| | **Mandantenrollen** | **Feature-Instanz-Rollen** |
+|--|---------------------|----------------------------|
+| **Labels (Beispiele)** | `admin`, `user`, `viewer` | `workspace-admin`, `workspace-user`, `workspace-viewer`, feature-spezifisch |
+| **Scope** | `mandateId` | `mandateId` + `featureCode` + `featureInstanceId` |
+| **Zuordnung** | `UserMandateRole` | `FeatureAccessRole` |
+
+**Invariante:** Mandantenrollen und Feature-Instanz-Rollen **nicht vermischen** — kein Zuweisen eines Mandanten-Labels zu `FeatureAccessRole` oder umgekehrt.
+
+Zusätzlich (Systemebene, laut RBAC-Dokument): globale Rollen wie **SysAdmin** / **SystemUser** für mandantenübergreifende Sonderfälle; Mandantenrollen **Admin** / **User** / **Viewer** für Zugriff innerhalb eines Mandats.
+
+## Access Rules (DATA / UI / RESOURCE)
+
+### Kontexte
+
+- **DATA:** Tabellen und Felder; CRUD über `read`, `create`, `update`, `delete` mit Access Levels `a` (all), `m` (my), `g` (group / Mandat), `n` (none); zusätzlich `view`.
+- **UI:** Sichtbarkeit/Aktivierung von Oberflächenelementen; relevant ist **`view`** (boolean). Item-Format: kaskadierender String (z. B. `playground.voice.settings`).
+- **RESOURCE:** Systemressourcen (KI-Modelle, Aktionen, …); ebenfalls primär **`view`**. Item-Format: kaskadierend (z. B. `ai.model.anthropic`).
+
+### Spezifität (pro Rolle)
+
+Innerhalb **einer** Rolle gewinnt die **spezifischste** passende Regel (längster passender Präfix/exakter `item`) gegenüber generischen Regeln (`item = null`).
+
+### Mehrere Rollen
+
+Über Rollen hinweg: **Union** — wenn eine Rolle nach interner Auflösung `view: true` liefert, gilt das Element als sichtbar/erlaubt (OR über Rollen). Für **DATA** werden die **freizügigsten** Stufen über Rollen kombiniert.
+
+### DATA: Öffnungsrechte (CUD vs. Read)
+
+- Ohne Leserecht (`read = n`) keine CUD.
+- Mit `read = m` sind CUD höchstens `m` oder `n`.
+- Mit `read = g` sind CUD höchstens `g`, `m` oder `n`.
+- Mit `read = a` sind alle Stufen für CUD zulässig.
+
+### Systemfelder (DATA)
+
+Felder `id` und Namen mit führendem `_` sind für Anwendungs-CUD geschützt; Connector erzwingt das unabhängig von Access Rules.
+
+### Frontend-Optionen für Rollen
+
+`frontend_options` an Feldern kann statische Listen oder String-Referenzen (z. B. `"user.role"`) nutzen; dynamische Optionen über `/api/options/{optionsName}`. Typ-Hilfen: `gateway/modules/shared/frontendOptionsTypes.py`.
+
+## Schlüssel-Dateien
+
+| Rolle | Pfad |
+|-------|------|
+| RBAC-Auswertung / DB-Schicht | `gateway/modules/interfaces/interfaceRbac.py` |
+| AccessRule- und Permission-Modelle | `gateway/modules/datamodels/` (u. a. RBAC-bezogene Modelle) |
+| Nutzer / Rollenlabels | User-Modell mit `roleLabels` (Multiselect, Union) |
+| Konzept & Feldsemantik | `wiki/appdoc/doc_security_role_based_access.md` |
+
+## Regeln / Invarianten
+
+- Mandanten- vs. Feature-Rollen **strikt trennen** (keine Kreuz-Zuweisung der Label-Typen).
+- **Spezifisch vor generisch** innerhalb einer Rolle; **Union** über Rollen.
+- UI/RESOURCE: Effektiv sichtbar nur, wenn nach Regelauflösung **`view: true`** (kein `hasAccess: false` in Navigationskonzept — nicht berechtigte UI-Einträge werden gar nicht geliefert).
+- DATA: Validierung der Regeln so, dass CUD nicht über dem jeweiligen Read-Level liegen.
+- Performance-Ziel: DATA-Zugriffe mit RBAC-Filter in SQL, nicht erst vollständige Tabellen in Python filtern.
diff --git a/b-reference/private-llm/architecture.md b/b-reference/private-llm/architecture.md
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+
+
+
+
+# Private LLM -- Architektur
+
+## Überblick
+
+Eigenständiger Service für die Verarbeitung sensitiver Daten mit lokalen AI-Modellen (Ollama). Läuft auf einem dedizierten GPU-Server (Infomaniak Swiss Cloud) und wird vom Gateway als Provider-Plugin (`aicorePluginPrivateLlm.py`) angesprochen. Kein Datenabfluss an externe Cloud-APIs.
+
+## Technologie-Stack
+
+| Layer | Technologie |
+|-------|------------|
+| Framework | FastAPI (Python) |
+| AI Runtime | Ollama (lokale Vision/Text-Modelle) |
+| PDF-Support | PyMuPDF (fitz) |
+| Hosting | Infomaniak Swiss Cloud (GPU) |
+| Deployment | GitHub Actions → `main` Branch |
+
+## Modelle
+
+| Externer Name | Internes Ollama-Modell | Typ |
+|--------------|----------------------|-----|
+| `poweron-text-general` | `qwen2.5:7b` | Text |
+| `poweron-vision-general` | `qwen2.5vl:7b` | Vision |
+| `poweron-vision-deep` | `granite3.2-vision` | Vision |
+
+## API-Routen
+
+| Modul | Zweck |
+|-------|-------|
+| `routeApi.py` | Analyse-API: Bild-/PDF-Analyse mit Prompt, Modellauswahl |
+| `routeOpenAi.py` | OpenAI-kompatibles Chat-Completion-API (für Cursor-Integration) |
+| `routeWeb.py` | Web-UI für manuelle Tests |
+
+## Integration mit Gateway
+
+Der Gateway nutzt das Private LLM über `aicorePluginPrivateLlm.py` als Provider für:
+- **Neutralisierung:** Text-Analyse mit `poweron-text-general`
+- **Sensitive Datenverarbeitung:** Vision-Analyse von Dokumenten (Rechnungen, Belege, Handschrift)
+- **Keine Billing-Kosten** für mandanteninterne LLM-Calls (eigene Infrastruktur)
+
+## Sicherheit
+
+- API-Key-Authentifizierung (`X-API-Key` Header)
+- Separater Cursor-API-Key für OpenAI-kompatible Endpoints (Bearer Token)
+- Rate-Limiting per API-Key (Token Bucket, konfigurierbar)
+- Konfiguration über `config.ini` + Environment-Variablen (Secrets nie im Code)
+
+## Schlüssel-Dateien
+
+| Datei | Rolle |
+|-------|-------|
+| `app.py` | FastAPI-Einstieg, Router-Mount |
+| `config.py` | Konfiguration, Model-Mapping, Auth, Rate-Limiting, Request/Response-Modelle |
+| `routeApi.py` | Analyse-Endpunkte (Bild, PDF) |
+| `routeOpenAi.py` | OpenAI-kompatibles Chat-API |
+| `routeWeb.py` | Test-UI |
+
+## Regeln / Invarianten
+
+- Alle Daten werden **lokal** verarbeitet -- kein Weiterleiten an externe APIs
+- Model-Mapping ist die einzige Stelle für Namensauflösung (`MODEL_MAPPING` in `config.py`)
+- API-Keys werden aus `config.ini` oder Environment gelesen, nie hardcoded
+- PDF-Verarbeitung rendert Seiten als Bilder für Vision-Modelle (max 5 Seiten)
diff --git a/b-reference/product.md b/b-reference/product.md
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+++ b/b-reference/product.md
@@ -0,0 +1,56 @@
+
+
+
+# PowerOn Portal -- Komponentenübersicht
+
+## Produkt
+
+PowerOn Portal ist eine Multi-Tenant SaaS-Plattform mit Feature-Store-Modell, AI-Agent-Workspace und mandantenweiter Datenneutralisierung.
+
+## Komponenten
+
+| Komponente | Repository | Technologie | Beschreibung |
+|-----------|-----------|-------------|-------------|
+| Frontend Nyla | frontend_nyla | React/TypeScript, Vite | Zentrales UI für alle Features |
+| Gateway | gateway | FastAPI, Python, PostgreSQL | Backend REST-API, Services, AI-Core |
+| Private LLM | private-llm | Python | Internes LLM für Neutralisierung + sensitive Daten |
+| Teams Bot | service-teams-browser-bot | Node.js/.NET | Bot für Teams-Meeting-Teilnahme |
+| Wiki | wiki | Markdown | Dokumentation (dieses Repo) |
+
+## Technologie-Stack
+
+| Layer | Technologie | Pfad |
+|-------|------------|------|
+| Backend (Gateway) | FastAPI (Python), PostgreSQL | `@poweron/gateway` |
+| Frontend | React/TypeScript (Vite) | `@poweron/frontend_nyla` |
+| AI Core | Multi-Provider (Anthropic, OpenAI, Mistral, Perplexity, Tavily, PrivateLLM) | `@poweron/gateway/modules/aicore` |
+| DB-Connector | PostgreSQL mit pgvector (Embeddings) | `@poweron/gateway/modules/connectors/connectorDbPostgre.py` |
+
+## Feature-Module
+
+| Feature | Beschreibung |
+|---------|-------------|
+| `workspace` | AI-Agent-Workspace mit Chat, Tools, RAG, Streaming |
+| `automation` | Workflow-Automatisierung (v1) |
+| `automation2` | Flow-Editor n8n-Style (v2) |
+| `chatbot` | Chatbot-Feature |
+| `commcoach` | Kommunikations-Coach mit Voice, Dossier, UDB |
+| `neutralization` | Datenneutralisierungs-Service und Config |
+| `trustee` | Trustee/Treuhand-Feature (Buchhaltung, Positionen) |
+| `realEstate` | Immobilien-Feature |
+| `teamsbot` | MS Teams Bot |
+
+## Coding-Konventionen
+
+- Alle internen Funktionen beginnen mit `_` Prefix
+- camelCase für Variablen und Funktionsnamen (kein snake_case)
+- Keine Browser-Dialoge — `useConfirm()` / `usePrompt()` Hooks
+- Fehler propagieren — keine stillen Fallbacks bei kritischen Pfaden
+- Pydantic-Models als einzige Quelle für UI-Feld-Definitionen
+- `PowerOnModel` als Basis mit `sysCreatedAt`, `sysCreatedBy`, `sysModifiedAt`, `sysModifiedBy`
+
+## Cross-Cutting Concerns
+
+- Neutralisierung: Gateway ↔ Private LLM (→ platform/neutralization.md)
+- RBAC: Gateway ↔ Frontend (→ platform/rbac.md)
+- Navigation: Gateway → Frontend (→ platform/navigation.md)
diff --git a/b-reference/teams-bot/architecture.md b/b-reference/teams-bot/architecture.md
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+
+
+
+
+# Teams Meeting Bot -- Architektur
+
+## Überblick
+
+AI-gesteuerter Meeting-Bot für Microsoft Teams. Tritt Meetings als regulärer Teilnehmer bei (Browser-Automation via Playwright/Chromium), erfasst Live-Transkripte, reagiert per Sprache (TTS) und/oder Chat. Kein Teams-Graph-SDK nötig -- funktioniert mandantenübergreifend ohne Admin-Approval.
+
+## System-Architektur
+
+```
+┌────────────┐ SSE ┌──────────────┐ WebSocket ┌─────────────┐
+│ Frontend │◄──────────────│ Gateway │◄───────────────│ Bot Service │
+│ (Nyla UI) │ │ (AI, TTS, │ HTTP (join/ │ (Playwright │
+│ │ │ Sessions) │ leave) │ Chromium) │
+└────────────┘ └──────────────┘ └─────────────┘
+```
+
+| Verbindung | Protokoll | Zweck |
+|------------|----------|-------|
+| Gateway ↔ Bot | WebSocket | Echtzeit: Transkripte, Chat, Audio, Status |
+| Gateway → Bot | HTTP | Session-Steuerung (join, leave, status) |
+| Frontend ← Gateway | SSE | Live-Transkript-Stream für UI |
+
+## Kernfähigkeiten
+
+- **Live Transcription:** Erfasst Untertitel mit Sprecher-Zuordnung, streamt via SSE
+- **AI-Analyse:** Transkript-Segmente werden durch AI-Modell (GPT-4o-mini / Claude) analysiert
+- **Voice Response:** TTS-Audio wird über den Mikrofon-Kanal ins Meeting gespielt
+- **Chat Response:** Bot kann Chat-Nachrichten ins Meeting schreiben
+- **Multi-Session:** Mehrere Bot-Instanzen parallel in verschiedenen Meetings
+
+## Use Cases
+
+| UC | Beschreibung |
+|----|-------------|
+| AI Meeting Assistant | Bot nimmt teil, hört zu, antwortet auf Ansprache ("Hey Nyla, ...") |
+| Live Transcription | Echtzeit-Transkript-Stream für Teilnehmer ausserhalb des Meetings |
+| Meeting Summary | AI-generierte Zusammenfassung nach Meeting-Ende |
+| Multi-Bot | Mehrere parallele Sessions in verschiedenen Meetings |
+
+## Integration mit Gateway
+
+Der Gateway (Feature `teamsbot`) verwaltet Sessions und stellt die AI-Pipeline bereit:
+- Session-Lifecycle: erstellen, starten, stoppen
+- WebSocket-Verbindung pro Session
+- AI-Analyse der Transkript-Segmente via `serviceAi`
+- TTS-Generierung für Voice-Responses
+
+## Schlüssel-Dateien
+
+| Datei / Bereich | Rolle |
+|-----------------|-------|
+| `gateway/modules/features/teamsbot/` | Gateway-seitiges Feature-Modul |
+| `service-teams-browser-bot/` | Eigenständiger Bot-Service (separates Repository) |
+
+## Regeln / Invarianten
+
+- Bot tritt als **regulärer Web-Teilnehmer** bei (Browser-Automation), nicht via Graph Communications SDK
+- Jede Session läuft in einer **eigenen Browser-Instanz** (Isolation)
+- Authentifizierter Join (mit Microsoft-Account) oder Anonymous Guest -- je nach Konfiguration
+- Gateway ist die **einzige** Schnittstelle für AI-Aufrufe und TTS -- der Bot-Service selbst hat keine AI-Logik
diff --git a/c-work/1-plan/2026-03-codeeditor-phase1.md b/c-work/1-plan/2026-03-codeeditor-phase1.md
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+++ b/c-work/1-plan/2026-03-codeeditor-phase1.md
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+# PR: CodeEditor Feature - Phase 1 (MVP)
+
+## Summary
+
+Neues Feature "CodeEditor" -- Cursor-artiger AI-gestuetzter Text-Editor als eigenstaendiges Feature im Gateway mit Frontend-Integration in Nyla UI. Komplett unabhaengig vom bestehenden Workflow-System (Option B).
+
+- Eigenstaendiger Verarbeitungspfad in `features/codeeditor/` ohne Eingriff in `workflowManager.py`
+- AI-Aufrufe direkt ueber `interfaceAiObjects.callWithTextContext()` mit voller Model Selection, Failover und Billing
+- SSE-Streaming via bestehender `EventManager`-Infrastruktur aus dem Chatbot-Feature
+- Frontend: Drei-Panel-Layout (FileList, Chat, DiffPreview) mit Accept/Reject fuer Datei-Aenderungen
+- Phase 1 = Single-Shot Mode (1 AI Call pro Prompt). Phase 2 (Agent Loop mit Tool Calling) ist geplant.
+
+## Neue Dateien
+
+### Backend (Gateway)
+
+| Datei | Beschreibung |
+|---|---|
+| `gateway/modules/features/codeeditor/__init__.py` | Package init |
+| `gateway/modules/features/codeeditor/datamodelCodeeditor.py` | Pydantic Models: FileContext, ResponseSegment, FileEditProposal, FileVersion, MIME-Type Validierung |
+| `gateway/modules/features/codeeditor/mainCodeeditor.py` | Feature-Registration: RBAC UI/Resource Objects, Template Roles (Plug&Play) |
+| `gateway/modules/features/codeeditor/fileContextManager.py` | Text-Dateien aus DB laden, MIME-Type filtern |
+| `gateway/modules/features/codeeditor/promptAssembly.py` | System Prompt Builder mit Datei-Kontext und Format-Instruktionen |
+| `gateway/modules/features/codeeditor/responseParser.py` | AI-Antwort in typisierte Segmente parsen (text, code_block, file_edit) |
+| `gateway/modules/features/codeeditor/codeEditorProcessor.py` | Orchestrator: Files laden -> Prompt bauen -> AI call -> Parse -> SSE emit |
+| `gateway/modules/features/codeeditor/routeFeatureCodeeditor.py` | 8 FastAPI Endpoints inkl. SSE Stream |
+
+### Frontend (Nyla UI)
+
+| Datei | Beschreibung |
+|---|---|
+| `frontend_nyla/src/pages/views/codeeditor/CodeEditorPage.tsx` | Drei-Panel-Layout mit resizable Panels |
+| `frontend_nyla/src/pages/views/codeeditor/FileListPanel.tsx` | Datei-Auswahl mit Checkboxen |
+| `frontend_nyla/src/pages/views/codeeditor/DiffPreviewPanel.tsx` | Diff-Anzeige mit Accept/Reject |
+| `frontend_nyla/src/pages/views/codeeditor/useCodeEditor.ts` | SSE Hook mit Auth/CSRF, File-Selection, Edit-State |
+| `frontend_nyla/src/pages/views/codeeditor/CodeEditor.module.css` | Styling |
+| `frontend_nyla/src/pages/views/codeeditor/index.ts` | Export |
+
+## Geaenderte Dateien
+
+| Datei | Aenderung |
+|---|---|
+| `gateway/modules/datamodels/datamodelChat.py` | `WORKFLOW_CODEEDITOR = "CodeEditor"` zu `WorkflowModeEnum` hinzugefuegt |
+| `gateway/modules/routes/routeSystem.py` | `codeeditor` in `_getFeatureUiObjects()` fuer Navigation API |
+| `gateway/modules/system/mainSystem.py` | Store-Resource `resource.store.codeeditor` |
+| `gateway/modules/interfaces/interfaceBootstrap.py` | `resource.store.codeeditor` in `storeResources` |
+| `frontend_nyla/src/pages/FeatureView.tsx` | Import + `codeeditor` in `VIEW_COMPONENTS` Registry |
+| `frontend_nyla/src/config/pageRegistry.tsx` | `feature.codeeditor` Icon (FaFileAlt) |
+| `frontend_nyla/src/types/mandate.ts` | `codeeditor` in `FEATURE_REGISTRY` mit Views |
+| `frontend_nyla/src/pages/Store.tsx` | Icon + Beschreibung fuer Feature Store |
+| `frontend_nyla/src/App.tsx` | Route `editor` fuer CodeEditorPage |
+
+## API Endpoints
+
+| Endpoint | Methode | Beschreibung |
+|---|---|---|
+| `/api/codeeditor/{instanceId}/start/stream` | POST | Workflow starten + SSE-Stream |
+| `/api/codeeditor/{instanceId}/{workflowId}/stop` | POST | Workflow stoppen |
+| `/api/codeeditor/{instanceId}/{workflowId}/chatData` | GET | Polling-Fallback |
+| `/api/codeeditor/{instanceId}/workflows` | GET | Workflows auflisten |
+| `/api/codeeditor/{instanceId}/files` | GET | Text-Dateien auflisten |
+| `/api/codeeditor/{instanceId}/files/{fileId}/content` | GET | Datei-Inhalt laden |
+| `/api/codeeditor/{instanceId}/{workflowId}/apply` | POST | Aenderung akzeptieren |
+
+## Architektur-Entscheide
+
+- **Option B**: Eigenstaendiger Pfad, kein Eingriff in WorkflowManager/WorkflowProcessor
+- **AI-Zugriff**: Direkt ueber `interfaceAiObjects.callWithTextContext()` -- nutzt bestehende Model Selection, Failover, Provider-Filtering, Billing
+- **SSE**: Segment-weise Emission (nicht token-weise), da aicore aktuell kein Token-Streaming hat
+- **Feature-Discovery**: Plug&Play via `mainCodeeditor.py` + `routeFeatureCodeeditor.py` (automatisch entdeckt durch `registry.py`)
+
+## Test Plan
+
+- [ ] Gateway startet ohne Fehler mit neuem Feature
+- [ ] Feature erscheint im Feature Store und kann aktiviert werden
+- [ ] Navigation zeigt CodeEditor-Instanz mit Icon und Views (Editor, Workflows)
+- [ ] Editor-View laedt: FileList links, Chat mitte, DiffPreview rechts
+- [ ] Panel-Divider sind verschiebbar
+- [ ] Text-Dateien werden in FileList angezeigt (nur text-basierte MIME-Types)
+- [ ] Chat-Prompt mit ausgewaehlten Dateien sendet SSE-Request
+- [ ] AI-Antwort wird als Chat-Nachrichten gerendert
+- [ ] file_edit Vorschlaege erscheinen im DiffPreview Panel
+- [ ] Accept/Reject Buttons funktionieren (Accept ueberschreibt Datei in DB)
+- [ ] Follow-Up Prompts nutzen bestehenden Workflow (kein neuer Workflow pro Message)
+- [ ] Keine Auswirkungen auf bestehende Features (Chatplayground, Automation, Chatbot, Teamsbot)
diff --git a/c-work/1-plan/2026-03-cursor-style-chat.md b/c-work/1-plan/2026-03-cursor-style-chat.md
new file mode 100644
index 0000000..15843c1
--- /dev/null
+++ b/c-work/1-plan/2026-03-cursor-style-chat.md
@@ -0,0 +1,263 @@
+---
+name: Cursor-Style Chat Feature MVP
+overview: Integration eines Cursor-artigen File-Editing-Chat-Features als neues Feature "codeeditor" im Gateway und der Nyla UI. Nutzt aicore-Modelle direkt, Chat-Datenmodelle vom Chatplayground, SSE-Streaming vom Chatbot-Feature. Nur Text-Dokumente (Markdown, JSON, YAML, Code). Dateien werden hochgeladen (kein SharePoint), spaeter mit virtuellen Folder-Tags strukturiert. Apply erzeugt neue lokale Dokument-Versionen.
+todos:
+ - id: extend-workflow-mode
+ content: WorkflowModeEnum um WORKFLOW_CODEEDITOR erweitern in datamodelChat.py + FileContext/FileEditProposal Models
+ status: pending
+ - id: backend-feature-scaffold
+ content: "Feature-Scaffold: mainCodeeditor.py (Registrierung) + routeFeatureCodeeditor.py (Endpoints, Vorlage: chatplayground)"
+ status: pending
+ - id: file-context-manager
+ content: "fileContextManager.py: Hochgeladene Text-Dateien laden, Workspace-Snapshot erstellen (kein SharePoint)"
+ status: pending
+ - id: prompt-assembly
+ content: "promptAssembly.py: Cursor-artiger System Prompt Builder mit Datei-Kontext und Format-Instruktionen"
+ status: pending
+ - id: response-parser
+ content: "responseParser.py: AI-Antwort in Document-Segmente parsen (text, code_block, file_edit, etc.)"
+ status: pending
+ - id: frontend-feature-register
+ content: "FeatureView.tsx: codeeditor Views registrieren, CodeEditorPage + FileBrowserPanel + DiffPreviewPanel erstellen"
+ status: pending
+ - id: frontend-hooks
+ content: "useCodeEditor.ts Hook: Erweitert Playground-Pattern um File-Selection und Edit-Management"
+ status: pending
+isProject: false
+---
+
+# MVP: Cursor-Style File-Editing Chat Feature ("CodeEditor")
+
+## Professionelle Einschaetzung
+
+### Kernfrage: aicore-Modelle direkt oder ueber Chat-Komponente?
+
+**Empfehlung: Die bestehenden aicore-Modelle direkt nutzen** (nicht ueber eine externe Cursor-Chat-Komponente).
+
+Begruendung:
+
+- Die aicore-Infrastruktur (`aicoreModelRegistry`, `aicoreModelSelector`, Plugin-System) ist bereits produktionsreif mit Failover, Billing, RBAC und Multi-Provider-Support
+- Eine externe Cursor-Komponente wuerde eine Abhaengigkeit schaffen, die schwer zu kontrollieren ist
+- Der Mehrwert liegt nicht im LLM-Aufruf (den beherrscht aicore), sondern in der **Prompt-Orchestrierung** (System Prompt + Context + Tool Definitions) und dem **Response Parsing** (Antwort in Dokument-Segmente zerlegen)
+- Der neue "Cursor-Style" Layer wird **auf aicore aufgebaut**, nicht neben oder statt aicore
+
+### Was vom Chatplayground uebernommen werden kann
+
+Sehr viel -- die Grundarchitektur ist ideal:
+
+- **ChatWorkflow** Datenmodell: 1:1 wiederverwendbar (neuer `workflowMode: "CodeEditor"`)
+- **ChatMessage** + **ChatDocument**: Vollstaendig wiederverwendbar fuer Chat-Verlauf und Datei-Referenzen
+- **Polling-Mechanismus** (`getUnifiedChatData` mit `afterTimestamp`): Sofort nutzbar
+- **SSE-Infrastruktur** (aus Chatbot-Feature): Kann fuer Echtzeit-Streaming aktiviert werden
+- **PlaygroundPage UI-Pattern**: Resizable Two-Column Layout, Messages-Komponente, File-Upload, Input-Footer
+- **Route-Pattern** (`routeFeatureChatplayground.py`): Als Vorlage fuer neue Feature-Route
+- **Feature-Registrierung**: `VIEW_COMPONENTS` Registry in `FeatureView.tsx`, Backend `mainChatplayground.py`
+
+### Was NEU gebaut werden muss
+
+1. **File-Context-Manager** (Backend): Hochgeladene Text-Dateien als "Workspace" laden und als Kontext bereitstellen (kein SharePoint, spaeter virtuelle Folder-Tags)
+2. **Prompt Assembly Service** (Backend): System Prompt mit File-Kontext und Cursor-artigen Instruktionen zusammenbauen
+3. **Response Document Parser** (Backend): AI-Antwort in typisierte Dokument-Segmente zerlegen (text, code_block, file_edit, etc.)
+4. **Diff-Preview UI** (Frontend): Text-Aenderungen als Diff anzeigen mit Accept/Reject
+5. **File-List Panel** (Frontend): Hochgeladene Dateien auflisten und als Kontext auswaehlen (spaeter: virtuelle Folder-Tags)
+6. **SSE-Integration** (Backend+Frontend): Echtzeit-Streaming ueber bestehende EventManager-Infrastruktur
+
+---
+
+## Architektur
+
+```mermaid
+flowchart TB
+ subgraph ui [Nyla UI - Frontend]
+ CodeEditorPage["CodeEditorPage\n(neue View)"]
+ FileList["FileListPanel\n(hochgeladene Dateien)"]
+ ChatPanel["ChatPanel\n(Messages + SSE)"]
+ DiffPreview["DiffPreviewPanel\n(Text-Diffs)"]
+ CodeEditorPage --> FileList
+ CodeEditorPage --> ChatPanel
+ CodeEditorPage --> DiffPreview
+ end
+
+ subgraph gw [Gateway - Backend]
+ Route["routeFeatureCodeeditor.py\n(FastAPI Endpoints)"]
+ SSE["SSE Stream Endpoint\n(EventManager)"]
+ FileCtx["fileContextManager.py\n(Text-Dateien laden)"]
+ PromptAsm["promptAssembly.py\n(System Prompt Builder)"]
+ RespParse["responseParser.py\n(Document Segmentation)"]
+ Route --> FileCtx
+ Route --> PromptAsm
+ PromptAsm --> AiService["serviceAi\n(bestehend)"]
+ AiService --> AiCore["aicore\n(ModelRegistry + Plugins)"]
+ RespParse --> Route
+ RespParse --> SSE
+ end
+
+ subgraph data [Datenspeicher]
+ DB["Gateway DB\n(interfaceDbComponent)\nHochgeladene Dateien"]
+ end
+
+ ChatPanel -->|"POST /api/codeeditor/.../start"| Route
+ ChatPanel -->|"GET .../stream (SSE)"| SSE
+ FileList -->|"GET .../files"| Route
+ DiffPreview -->|"POST .../apply"| Route
+ FileCtx --> DB
+```
+
+
+
+---
+
+## MVP Scope: Konkrete Implementierung
+
+### Backend: Gateway
+
+**1. Neues Feature `codeeditor`**
+
+- Datei: `gateway/modules/features/codeeditor/mainCodeeditor.py`
+- Registrierung analog zu `mainChatplayground.py` (RBAC, Feature-Config)
+
+**2. Routes**
+
+- Datei: `gateway/modules/features/codeeditor/routeFeatureCodeeditor.py`
+- Kopie von `routeFeatureChatplayground.py` als Basis, erweitert um:
+
+
+| Endpoint | Methode | Beschreibung |
+| -------------------------------------- | ------- | ---------------------------------------------------------- |
+| `/{instanceId}/start` | POST | Workflow starten (nutzt `chatStart` mit mode `CodeEditor`) |
+| `/{instanceId}/{workflowId}/stop` | POST | Workflow stoppen |
+| `/{instanceId}/{workflowId}/stream` | GET | SSE-Stream fuer Echtzeit-Updates (Messages, Logs, Edits) |
+| `/{instanceId}/{workflowId}/chatData` | GET | Fallback-Polling fuer Chat-Daten |
+| `/{instanceId}/workflows` | GET | Workflows auflisten |
+| `/{instanceId}/files` | GET | Hochgeladene Text-Dateien auflisten |
+| `/{instanceId}/files/{fileId}/content` | GET | Text-Datei-Inhalt laden |
+| `/{instanceId}/{workflowId}/apply` | POST | Aenderung als neue Dokument-Version speichern |
+
+
+**3. WorkflowMode Erweiterung**
+
+- Datei: `gateway/modules/datamodels/datamodelChat.py`
+- Neuer Enum-Wert: `WORKFLOW_CODEEDITOR = "CodeEditor"` in `WorkflowModeEnum`
+
+**4. File Context Manager**
+
+- Datei: `gateway/modules/features/codeeditor/fileContextManager.py`
+- Laedt hochgeladene Text-Dateien aus Gateway DB (`interfaceDbComponent`)
+- Unterstuetzte Formate: `.md`, `.txt`, `.json`, `.yaml`, `.yml`, `.xml`, `.csv`, `.py`, `.js`, `.ts`, `.html`, `.css`, `.sql`
+- Baut einen "Workspace-Snapshot": Dateiliste + Inhalte der vom User ausgewaehlten Dateien
+- Validiert MIME-Types (nur text-basierte Dateien akzeptieren)
+- Spaeter erweiterbar: virtuelle Folder-Tags pro Datei fuer Strukturierung
+
+**5. Prompt Assembly**
+
+- Datei: `gateway/modules/features/codeeditor/promptAssembly.py`
+- Baut System Prompt nach Cursor-Muster (dokumentiert in `wiki/cursor-doc/doc_cursor_ai_agent_architecture.md`)
+- Injiziert: Datei-Kontexte, Benutzer-Instruktionen, Antwort-Format-Vorgaben
+- Nutzt `aiService.callAiContent()` oder `interfaceAiObjects.callWithTextContext()` als LLM-Aufruf
+
+**6. Response Document Parser**
+
+- Datei: `gateway/modules/features/codeeditor/responseParser.py`
+- Parst AI-Antwort in typisierte Segmente: `text`, `code_block`, `code_reference`, `file_edit`
+- Speichert Segmente als erweiterte `ChatMessage` Eintraege (mit `actionMethod: "codeeditor"`)
+- Spezifikation: `wiki/cursor-doc/doc_cursor_response_json_structure.md`
+
+### Frontend: Nyla UI
+
+**7. Feature-Registrierung**
+
+- Datei: `frontend_nyla/src/pages/FeatureView.tsx`
+- Neuer Eintrag in `VIEW_COMPONENTS`:
+
+```typescript
+codeeditor: {
+ editor: CodeEditorPage,
+ workflows: WorkflowsPage, // wiederverwendet
+}
+```
+
+**8. CodeEditorPage**
+
+- Datei: `frontend_nyla/src/pages/views/codeeditor/CodeEditorPage.tsx`
+- Drei-Panel-Layout (File-Browser links, Chat mitte, Diff-Preview rechts)
+- Nutzt bestehende `Messages` Komponente, `useResizablePanels`, `usePlayground`-Pattern
+
+**9. File List Panel**
+
+- Datei: `frontend_nyla/src/components/CodeEditor/FileListPanel.tsx`
+- Flache Liste der hochgeladenen Text-Dateien mit Checkbox-Auswahl
+- Upload-Button fuer neue Dateien (Drag & Drop wiederverwendet aus Playground)
+- Ausgewaehlte Dateien werden als Kontext an den Chat gesendet (analog `listFileId`)
+- Spaeter erweiterbar: virtuelle Folder-Tags als Gruppierung
+
+**10. Diff Preview Panel**
+
+- Datei: `frontend_nyla/src/components/CodeEditor/DiffPreviewPanel.tsx`
+- Zeigt `file_edit` Segmente aus der AI-Antwort als Text-Diff an
+- Accept/Reject Buttons pro Aenderung
+- Accept erzeugt neue Dokument-Version (POST `/{instanceId}/{workflowId}/apply`)
+- MVP: einfacher Side-by-Side Text-Diff (kein vollstaendiger Code-Editor noetig)
+
+**11. Hooks**
+
+- Datei: `frontend_nyla/src/hooks/useCodeEditor.ts`
+- Erweitert `useDashboardInputForm` Pattern um:
+ - `selectedFiles: string[]` (ausgewaehlte Kontext-Dateien)
+ - `pendingEdits: FileEdit[]` (vorgeschlagene Aenderungen)
+ - `applyEdit(editId)` / `rejectEdit(editId)` Aktionen
+
+### Datenmodell-Erweiterungen
+
+**12. Neue Pydantic Models** (in bestehendem `datamodelChat.py` oder eigenem File)
+
+```python
+class FileContext(BaseModel):
+ fileId: str
+ fileName: str
+ content: Optional[str] = None
+ mimeType: str
+ tags: List[str] = Field(default_factory=list) # virtuelle Folder-Tags (spaeter)
+
+class FileEditProposal(BaseModel):
+ id: str = Field(default_factory=lambda: str(uuid.uuid4()))
+ fileId: str # Referenz auf bestehende Datei
+ fileName: str
+ operation: str # "edit" | "create"
+ oldContent: Optional[str] = None
+ newContent: str
+ diffSummary: Optional[str] = None # Kurzbeschreibung der Aenderung
+ status: str = "pending" # "pending" | "accepted" | "rejected"
+
+class FileVersion(BaseModel):
+ id: str = Field(default_factory=lambda: str(uuid.uuid4()))
+ sourceFileId: str # Original-Datei
+ editProposalId: str # Referenz auf akzeptiertes FileEditProposal
+ newFileId: str # Neue Datei-Version in DB
+ createdAt: float = Field(default_factory=getUtcTimestamp)
+```
+
+---
+
+## Entschiedene Design-Entscheide
+
+1. **Datenquelle**: Hochgeladene Dateien im System (kein SharePoint). Spaeter: virtuelle Folder-Tags pro Datei fuer Strukturierung
+2. **Dateitypen**: Nur Text-basierte Dokumente (Markdown, JSON, YAML, Code, etc.)
+3. **Apply-Mechanismus**: Erzeugt neue lokale Dokument-Version in der DB (keine externe Synchronisation)
+4. **Streaming**: SSE ueber bestehende `EventManager`-Infrastruktur aus dem Chatbot-Feature
+
+---
+
+## SSE-Integration (Details)
+
+Nutzt die bestehende Infrastruktur aus `gateway/modules/features/chatbot/streaming/events.py`:
+
+- **EventManager** Singleton: `get_event_manager()` - verwaltet async Queues pro Workflow
+- **Event-Emission**: In `interfaceDbChat.createMessage()` und `createLog()` bereits eingebaut
+- **Neuer SSE-Endpoint**: `GET /api/codeeditor/{instanceId}/{workflowId}/stream`
+- **Event-Typen fuer CodeEditor**:
+ - `chatdata` (bestehend): Messages, Logs, Stats
+ - `file_edit` (neu): FileEditProposal Events fuer Echtzeit-Diff-Updates
+ - `file_version` (neu): Neue Datei-Version erstellt (nach Apply)
+- **Frontend**: `useCodeEditor` Hook oeffnet `EventSource` statt Polling
+- **Fallback**: `chatData` Polling-Endpoint bleibt als Fallback verfuegbar
+
diff --git a/c-work/1-plan/2026-03-web-image-search.md b/c-work/1-plan/2026-03-web-image-search.md
new file mode 100644
index 0000000..240fd65
--- /dev/null
+++ b/c-work/1-plan/2026-03-web-image-search.md
@@ -0,0 +1,361 @@
+# Refactoring Concept: Add WEB_SEARCH_MEDIA Operation Type
+
+## Executive Summary
+
+**Refactoring Goal**: Add image search capability by introducing `WEB_SEARCH_MEDIA` operation type and Google Custom Search connector.
+
+**Current State**:
+- ✅ `WEB_SEARCH_DATA` already exists (replaces former `WEB_SEARCH`)
+- ✅ Tavily connector handles `WEB_SEARCH_DATA` for web page/content search
+- ✅ `AiCallPromptWebSearchData` model exists
+
+**Target State**:
+- Add `WEB_SEARCH_MEDIA` operation type for image/media search
+- Create Google Custom Search connector for `WEB_SEARCH_MEDIA`
+- Create `AiCallPromptWebSearchMedia` model
+- Add `ai.searchImages` action using `WEB_SEARCH_MEDIA`
+
+**Estimated Complexity**: Medium (1-2 days development)
+
+**Integration Impact**: Low - additive changes, no breaking changes
+
+---
+
+## 1. Current Architecture
+
+### 1.1 Operation Types
+
+**Current Operation Types** (`gateway/modules/datamodels/datamodelAi.py`):
+```python
+class OperationTypeEnum(str, Enum):
+ # ... existing operations ...
+
+ # Web Operations
+ WEB_SEARCH_DATA = "webSearchData" # Web page search (Tavily) ✅ EXISTS
+ WEB_CRAWL = "webCrawl" # Web crawl for a given URL
+```
+
+**Target Operation Types**:
+```python
+class OperationTypeEnum(str, Enum):
+ # ... existing operations ...
+
+ # Web Operations
+ WEB_SEARCH_DATA = "webSearchData" # Web page search (Tavily) ✅ EXISTS
+ WEB_SEARCH_MEDIA = "webSearchMedia" # Image/media search (Google) ⬅️ NEW
+ WEB_CRAWL = "webCrawl" # Web crawl for a given URL
+```
+
+### 1.2 Model Capabilities
+
+**Tavily Connector** (`gateway/modules/aicore/aicorePluginTavily.py`):
+- ✅ Registered for `WEB_SEARCH_DATA` (rating: 9)
+- ✅ Registered for `WEB_CRAWL` (rating: 10)
+- ❌ Does NOT support image search - designed for web/text content only
+
+**Model Selection**:
+- Dynamic model selection routes based on `OperationTypeEnum` in `AiCallOptions`
+- Models register capabilities via `operationTypes` with ratings (1-10)
+- System automatically selects best model for each operation type
+
+---
+
+## 2. Refactoring Plan
+
+### 2.1 Add WEB_SEARCH_MEDIA Operation Type
+
+**File**: `gateway/modules/datamodels/datamodelAi.py`
+
+**Changes**:
+```python
+class OperationTypeEnum(str, Enum):
+ # ... existing operations ...
+
+ # Web Operations
+ WEB_SEARCH_DATA = "webSearchData" # Web page search (Tavily)
+ WEB_SEARCH_MEDIA = "webSearchMedia" # Image/media search (Google) ⬅️ ADD
+ WEB_CRAWL = "webCrawl" # Web crawl for a given URL
+```
+
+### 2.2 Create AiCallPromptWebSearchMedia Model
+
+**File**: `gateway/modules/datamodels/datamodelAi.py`
+
+**Add after `AiCallPromptWebSearchData`**:
+```python
+class AiCallPromptWebSearchMedia(BaseModel):
+ """Structured prompt format for WEB_SEARCH_MEDIA operation - returns list of image URLs."""
+
+ instruction: str = Field(description="Search instruction/query for finding relevant images")
+ maxResults: Optional[int] = Field(default=10, description="Maximum number of images to return (default: 10)")
+ imageType: Optional[str] = Field(default=None, description="Image type filter: 'photo', 'clipart', 'lineart', 'animated'")
+ size: Optional[str] = Field(default=None, description="Image size filter: 'small', 'medium', 'large', 'xlarge'")
+ color: Optional[str] = Field(default=None, description="Color filter: 'color', 'grayscale', 'transparent'")
+ country: Optional[str] = Field(default=None, description="Two-digit country code (lowercase, e.g., ch, us, de, fr)")
+ language: Optional[str] = Field(default=None, description="Language code (lowercase, e.g., de, en, fr)")
+```
+
+### 2.3 Create Google Custom Search Connector
+
+**New File**: `gateway/modules/aicore/aicorePluginGoogle.py`
+
+**Structure** (similar to `aicorePluginTavily.py`):
+```python
+class AiGoogle(BaseConnectorAi):
+ """Google Custom Search connector for image search."""
+
+ def getModels(self) -> List[AiModel]:
+ """Get Google Custom Search model."""
+ return [
+ AiModel(
+ name="google-custom-search",
+ displayName="Google Custom Search",
+ connectorType="google",
+ apiUrl="https://www.googleapis.com/customsearch/v1",
+ # ... model configuration ...
+ operationTypes=createOperationTypeRatings(
+ (OperationTypeEnum.WEB_SEARCH_MEDIA, 9)
+ ),
+ functionCall=self._routeWebOperation,
+ # ...
+ )
+ ]
+
+ async def _routeWebOperation(self, modelCall: AiModelCall) -> "AiModelResponse":
+ """Route web operation based on operation type."""
+ operationType = modelCall.options.operationType
+
+ if operationType == OperationTypeEnum.WEB_SEARCH_MEDIA:
+ return await self.webSearchMedia(modelCall)
+ else:
+ return AiModelResponse(
+ content="",
+ success=False,
+ error=f"Unsupported operation type: {operationType}"
+ )
+
+ async def webSearchMedia(self, modelCall: AiModelCall) -> "AiModelResponse":
+ """WEB_SEARCH_MEDIA operation - returns list of image URLs using Google Custom Search."""
+ # Parse AiCallPromptWebSearchMedia from messages
+ # Call Google Custom Search API with searchType=image
+ # Return JSON array of image URLs (same format as Tavily for consistency)
+```
+
+**Key Implementation Points**:
+- Use Google Custom Search API with `searchType=image`
+- Return image URLs in JSON array format (consistent with Tavily)
+- Support filters: imageType, size, color, country, language
+- Handle API errors and rate limiting
+
+### 2.4 Update Service AI Handler
+
+**File**: `gateway/modules/services/serviceAi/mainServiceAi.py`
+
+**Update `_handleWebOperations()` method**:
+```python
+async def _handleWebOperations(
+ self,
+ prompt: str,
+ options: AiCallOptions,
+ opType: OperationTypeEnum,
+ aiOperationId: str
+) -> AiResponse:
+ """Handle WEB_SEARCH_DATA, WEB_SEARCH_MEDIA, and WEB_CRAWL operation types."""
+ # Existing logic handles WEB_SEARCH_DATA and WEB_CRAWL
+ # Add support for WEB_SEARCH_MEDIA
+ if opType == OperationTypeEnum.WEB_SEARCH_DATA or opType == OperationTypeEnum.WEB_SEARCH_MEDIA or opType == OperationTypeEnum.WEB_CRAWL:
+ # ... existing implementation ...
+```
+
+### 2.5 Add searchImages Action
+
+**New File**: `gateway/modules/workflows/methods/methodAi/actions/searchImages.py`
+
+**Implementation**:
+```python
+async def searchImages(self, parameters: Dict[str, Any]) -> ActionResult:
+ """Search for images on the web using a prompt and return them as documents."""
+ prompt = parameters.get("prompt")
+ if not prompt:
+ return ActionResult.isFailure(error="Search prompt is required")
+
+ maxResults = parameters.get("maxResults", 5)
+ imageType = parameters.get("imageType")
+ size = parameters.get("size")
+ color = parameters.get("color")
+
+ # Build AiCallPromptWebSearchMedia
+ searchPromptModel = AiCallPromptWebSearchMedia(
+ instruction=prompt,
+ maxResults=maxResults,
+ imageType=imageType,
+ size=size,
+ color=color
+ )
+
+ # Call AI with WEB_SEARCH_MEDIA operation
+ searchOptions = AiCallOptions(
+ operationType=OperationTypeEnum.WEB_SEARCH_MEDIA,
+ resultFormat="json"
+ )
+
+ # System will automatically route to Google connector
+ searchResponse = await self.services.ai.callAiContent(
+ prompt=searchPromptModel.model_dump_json(exclude_none=True, indent=2),
+ options=searchOptions,
+ outputFormat="json"
+ )
+
+ # Parse response to extract image URLs
+ # Download images in parallel
+ # Create ActionDocument for each image
+ # Return ActionResult with list of documents
+```
+
+**Update**: `gateway/modules/workflows/methods/methodAi/methodAi.py`
+
+**Add action definition**:
+```python
+"searchImages": WorkflowActionDefinition(
+ actionId="ai.searchImages",
+ description="Search for images on the web using a prompt and return them as documents",
+ dynamicMode=True,
+ parameters={
+ "prompt": WorkflowActionParameter(...),
+ "maxResults": WorkflowActionParameter(...),
+ "imageType": WorkflowActionParameter(...),
+ "size": WorkflowActionParameter(...)
+ },
+ execute=searchImages.__get__(self, self.__class__)
+)
+```
+
+---
+
+## 3. Implementation Steps
+
+### Phase 1: Add WEB_SEARCH_MEDIA Operation Type (30 min)
+
+1. ✅ Add `WEB_SEARCH_MEDIA = "webSearchMedia"` to `OperationTypeEnum`
+2. ✅ Create `AiCallPromptWebSearchMedia` model
+3. ✅ Update imports/exports
+
+### Phase 2: Create Google Connector (4-6 hours)
+
+1. ✅ Create `aicorePluginGoogle.py` file
+2. ✅ Implement `AiGoogle` connector class
+3. ✅ Implement `webSearchMedia()` method
+4. ✅ Register connector in connector discovery
+5. ✅ Test Google API integration
+6. ✅ Handle errors and rate limiting
+
+### Phase 3: Update Service Handlers (1-2 hours)
+
+1. ✅ Update `serviceAi/mainServiceAi.py` to handle `WEB_SEARCH_MEDIA`
+2. ✅ Ensure routing works correctly
+3. ✅ Test model selection routes to Google connector
+
+### Phase 4: Add searchImages Action (3-4 hours)
+
+1. ✅ Create `actions/searchImages.py`
+2. ✅ Implement image search logic
+3. ✅ Implement parallel image download
+4. ✅ Add action definition to `methodAi.py`
+5. ✅ Add to `actions/__init__.py`
+6. ✅ Write unit tests
+
+### Phase 5: Testing & Integration (2-3 hours)
+
+1. ✅ Test Google connector with real API
+2. ✅ Test searchImages action end-to-end
+3. ✅ Verify dynamic model selection
+4. ✅ Test error handling
+5. ✅ Integration testing
+
+**Total Estimated Time**: 1-2 days
+
+---
+
+## 4. Configuration Requirements
+
+### 4.1 Environment Variables
+
+**Required**:
+- `GOOGLE_SEARCH_API_KEY` - Google Custom Search API key
+- `GOOGLE_SEARCH_ENGINE_ID` - Custom Search Engine ID
+ - Note: Must enable "Image Search" in Google Custom Search Engine settings
+
+### 4.2 Google Custom Search Setup
+
+1. Create Google Custom Search Engine at https://programmablesearchengine.google.com/
+2. Enable "Image Search" in settings
+3. Get API key from Google Cloud Console
+4. Configure environment variables
+
+---
+
+## 5. Files to Create/Modify
+
+### New Files
+- `gateway/modules/aicore/aicorePluginGoogle.py` - Google connector
+- `gateway/modules/workflows/methods/methodAi/actions/searchImages.py` - Image search action
+
+### Modified Files
+- `gateway/modules/datamodels/datamodelAi.py` - Add `WEB_SEARCH_MEDIA` and `AiCallPromptWebSearchMedia`
+- `gateway/modules/services/serviceAi/mainServiceAi.py` - Handle `WEB_SEARCH_MEDIA`
+- `gateway/modules/workflows/methods/methodAi/methodAi.py` - Add `searchImages` action
+- `gateway/modules/workflows/methods/methodAi/actions/__init__.py` - Export `searchImages`
+- Connector discovery module (if exists) - Register Google connector
+
+---
+
+## 6. Testing Requirements
+
+### Unit Tests
+- Google connector `webSearchMedia()` method
+- `searchImages` action with various parameters
+- Error handling (API errors, rate limits, invalid responses)
+- Image download and validation
+
+### Integration Tests
+- End-to-end image search workflow
+- Dynamic model selection routes to Google connector
+- Multiple image downloads in parallel
+- Verify ActionDocuments are created correctly
+
+---
+
+## 7. Risks & Mitigation
+
+| Risk | Impact | Probability | Mitigation |
+|------|--------|-------------|------------|
+| Google API setup complexity | Medium | Medium | Provide clear setup instructions, validate API keys at startup |
+| Dynamic model selection routing | Medium | Low | Thoroughly test operation type routing |
+| API rate limiting (Google) | Low | Medium | Implement retry logic with exponential backoff |
+| Missing connector registration | Medium | Low | Ensure connector is registered in discovery system |
+
+---
+
+## 8. Dependencies
+
+- **Google Custom Search API** - REQUIRED
+- **Google API Client Library** - May need `google-api-python-client` package
+- **HTTP Client** - For image downloads (existing)
+- **Base64 Encoding** - Python standard library (no dependency)
+
+---
+
+## 9. Success Criteria
+
+✅ `WEB_SEARCH_MEDIA` operation type exists
+✅ Google connector is registered and functional
+✅ `searchImages` action works end-to-end
+✅ Dynamic model selection routes `WEB_SEARCH_MEDIA` to Google connector
+✅ Images are downloaded and returned as ActionDocuments
+✅ All tests pass
+
+---
+
+**Document Version**: 2.0
+**Last Updated**: 2026-01-01
+**Status**: Refactoring Concept - Ready for Implementation
diff --git a/c-work/1-plan/2026-03-workflow-editor.md b/c-work/1-plan/2026-03-workflow-editor.md
new file mode 100644
index 0000000..66c0df4
--- /dev/null
+++ b/c-work/1-plan/2026-03-workflow-editor.md
@@ -0,0 +1,1219 @@
+# Graphischer Workflow-Editor Konzept
+
+## Übersicht
+
+Dieses Dokument beschreibt das Konzept für einen graphischen Workflow-Editor, der es ermöglicht, Workflow-Templates visuell zu modellieren. Der Editor wird für die Erstellung und Bearbeitung von Automation-Templates verwendet, die in `formAutomations.js` verwaltet werden.
+
+## Wichtige Terminologie: Workflow vs. WorkflowTemplate
+
+**WICHTIG**: Es gibt eine klare Trennung zwischen ausführbaren Workflows und Templates:
+
+### ChatWorkflow (ausführbares Objekt)
+- **Klasse**: `ChatWorkflow` (in `datamodelChat.py`)
+- **Zweck**: Ausführbare Workflow-Instanz
+- **Eigenschaften**:
+ - Hat `id`, `status` (running/completed/stopped/error)
+ - Enthält `tasks` (Liste von TaskItem-Objekten)
+ - Enthält `messages`, `logs`, `stats`
+ - Hat `workflowMode` (automatic oder dynamic)
+- **Ausführung**:
+ - Kann über Route mit `start` oder `stop` ausgeführt werden
+ - Wird automatisch (scheduled) oder dynamisch (on-demand) gestartet
+- **Lebenszyklus**: Wird zur Laufzeit erstellt und ausgeführt
+
+### AutomationDefinition (Template-Objekt)
+- **Klasse**: `AutomationDefinition` (in `datamodelChat.py`)
+- **Zweck**: Vorlage für ChatWorkflows
+- **Eigenschaften**:
+ - Hat `id`, `label`, `schedule` (Cron-Pattern)
+ - Enthält `template` (JSON-String mit Workflow-Struktur)
+ - Enthält `placeholders` (Dict mit Platzhalter-Werten)
+ - Hat `active` (ob Automation aktiviert ist)
+- **Verwendung**:
+ - Wird im Workflow-Editor bearbeitet
+ - Wird verwendet, um ChatWorkflows zu erstellen
+ - Template wird mit Placeholders gefüllt → ChatWorkflow wird erstellt
+- **Lebenszyklus**: Wird einmal erstellt und mehrfach verwendet
+
+### WorkflowTemplateModel (Editor-Modell)
+- **Klasse**: `WorkflowTemplateModel` (nur für Editor, nicht in Datenbank)
+- **Zweck**: Strukturiertes Modell für graphischen Editor
+- **Verwendung**:
+ - Wird aus `AutomationDefinition.template` (JSON-String) geparst
+ - Wird im Editor bearbeitet
+ - Wird zurück zu `AutomationDefinition.template` konvertiert
+- **Lebenszyklus**: Nur während Editor-Session vorhanden
+
+### Beziehung zwischen Objekten
+
+```
+AutomationDefinition (Template)
+ ↓ (wird verwendet, um zu erstellen)
+ChatWorkflow (ausführbare Instanz)
+ ↓ (wird ausgeführt)
+TaskItem → ActionItem → Ergebnisse
+```
+
+**Beispiel**:
+1. `AutomationDefinition` mit `template: '{"tasks": [...]}'` und `placeholders: {"connectionName": "MyConn"}`
+2. Template wird mit Placeholders gefüllt → `ChatWorkflow` wird erstellt
+3. `ChatWorkflow` wird gestartet → Tasks werden ausgeführt → Actions werden ausgeführt
+
+## Zielsetzung
+
+1. **Visuelle Modellierung**: Workflows mit Tasks und Actions graphisch erstellen
+2. **Parameter-Konfiguration**: Action-Parameter direkt im Editor setzen
+3. **Dependency-Management**: Document-Dependencies zwischen Actions visuell darstellen
+4. **Template-Generierung**: Automatische Generierung von JSON-Templates aus graphischem Modell
+
+## Datenstruktur-Analyse
+
+### Bestehende Datenmodelle
+
+#### ChatWorkflow (datamodelChat.py) - AUSFÜHRBARES OBJEKT
+```python
+class ChatWorkflow(BaseModel):
+ """Ausführbare Workflow-Instanz"""
+ id: str
+ mandateId: str
+ status: str # "running", "completed", "stopped", "error"
+ workflowMode: WorkflowModeEnum # "automatic" oder "dynamic"
+ tasks: list # Liste von TaskItem-Objekten (zur Laufzeit erstellt)
+ messages: List[ChatMessage]
+ logs: List[ChatLog]
+ stats: List[ChatStat]
+ # ... weitere Felder
+```
+
+**WICHTIG**: `ChatWorkflow` ist das **ausführbare Objekt**, das über Route mit `start`/`stop` gesteuert werden kann.
+
+#### TaskItem (datamodelChat.py) - Teil von ChatWorkflow
+```python
+class TaskItem(BaseModel):
+ """Task innerhalb eines ausführbaren ChatWorkflows"""
+ id: str
+ workflowId: str # Foreign Key zu ChatWorkflow
+ userInput: str
+ status: TaskStatus
+ actionList: List[ActionItem] # Liste von Actions
+ dependencies: List[str] # Task IDs, von denen dieser Task abhängt
+ # ... weitere Felder
+```
+
+**WICHTIG**: `TaskItem` existiert nur in ausführbaren `ChatWorkflow`-Instanzen, nicht in Templates.
+
+#### ActionItem (datamodelChat.py) - Teil von TaskItem
+```python
+class ActionItem(BaseModel):
+ """Action innerhalb eines TaskItems"""
+ id: str
+ execMethod: str # z.B. "outlook", "sharepoint", "ai"
+ execAction: str # z.B. "readEmails", "uploadDocument"
+ execParameters: Dict[str, Any] # Action-Parameter (mit konkreten Werten)
+ execResultLabel: Optional[str] # Label für resultierende Documents
+ # ... weitere Felder
+```
+
+**WICHTIG**: `ActionItem` existiert nur in ausführbaren `ChatWorkflow`-Instanzen, nicht in Templates.
+
+#### AutomationDefinition (datamodelChat.py) - TEMPLATE-OBJEKT
+```python
+class AutomationDefinition(BaseModel):
+ """Template/Vorlage für ChatWorkflows"""
+ id: str
+ mandateId: str
+ label: str # User-friendly name
+ template: str # JSON-String mit Workflow-Struktur (enthält Tasks und Actions als Template)
+ placeholders: Dict[str, str] # Platzhalter-Werte (z.B. {"connectionName": "MyConn"})
+ schedule: str # Cron-Schedule für automatische Ausführung
+ active: bool # Ob Automation aktiviert ist
+ eventId: Optional[str] # Event ID für Event-Management
+ executionLogs: List[Dict[str, Any]] # Logs von Workflow-Ausführungen
+ # ... weitere Felder
+```
+
+**WICHTIG**:
+- `AutomationDefinition` ist das **Template-Objekt**, das im Workflow-Editor bearbeitet wird
+- `template` Feld enthält JSON-String mit Workflow-Struktur (Tasks und Actions als Vorlage)
+- `placeholders` enthält Werte für Platzhalter im Template
+- Wird verwendet, um `ChatWorkflow`-Instanzen zu erstellen
+
+### Document Dependencies
+
+Actions können `documentList` Parameter haben, die auf Ergebnisse von anderen Actions verweisen:
+
+**Formate**:
+- `docList:label` - Referenz zu einem Document-Label aus einer vorherigen Action
+- `docList:messageId:label` - Cross-Round Referenz mit Message-ID
+
+**Beispiel**:
+```json
+{
+ "execMethod": "sharepoint",
+ "execAction": "readDocuments",
+ "execParameters": {
+ "connectionReference": "{{connectionName}}",
+ "documentList": ["docList:emails_found"] // Verweist auf execResultLabel "emails_found"
+ }
+}
+```
+
+## Workflow-Editor UI-Konzept
+
+### Layout-Struktur
+
+```
+┌─────────────────────────────────────────────────────────────┐
+│ Workflow Editor - [Template Name] │
+├─────────────────────────────────────────────────────────────┤
+│ [Toolbar] [Save] [Validate] [Preview] [Help] │
+├─────────────────────────────────────────────────────────────┤
+│ ┌──────────────────┐ ┌─────────────────────────────────┐ │
+│ │ Toolbox │ │ Canvas (Graph Editor) │ │
+│ │ │ │ │ │
+│ │ 📋 Tasks │ │ ┌─────────┐ │ │
+│ │ ┌─────────────┐ │ │ │ Task 1 │ │ │
+│ │ │ + Task │ │ │ └────┬───┘ │ │
+│ │ └─────────────┘ │ │ │ │ │
+│ │ │ │ ┌────▼───┐ │ │
+│ │ ⚙️ Actions │ │ │Action 1 │ │ │
+│ │ ┌─────────────┐ │ │ └────┬───┘ │ │
+│ │ │ outlook │ │ │ │ │ │
+│ │ │ sharepoint │ │ │ ┌────▼───┐ │ │
+│ │ │ ai │ │ │ │Action 2│ │ │
+│ │ │ ... │ │ │ └────────┘ │ │
+│ │ └─────────────┘ │ │ │ │
+│ │ │ │ ┌─────────┐ │ │
+│ │ 🔗 Connections │ │ │ Task 2 │ │ │
+│ │ (Drag to link) │ │ └─────────┘ │ │
+│ └──────────────────┘ └─────────────────────────────────┘ │
+├─────────────────────────────────────────────────────────────┤
+│ [Properties Panel] - Selected: Task 1 │
+│ ┌───────────────────────────────────────────────────────┐ │
+│ │ Task Properties: │ │
+│ │ ID: task_1 │ │
+│ │ User Input: {{userPrompt}} │ │
+│ │ Dependencies: [task_0] │ │
+│ │ │ │
+│ │ Actions: │ │
+│ │ [Action 1] [Action 2] [+ Add Action] │ │
+│ └───────────────────────────────────────────────────────┘ │
+└─────────────────────────────────────────────────────────────┘
+```
+
+### Komponenten
+
+#### 1. Toolbox (Links)
+- **Tasks**: Drag & Drop für neue Tasks
+- **Actions**: Gruppiert nach Methoden (outlook, sharepoint, ai, etc.)
+- **Connections**: Visueller Hinweis für Dependency-Verbindungen
+
+#### 2. Canvas (Mitte)
+- **Graph-Editor**: Visualisierung des Workflows
+- **Nodes**: Tasks (große Boxen) und Actions (kleinere Boxen innerhalb von Tasks)
+- **Edges**: Verbindungen zwischen Tasks (Dependencies) und Actions (Document-Flows)
+
+#### 3. Properties Panel (Unten)
+- **Task Properties**: Wenn Task selektiert
+- **Action Properties**: Wenn Action selektiert
+- **Parameter Editor**: Dynamisches Formular basierend auf `WorkflowActionParameter` Definitionen
+
+## Graphische Darstellung
+
+### Task-Node
+```
+┌─────────────────────────────────────┐
+│ 📋 Task 1 │
+│ ───────────────────────────────── │
+│ User Input: {{userPrompt}} │
+│ │
+│ ┌─────────────┐ ┌─────────────┐ │
+│ │ Action 1.1 │ │ Action 1.2 │ │
+│ │ outlook. │ │ sharepoint. │ │
+│ │ readEmails │ │ uploadDoc │ │
+│ └─────────────┘ └─────────────┘ │
+│ │
+│ Dependencies: [Task 0] │
+└─────────────────────────────────────┘
+```
+
+### Action-Node
+```
+┌─────────────────────────┐
+│ ⚙️ outlook.readEmails │
+│ ─────────────────────── │
+│ connectionRef: {{...}} │
+│ query: "unread" │
+│ limit: 50 │
+│ │
+│ Result Label: emails │
+│ ─────────────────────── │
+│ [Edit] [Delete] │
+└─────────────────────────┘
+```
+
+### Dependency-Verbindungen
+
+**Task Dependencies** (gestrichelte Linie):
+```
+Task 0 ──┐
+ │ (depends on)
+ ▼
+ Task 1
+```
+
+**Document Flow** (durchgezogene Linie mit Label):
+```
+Action 1.1 (emails) ──[docList:emails]──► Action 2.1
+```
+
+## Datenmodell für Editor
+
+### WorkflowTemplateModel (neues Datenmodell)
+
+```python
+class WorkflowTemplateModel(BaseModel):
+ """Template-Modell für graphischen Editor"""
+
+ # Metadaten
+ name: str = Field(description="Template name")
+ description: Optional[str] = Field(None, description="Template description")
+ version: str = Field(default="1.0", description="Template version")
+
+ # Graph-Struktur
+ tasks: List[TaskTemplateModel] = Field(
+ default_factory=list,
+ description="List of task templates"
+ )
+
+ # Placeholders (werden aus Template extrahiert)
+ placeholders: Dict[str, str] = Field(
+ default_factory=dict,
+ description="Placeholder definitions with default values"
+ )
+
+ # UI-Metadaten (für Editor)
+ uiMetadata: Optional[Dict[str, Any]] = Field(
+ None,
+ description="UI metadata (node positions, zoom level, etc.)"
+ )
+
+class TaskTemplateModel(BaseModel):
+ """Task-Template für Editor"""
+
+ id: str = Field(description="Task ID (unique within template)")
+ label: str = Field(description="Task label/name")
+ userInput: str = Field(
+ description="User input template (can contain placeholders like {{userPrompt}})"
+ )
+ dependencies: List[str] = Field(
+ default_factory=list,
+ description="List of task IDs this task depends on"
+ )
+ actions: List[ActionTemplateModel] = Field(
+ default_factory=list,
+ description="List of actions in this task"
+ )
+
+ # UI-Metadaten
+ position: Optional[Dict[str, float]] = Field(
+ None,
+ description="Node position in editor: {x: number, y: number}"
+ )
+
+class ActionTemplateModel(BaseModel):
+ """Action-Template für Editor"""
+
+ id: str = Field(description="Action ID (unique within task)")
+ method: str = Field(description="Method name (e.g., 'outlook', 'sharepoint')")
+ action: str = Field(description="Action name (e.g., 'readEmails', 'uploadDocument')")
+ parameters: Dict[str, Any] = Field(
+ default_factory=dict,
+ description="Action parameters (can contain placeholders and document references)"
+ )
+ resultLabel: Optional[str] = Field(
+ None,
+ description="Result label for document output (used in documentList references)"
+ )
+
+ # Document Dependencies (automatisch aus parameters extrahiert)
+ documentDependencies: List[str] = Field(
+ default_factory=list,
+ description="List of result labels this action depends on (from documentList parameter)"
+ )
+
+ # UI-Metadaten
+ position: Optional[Dict[str, float]] = Field(
+ None,
+ description="Node position within task: {x: number, y: number}"
+ )
+```
+
+## Konvertierung: Template ↔ Editor-Modell
+
+### AutomationDefinition.template → Editor-Modell
+
+```python
+def parseTemplateToEditorModel(templateJson: str) -> WorkflowTemplateModel:
+ """
+ Parse AutomationDefinition.template (JSON string) to WorkflowTemplateModel
+
+ INPUT: AutomationDefinition.template (JSON-String)
+ OUTPUT: WorkflowTemplateModel (Editor-Modell)
+
+ Template-Format (aktuell in AutomationDefinition.template):
+ {
+ "tasks": [
+ {
+ "id": "task_1",
+ "userInput": "{{userPrompt}}",
+ "dependencies": [],
+ "actions": [
+ {
+ "method": "outlook",
+ "action": "readEmails",
+ "parameters": {
+ "connectionReference": "{{connectionName}}",
+ "query": "unread",
+ "limit": 50
+ },
+ "resultLabel": "emails"
+ }
+ ]
+ }
+ ]
+ }
+ """
+ templateData = json.loads(templateJson)
+
+ tasks = []
+ for taskData in templateData.get("tasks", []):
+ actions = []
+ for actionData in taskData.get("actions", []):
+ # Extract document dependencies from documentList parameter
+ documentDeps = []
+ if "documentList" in actionData.get("parameters", {}):
+ docList = actionData["parameters"]["documentList"]
+ if isinstance(docList, list):
+ for ref in docList:
+ if isinstance(ref, str) and ref.startswith("docList:"):
+ # Extract label: docList:label or docList:messageId:label
+ parts = ref.split(":")
+ if len(parts) >= 2:
+ label = parts[-1] # Last part is always the label
+ documentDeps.append(label)
+
+ actions.append(ActionTemplateModel(
+ id=actionData.get("id", f"action_{len(actions)}"),
+ method=actionData["method"],
+ action=actionData["action"],
+ parameters=actionData.get("parameters", {}),
+ resultLabel=actionData.get("resultLabel"),
+ documentDependencies=documentDeps
+ ))
+
+ tasks.append(TaskTemplateModel(
+ id=taskData["id"],
+ label=taskData.get("label", taskData["id"]),
+ userInput=taskData.get("userInput", ""),
+ dependencies=taskData.get("dependencies", []),
+ actions=actions
+ ))
+
+ # Extract placeholders from template
+ placeholders = extractPlaceholders(templateJson)
+
+ return WorkflowTemplateModel(
+ name="Template",
+ tasks=tasks,
+ placeholders=placeholders
+ )
+```
+
+### Editor-Modell → AutomationDefinition.template
+
+```python
+def convertEditorModelToTemplate(
+ editorModel: WorkflowTemplateModel,
+ placeholders: Dict[str, str]
+) -> str:
+ """
+ Convert WorkflowTemplateModel to AutomationDefinition.template JSON string
+
+ INPUT: WorkflowTemplateModel (Editor-Modell) + placeholders Dict
+ OUTPUT: JSON-String für AutomationDefinition.template Feld
+ """
+ templateData = {
+ "tasks": []
+ }
+
+ for task in editorModel.tasks:
+ taskData = {
+ "id": task.id,
+ "userInput": task.userInput,
+ "dependencies": task.dependencies,
+ "actions": []
+ }
+
+ for action in task.actions:
+ # Build documentList from documentDependencies
+ parameters = action.parameters.copy()
+ if action.documentDependencies:
+ documentList = [f"docList:{label}" for label in action.documentDependencies]
+ parameters["documentList"] = documentList
+
+ actionData = {
+ "method": action.method,
+ "action": action.action,
+ "parameters": parameters
+ }
+
+ if action.resultLabel:
+ actionData["resultLabel"] = action.resultLabel
+
+ taskData["actions"].append(actionData)
+
+ templateData["tasks"].append(taskData)
+
+ return json.dumps(templateData, indent=2)
+```
+
+## UI-Implementierung
+
+### Technologie-Stack
+
+**Empfehlung**:
+- **Graph-Library**: [Cytoscape.js](https://js.cytoscape.org/) oder [React Flow](https://reactflow.dev/) oder [JointJS](https://www.jointjs.com/)
+- **Framework**: Vanilla JavaScript (konsistent mit bestehendem Frontend) oder React (falls Migration geplant)
+- **Styling**: CSS mit bestehenden Styles aus `formGeneric.js`
+
+### HTML-Struktur
+
+```html
+
+
+
+ Workflow Editor
+
+
+
+
+
+
+
+
+
+
+
+
+ Tasks
+
+ Task
+
+
+
+
+ Actions
+
+ Outlook
+
+ readEmails
+
+
+ sendEmail
+
+
+
+ SharePoint
+
+ readDocuments
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Properties
+
+
+ Select a node to edit properties
+
+
+
+
+
+
+ Placeholders
+
+
+
+
+
+
+
+```
+
+### JavaScript-Architektur
+
+```javascript
+// workflow-editor.js
+
+class WorkflowEditor {
+ constructor(containerId, initialTemplate = null) {
+ this.container = document.getElementById(containerId);
+ this.graph = null; // Graph-Library Instanz
+ this.model = null; // WorkflowTemplateModel
+ this.selectedNode = null;
+
+ this.init();
+ if (initialTemplate) {
+ this.loadTemplate(initialTemplate);
+ }
+ }
+
+ init() {
+ this.initGraph();
+ this.initToolbox();
+ this.initPropertiesPanel();
+ this.initEventHandlers();
+ }
+
+ initGraph() {
+ // Initialize graph library (z.B. Cytoscape.js)
+ this.graph = cytoscape({
+ container: document.getElementById('editor-canvas'),
+ elements: [],
+ style: [
+ {
+ selector: 'node[type="task"]',
+ style: {
+ 'shape': 'roundrectangle',
+ 'width': 200,
+ 'height': 150,
+ 'background-color': '#e8f4f8',
+ 'label': 'data(label)',
+ 'text-valign': 'top',
+ 'text-margin-y': 10
+ }
+ },
+ {
+ selector: 'node[type="action"]',
+ style: {
+ 'shape': 'roundrectangle',
+ 'width': 150,
+ 'height': 80,
+ 'background-color': '#fff4e6',
+ 'label': 'data(label)',
+ 'text-valign': 'center'
+ }
+ },
+ {
+ selector: 'edge[type="task-dependency"]',
+ style: {
+ 'line-style': 'dashed',
+ 'target-arrow-shape': 'triangle',
+ 'curve-style': 'bezier'
+ }
+ },
+ {
+ selector: 'edge[type="document-flow"]',
+ style: {
+ 'line-style': 'solid',
+ 'target-arrow-shape': 'triangle',
+ 'label': 'data(label)',
+ 'curve-style': 'bezier',
+ 'line-color': '#4a90e2'
+ }
+ }
+ ],
+ layout: {
+ name: 'dagre',
+ rankDir: 'TB',
+ spacingFactor: 1.5
+ }
+ });
+
+ // Event handlers
+ this.graph.on('tap', 'node', (evt) => {
+ this.selectNode(evt.target);
+ });
+
+ this.graph.on('tap', (evt) => {
+ if (evt.target === this.graph) {
+ this.deselectNode();
+ }
+ });
+ }
+
+ loadTemplate(templateJson) {
+ // Parse template to editor model
+ this.model = parseTemplateToEditorModel(templateJson);
+
+ // Render graph
+ this.renderGraph();
+
+ // Update placeholders panel
+ this.updatePlaceholdersPanel();
+ }
+
+ renderGraph() {
+ const elements = [];
+
+ // Add task nodes
+ this.model.tasks.forEach((task, taskIndex) => {
+ // Task node
+ elements.push({
+ data: {
+ id: `task_${task.id}`,
+ type: 'task',
+ label: task.label || task.id,
+ taskId: task.id,
+ nodeType: 'task'
+ },
+ position: task.position || { x: 100, y: taskIndex * 200 + 100 }
+ });
+
+ // Action nodes within task
+ task.actions.forEach((action, actionIndex) => {
+ const actionNodeId = `action_${task.id}_${action.id}`;
+ elements.push({
+ data: {
+ id: actionNodeId,
+ type: 'action',
+ label: `${action.method}.${action.action}`,
+ taskId: task.id,
+ actionId: action.id,
+ nodeType: 'action'
+ },
+ position: action.position || {
+ x: 100 + actionIndex * 180,
+ y: taskIndex * 200 + 150
+ }
+ });
+
+ // Parent-child relationship (action belongs to task)
+ elements.push({
+ data: {
+ id: `edge_${task.id}_${action.id}`,
+ source: `task_${task.id}`,
+ target: actionNodeId,
+ type: 'contains'
+ }
+ });
+ });
+ });
+
+ // Add task dependencies
+ this.model.tasks.forEach(task => {
+ task.dependencies.forEach(depId => {
+ elements.push({
+ data: {
+ id: `dep_${depId}_${task.id}`,
+ source: `task_${depId}`,
+ target: `task_${task.id}`,
+ type: 'task-dependency'
+ }
+ });
+ });
+ });
+
+ // Add document flow edges
+ this.model.tasks.forEach(task => {
+ task.actions.forEach(action => {
+ action.documentDependencies.forEach(depLabel => {
+ // Find source action with matching resultLabel
+ const sourceAction = this.findActionByResultLabel(depLabel);
+ if (sourceAction) {
+ elements.push({
+ data: {
+ id: `doc_${sourceAction.id}_${action.id}`,
+ source: `action_${sourceAction.taskId}_${sourceAction.id}`,
+ target: `action_${task.id}_${action.id}`,
+ type: 'document-flow',
+ label: depLabel
+ }
+ });
+ }
+ });
+ });
+ });
+
+ this.graph.elements().remove();
+ this.graph.add(elements);
+ this.graph.layout({ name: 'dagre' }).run();
+ }
+
+ selectNode(node) {
+ this.selectedNode = node;
+ const nodeData = node.data();
+
+ if (nodeData.nodeType === 'task') {
+ this.showTaskProperties(nodeData.taskId);
+ } else if (nodeData.nodeType === 'action') {
+ this.showActionProperties(nodeData.taskId, nodeData.actionId);
+ }
+
+ // Highlight selected node
+ this.graph.elements().removeClass('selected');
+ node.addClass('selected');
+ }
+
+ showActionProperties(taskId, actionId) {
+ const task = this.model.tasks.find(t => t.id === taskId);
+ const action = task?.actions.find(a => a.id === actionId);
+
+ if (!action) return;
+
+ // Load action schema from API
+ this.loadActionSchema(action.method, action.action).then(schema => {
+ const propertiesHtml = this.renderActionPropertiesForm(action, schema);
+ document.getElementById('properties-content').innerHTML = propertiesHtml;
+
+ // Bind form handlers
+ this.bindActionFormHandlers(taskId, actionId, schema);
+ });
+ }
+
+ async loadActionSchema(method, actionName) {
+ // Fetch from /api/workflows/actions/{method}/{actionName}
+ const response = await fetch(`/api/workflows/actions/${method}/${actionName}`);
+ return await response.json();
+ }
+
+ renderActionPropertiesForm(action, schema) {
+ let html = `
+
+ ${action.method}.${action.action}
+
+
+
+ Label for document output (used in documentList references)
+
+
+
+ `;
+
+ // Render parameter fields based on schema
+ Object.entries(schema.parameters || {}).forEach(([paramName, paramDef]) => {
+ html += this.renderParameterField(paramName, paramDef, action.parameters[paramName]);
+ });
+
+ html += `
+
+
+
+
+
+
+ `;
+
+ return html;
+ }
+
+ renderParameterField(paramName, paramDef, currentValue) {
+ const value = currentValue !== undefined ? currentValue : (paramDef.default || '');
+ const valueStr = typeof value === 'object' ? JSON.stringify(value) : String(value);
+
+ let html = ``;
+ html += ``;
+
+ switch (paramDef.frontendType) {
+ case 'text':
+ case 'textarea':
+ html += ``;
+ break;
+ case 'number':
+ html += ``;
+ break;
+ case 'select':
+ case 'userConnection':
+ case 'documentReference':
+ html += ``;
+ break;
+ case 'checkbox':
+ html += ``;
+ break;
+ default:
+ html += ``;
+ }
+
+ html += `${paramDef.description || ''}`;
+ html += ``;
+
+ return html;
+ }
+
+ saveActionProperties(actionId) {
+ const task = this.model.tasks.find(t =>
+ t.actions.some(a => a.id === actionId)
+ );
+ const action = task?.actions.find(a => a.id === actionId);
+
+ if (!action) return;
+
+ // Collect parameter values from form
+ const parameters = {};
+ // ... collect from form fields ...
+
+ // Update action
+ action.parameters = parameters;
+ action.resultLabel = document.getElementById('action-result-label').value;
+
+ // Update document dependencies
+ action.documentDependencies = this.extractDocumentDependencies(parameters);
+
+ // Re-render graph to show updated connections
+ this.renderGraph();
+ }
+
+ extractDocumentDependencies(parameters) {
+ const deps = [];
+ if (parameters.documentList && Array.isArray(parameters.documentList)) {
+ parameters.documentList.forEach(ref => {
+ if (typeof ref === 'string' && ref.startsWith('docList:')) {
+ const parts = ref.split(':');
+ if (parts.length >= 2) {
+ deps.push(parts[parts.length - 1]); // Last part is label
+ }
+ }
+ });
+ }
+ return deps;
+ }
+
+ saveTemplate() {
+ // Convert editor model to template JSON
+ const templateJson = convertEditorModelToTemplate(
+ this.model,
+ this.getPlaceholders()
+ );
+
+ // Save via API to AutomationDefinition (Template-Objekt)
+ // WICHTIG: Dies speichert das Template, nicht das ausführbare ChatWorkflow
+ return this.saveToAutomationDefinition(templateJson);
+ }
+
+ validateTemplate() {
+ const errors = [];
+
+ // Check: All tasks have at least one action
+ this.model.tasks.forEach(task => {
+ if (task.actions.length === 0) {
+ errors.push(`Task "${task.id}" has no actions`);
+ }
+ });
+
+ // Check: All document dependencies resolve to valid result labels
+ this.model.tasks.forEach(task => {
+ task.actions.forEach(action => {
+ action.documentDependencies.forEach(depLabel => {
+ const sourceAction = this.findActionByResultLabel(depLabel);
+ if (!sourceAction) {
+ errors.push(`Action "${action.method}.${action.action}" depends on unknown result label "${depLabel}"`);
+ }
+ });
+ });
+ });
+
+ // Check: Circular dependencies
+ const circularDeps = this.detectCircularDependencies();
+ if (circularDeps.length > 0) {
+ errors.push(`Circular dependencies detected: ${circularDeps.join(', ')}`);
+ }
+
+ // Check: Required parameters are set
+ // ... weitere Validierungen ...
+
+ return {
+ valid: errors.length === 0,
+ errors: errors
+ };
+ }
+
+ findActionByResultLabel(resultLabel) {
+ for (const task of this.model.tasks) {
+ for (const action of task.actions) {
+ if (action.resultLabel === resultLabel) {
+ return { ...action, taskId: task.id };
+ }
+ }
+ }
+ return null;
+ }
+
+ detectCircularDependencies() {
+ // Graph-based cycle detection
+ // ... Implementation ...
+ return [];
+ }
+}
+
+// Initialize editor
+let editor;
+document.addEventListener('DOMContentLoaded', () => {
+ const templateJson = getInitialTemplate(); // From formAutomations.js
+ editor = new WorkflowEditor('workflow-editor', templateJson);
+});
+```
+
+## Integration mit formAutomations.js
+
+### Erweiterte Automation-Form
+
+```javascript
+// In formAutomations.js
+
+// Add "Edit Template" button to automation form
+function initAutomationForm() {
+ // ... existing code ...
+
+ // Add workflow editor button
+ const templateField = form.querySelector('#entity-template');
+ if (templateField) {
+ const editorButton = document.createElement('button');
+ editorButton.type = 'button';
+ editorButton.className = 'btn btn-secondary';
+ editorButton.innerHTML = ' Open Workflow Editor';
+ editorButton.addEventListener('click', () => {
+ openWorkflowEditor(templateField.value);
+ });
+ templateField.parentNode.appendChild(editorButton);
+ }
+}
+
+function openWorkflowEditor(templateJson) {
+ // Open workflow editor in modal or new tab
+ const modal = document.createElement('div');
+ modal.className = 'workflow-editor-modal';
+ modal.innerHTML = `
+
+ `;
+
+ document.body.appendChild(modal);
+
+ // Initialize editor
+ const editor = new WorkflowEditor('workflow-editor-container', templateJson);
+
+ // Save handler
+ document.getElementById('workflow-editor-save').addEventListener('click', () => {
+ const updatedTemplate = editor.saveTemplate();
+ // Update template field in form
+ document.querySelector('#entity-template').value = updatedTemplate;
+ modal.remove();
+ });
+
+ // Cancel handler
+ document.getElementById('workflow-editor-cancel').addEventListener('click', () => {
+ modal.remove();
+ });
+}
+```
+
+## API-Endpunkte
+
+### GET /api/workflows/actions
+Liefert alle verfügbaren Actions (bereits im RBAC-Konzept definiert).
+
+### GET /api/workflows/actions/{method}/{action}
+Liefert Action-Schema mit Parameter-Definitionen:
+
+```json
+{
+ "method": "outlook",
+ "action": "readEmails",
+ "actionId": "outlook.readEmails",
+ "description": "Read emails from Outlook mailbox",
+ "parameters": {
+ "connectionReference": {
+ "name": "connectionReference",
+ "type": "str",
+ "frontendType": "userConnection",
+ "frontendOptions": "user.connection",
+ "required": true,
+ "description": "Microsoft connection label"
+ },
+ "query": {
+ "name": "query",
+ "type": "str",
+ "frontendType": "text",
+ "required": false,
+ "description": "Search query for emails"
+ }
+ }
+}
+```
+
+### GET /api/automations/{automationId}
+Liefert AutomationDefinition für Editor.
+
+**Zweck**: Lädt AutomationDefinition (Template) für Bearbeitung im Editor
+**Rückgabe**: `AutomationDefinition` Objekt mit `template` (JSON-String) und `placeholders`
+
+### POST /api/automations/{automationId}
+Speichert AutomationDefinition (Template).
+
+**Zweck**: Speichert bearbeitetes Template zurück in AutomationDefinition
+**Input**: `AutomationDefinition` Objekt mit aktualisiertem `template` (JSON-String) und `placeholders`
+**Hinweis**: Dies ist das Template-Objekt, nicht das ausführbare ChatWorkflow-Objekt
+
+## Validierung
+
+### Template-Validierung
+
+1. **Struktur-Validierung**:
+ - Alle Tasks haben mindestens eine Action
+ - Alle Task-Dependencies verweisen auf existierende Tasks
+ - Keine zirkulären Dependencies
+
+2. **Action-Validierung**:
+ - Alle Actions haben gültige method/action Kombinationen
+ - Alle required Parameters sind gesetzt
+ - Alle documentList Referenzen verweisen auf existierende resultLabels
+
+3. **Placeholder-Validierung**:
+ - Alle Placeholders im Template sind in placeholders-Dict definiert
+ - Placeholder-Format: `{{PLACEHOLDER_NAME}}`
+
+## Beispiel-Workflow
+
+### Visuelle Darstellung
+
+```
+┌─────────────────────────────────────┐
+│ 📋 Task 1: Read Emails │
+│ ───────────────────────────────── │
+│ User Input: {{userPrompt}} │
+│ │
+│ ┌───────────────────────────────┐ │
+│ │ ⚙️ outlook.readEmails │ │
+│ │ connectionRef: {{conn}} │ │
+│ │ query: "unread" │ │
+│ │ Result: emails │ │
+│ └───────────────┬───────────────┘ │
+└──────────────────┼─────────────────┘
+ │ docList:emails
+ ▼
+┌─────────────────────────────────────┐
+│ 📋 Task 2: Process Documents │
+│ ───────────────────────────────── │
+│ Dependencies: [Task 1] │
+│ │
+│ ┌───────────────────────────────┐ │
+│ │ ⚙️ ai.process │ │
+│ │ documentList: [docList:emails]│ │
+│ │ aiPrompt: {{processPrompt}} │ │
+│ │ Result: processed │ │
+│ └───────────────────────────────┘ │
+└─────────────────────────────────────┘
+```
+
+### Generiertes Template JSON
+
+```json
+{
+ "tasks": [
+ {
+ "id": "task_1",
+ "userInput": "{{userPrompt}}",
+ "dependencies": [],
+ "actions": [
+ {
+ "method": "outlook",
+ "action": "readEmails",
+ "parameters": {
+ "connectionReference": "{{conn}}",
+ "query": "unread",
+ "limit": 50
+ },
+ "resultLabel": "emails"
+ }
+ ]
+ },
+ {
+ "id": "task_2",
+ "userInput": "Process emails",
+ "dependencies": ["task_1"],
+ "actions": [
+ {
+ "method": "ai",
+ "action": "process",
+ "parameters": {
+ "documentList": ["docList:emails"],
+ "aiPrompt": "{{processPrompt}}",
+ "resultType": "json"
+ },
+ "resultLabel": "processed"
+ }
+ ]
+ }
+ ]
+}
+```
+
+## Nächste Schritte
+
+1. **Graph-Library auswählen**: Cytoscape.js vs. React Flow vs. JointJS
+2. **Editor-Komponenten implementieren**: Toolbox, Canvas, Properties Panel
+3. **API-Integration**: Action-Schemas laden, Templates speichern
+4. **Validierung implementieren**: Dependency-Checking, Parameter-Validierung
+5. **Placeholder-Management**: UI für Placeholder-Definition
+6. **Testing**: Unit-Tests für Konvertierungs-Logik
+
+## Offene Fragen
+
+1. **Graph-Library**: Welche Library bevorzugt? (Cytoscape.js ist gut für komplexe Graphen, React Flow ist moderner)
+2. **Positionierung**: Sollen Node-Positionen gespeichert werden oder automatisch layouted?
+3. **Placeholder-UI**: Separate UI für Placeholder-Management oder integriert in Editor?
+4. **Versionierung**: Sollen Templates versioniert werden?
+
diff --git a/c-work/_TEMPLATE.md b/c-work/_TEMPLATE.md
new file mode 100644
index 0000000..1828412
--- /dev/null
+++ b/c-work/_TEMPLATE.md
@@ -0,0 +1,66 @@
+
+
+
+
+#
+
+## Beschreibung und Kontext
+
+Was ist das Thema? Warum jetzt? Was ist der Business-Treiber?
+Welche Abhängigkeiten bestehen? Was ist das Risiko wenn wir es NICHT machen?
+
+## Fokus und kritische Details
+
+- Worauf muss besonders geachtet werden?
+- Welche Stellen im Code sind fragil / komplex?
+- Bekannte Fallstricke oder Edge Cases
+
+## Ziel und Nicht-Ziele
+
+- Ziel: ...
+- Explizit NICHT: ...
+
+## Betroffene Module
+
+- Gateway: ...
+- Frontend: ...
+- DB-Migration: ja/nein
+- Andere Komponenten: ...
+
+## Entscheidungen
+
+| Datum | Entscheidung | Begründung |
+|-------|-------------|------------|
+
+## Umsetzungs-Checkliste
+
+- [ ] API-Endpunkte
+- [ ] DB-Schema / Migration
+- [ ] Frontend-Komponenten
+- [ ] RBAC / Permissions
+- [ ] Neutralisierung betroffen?
+- [ ] Navigation / Routing
+- [ ] Billing-Impact?
+
+## Akzeptanzkriterien
+
+| # | Kriterium (Given-When-Then) | Prio |
+|---|---------------------------|------|
+| 1 | Given ... When ... Then ... | must |
+
+## Testplan
+
+| ID | AC | Art | Automatisiert | Repo-Pfad | Status |
+|----|----|-----|--------------|-----------|--------|
+| T1 | 1 | api | ja | gateway/tests/... | pending |
+
+## Links
+
+- PR: ...
+- Issue: ...
+
+## Abschluss
+
+- [ ] b-reference/ aktualisiert (welche Seite?)
+- [ ] TOPICS.md aktualisiert (falls neues Thema)
+- [ ] Dieses Dokument → z-archive/ verschoben
diff --git a/d-guides/coding-conventions.md b/d-guides/coding-conventions.md
new file mode 100644
index 0000000..2782287
--- /dev/null
+++ b/d-guides/coding-conventions.md
@@ -0,0 +1,20 @@
+
+
+
+# Coding-Konventionen
+
+## Naming
+
+- Alle internen Funktionen beginnen mit `_` Prefix
+- camelCase für Variablen und Funktionsnamen (kein snake_case)
+
+## Frontend-Regeln
+
+- Keine Browser-Dialoge (alert/confirm/prompt) -- stattdessen `useConfirm()` und `usePrompt()` Hooks
+- CSS Modules für Komponenten-Styles
+
+## Backend-Regeln
+
+- Fehler propagieren -- keine stillen Fallbacks bei kritischen Pfaden
+- Pydantic-Models als einzige Quelle für UI-Feld-Definitionen
+- `PowerOnModel` als Basis mit `sysCreatedAt`, `sysCreatedBy`, `sysModifiedAt`, `sysModifiedBy`
diff --git a/deployment/Instanzenübersicht.drawio b/d-guides/deployment/Instanzenübersicht.drawio
similarity index 100%
rename from deployment/Instanzenübersicht.drawio
rename to d-guides/deployment/Instanzenübersicht.drawio
diff --git a/deployment/Instanzenübersicht.svg b/d-guides/deployment/Instanzenübersicht.svg
similarity index 100%
rename from deployment/Instanzenübersicht.svg
rename to d-guides/deployment/Instanzenübersicht.svg
diff --git a/deployment/README.txt b/d-guides/deployment/README.txt
similarity index 100%
rename from deployment/README.txt
rename to d-guides/deployment/README.txt
diff --git a/deployment/poweron_sec.kdbx b/d-guides/deployment/poweron_sec.kdbx
similarity index 100%
rename from deployment/poweron_sec.kdbx
rename to d-guides/deployment/poweron_sec.kdbx
diff --git a/d-guides/dev-setup.md b/d-guides/dev-setup.md
new file mode 100644
index 0000000..139a1c3
--- /dev/null
+++ b/d-guides/dev-setup.md
@@ -0,0 +1,25 @@
+
+
+
+# Dev-Setup
+
+## Voraussetzungen
+
+- Python (Anaconda/Miniconda)
+- Node.js
+- PostgreSQL mit pgvector
+
+## Gateway starten
+
+```bash
+conda activate
+cd gateway/
+uvicorn app:app --host 0.0.0.0 --port 8000
+```
+
+## Frontend Nyla starten
+
+```bash
+cd frontend_nyla/
+npx vite --port 8080 --mode dev
+```
diff --git a/appdoc/doc_admin_encrypt_env_secret.md b/d-guides/encrypt-env-secrets.md
similarity index 100%
rename from appdoc/doc_admin_encrypt_env_secret.md
rename to d-guides/encrypt-env-secrets.md
diff --git a/appdoc/doc_system_google_oauth_setup.md b/d-guides/google-oauth-setup.md
similarity index 100%
rename from appdoc/doc_system_google_oauth_setup.md
rename to d-guides/google-oauth-setup.md
diff --git a/implementation/security-migration-guide.md b/d-guides/security-migration-guide.md
similarity index 100%
rename from implementation/security-migration-guide.md
rename to d-guides/security-migration-guide.md
diff --git a/d-guides/testing-strategy.md b/d-guides/testing-strategy.md
new file mode 100644
index 0000000..db2b3ae
--- /dev/null
+++ b/d-guides/testing-strategy.md
@@ -0,0 +1,26 @@
+
+
+
+# Testing-Strategie
+
+## Testpyramide
+
+- **Unit Tests:** pytest (Gateway), vitest (Frontend)
+- **Integration Tests:** API-Tests gegen laufenden Gateway
+- **E2E Tests:** (zu definieren)
+
+## Akzeptanzkriterien-Format
+
+Given-When-Then Sätze in Arbeits-Dokumenten (`c-work/_TEMPLATE.md`)
+
+## Testplan-Tabelle
+
+Jedes Arbeits-Dokument enthält eine Testplan-Tabelle:
+
+| ID | AC | Art | Automatisiert | Repo-Pfad | Status |
+|----|----|-----|--------------|-----------|--------|
+
+## Test-Pfade im Repo
+
+- Gateway: `gateway/tests/`
+- Frontend: `frontend_nyla/src/**/*.test.ts`
diff --git a/compliance/2026-03-11-ai-skills-timeline-poweron-vs-claude.pdf b/e-compliance/2026-03-11-ai-skills-timeline-poweron-vs-claude.pdf
similarity index 100%
rename from compliance/2026-03-11-ai-skills-timeline-poweron-vs-claude.pdf
rename to e-compliance/2026-03-11-ai-skills-timeline-poweron-vs-claude.pdf
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diff --git a/z-archive/db-structure-model-comparison.md b/z-archive/db-structure-model-comparison.md
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+# Detaillierte Analyse: Datenbankstruktur vs. Pydantic-Modelle
+
+**Export-Datum:** 2026-01-19T20:12:28.176720Z
+**Export-Quelle:** Production Instance
+
+## Zusammenfassung
+
+Von 19 Tabellen haben alle ein entsprechendes Pydantic-Modell, aber es wurden Unterschiede gefunden. Die meisten Unterschiede sind erwartbar (z.B. ID-Felder mit `default_factory` sind im Modell optional, aber in der DB NOT NULL), aber es gibt einige wichtige Inkonsistenzen, die behoben werden sollten.
+
+---
+
+## Kritische Unterschiede (müssen behoben werden)
+
+### 1. **UserInDB** (`datamodelUam.py`)
+
+#### Felder nur in DB (fehlen im Modell):
+- **`privilege`** (text, nullable)
+ - **Problem:** Feld existiert in der Datenbank, aber nicht im Pydantic-Modell
+ - **Empfehlung:** Entweder Feld zum Modell hinzufügen oder aus der DB entfernen
+
+#### Typ-Mismatches:
+
+1. **`roleLabels`**
+ - **DB:** `jsonb` (dict) - nullable
+ - **Modell:** `List[str]` - optional
+ - **Problem:** Datenbank speichert JSONB (wird als dict interpretiert), Modell erwartet Liste von Strings
+ - **Empfehlung:** Prüfen, wie die Daten tatsächlich gespeichert werden. Wenn es eine Liste ist, sollte der Typ in der DB korrekt sein. Wenn es ein dict ist, sollte das Modell angepasst werden.
+
+2. **`resetTokenExpires`**
+ - **DB:** `text` - nullable
+ - **Modell:** `float` (UTC timestamp in seconds) - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Float (Unix-Timestamp)
+ - **Empfehlung:** DB-Typ sollte `double precision` (float8) sein, nicht `text`
+
+---
+
+### 2. **ChatLog** (`datamodelChat.py`)
+
+#### Felder nur im Modell (fehlen in DB):
+- **`actionNumber`** (Optional[int])
+- **`roundNumber`** (Optional[int])
+- **`taskNumber`** (Optional[int])
+- **Problem:** Diese Felder sind im Modell definiert, aber nicht in der Datenbank vorhanden
+- **Empfehlung:** Entweder Migration erstellen, um diese Spalten hinzuzufügen, oder aus dem Modell entfernen
+
+#### Typ-Mismatches:
+
+1. **`progress`**
+ - **DB:** `text` - nullable
+ - **Modell:** `float` (0.0 to 1.0) - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Float
+ - **Empfehlung:** DB-Typ sollte `double precision` (float8) sein
+
+2. **`performance`**
+ - **DB:** `text` - nullable
+ - **Modell:** `Dict[str, Any]` - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Dictionary (JSON)
+ - **Empfehlung:** DB-Typ sollte `jsonb` sein
+
+---
+
+### 3. **Token** (`datamodelSecurity.py`)
+
+#### Typ-Mismatches:
+
+1. **`userId`**
+ - **DB:** `text` - nullable
+ - **Modell:** `str` - required (nicht optional)
+ - **Problem:** Datenbank erlaubt NULL, Modell erwartet zwingend einen Wert
+ - **Empfehlung:** DB sollte `NOT NULL` sein, da es ein required Feld ist
+
+2. **`authority`**
+ - **DB:** `text` - nullable
+ - **Modell:** `AuthAuthority` (Enum) - required
+ - **Problem:** Datenbank erlaubt NULL, Modell erwartet zwingend einen Wert
+ - **Empfehlung:** DB sollte `NOT NULL` sein
+
+3. **`tokenAccess`**
+ - **DB:** `text` - nullable
+ - **Modell:** `str` - required
+ - **Problem:** Datenbank erlaubt NULL, Modell erwartet zwingend einen Wert
+ - **Empfehlung:** DB sollte `NOT NULL` sein
+
+4. **`createdAt`**
+ - **DB:** `text` - nullable
+ - **Modell:** `float` (UTC timestamp) - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Float
+ - **Empfehlung:** DB-Typ sollte `double precision` (float8) sein
+
+5. **`revokedAt`**
+ - **DB:** `text` - nullable
+ - **Modell:** `float` (UTC timestamp) - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Float
+ - **Empfehlung:** DB-Typ sollte `double precision` (float8) sein
+
+---
+
+### 4. **UserConnection** (`datamodelUam.py`)
+
+#### Typ-Mismatches:
+
+1. **`expiresAt`**
+ - **DB:** `text` - nullable
+ - **Modell:** `float` (UTC timestamp) - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Float
+ - **Empfehlung:** DB-Typ sollte `double precision` (float8) sein
+
+2. **`tokenExpiresAt`**
+ - **DB:** `text` - nullable
+ - **Modell:** `float` (UTC timestamp) - optional
+ - **Problem:** Datenbank speichert als Text, Modell erwartet Float
+ - **Empfehlung:** DB-Typ sollte `double precision` (float8) sein
+
+---
+
+### 5. **ChatWorkflow** (`datamodelChat.py`)
+
+#### Typ-Mismatches (JSONB vs. List):
+
+Mehrere Felder haben das Problem, dass die DB `jsonb` (als dict interpretiert) speichert, aber das Modell `List[...]` erwartet:
+
+- **`logs`**: DB=`jsonb` (dict), Modell=`List[ChatLog]`
+- **`messages`**: DB=`jsonb` (dict), Modell=`List[ChatMessage]`
+- **`stats`**: DB=`jsonb` (dict), Modell=`List[ChatStat]`
+- **`tasks`**: DB=`jsonb` (dict), Modell=`List[...]`
+- **`expectedFormats`**: DB=`text`, Modell=`List[...]`
+
+**Problem:** JSONB-Felder werden als Dictionary interpretiert, aber das Modell erwartet Listen. Dies deutet darauf hin, dass die Daten möglicherweise als Arrays im JSONB gespeichert werden sollten, oder dass die Serialisierung/Deserialisierung angepasst werden muss.
+
+**Empfehlung:** Prüfen, wie diese Daten tatsächlich gespeichert und geladen werden. Möglicherweise benötigt die Anwendung eine Custom Serialisierung für JSONB-Arrays.
+
+---
+
+## Erwartbare Unterschiede (keine Aktion erforderlich)
+
+### ID-Felder mit `default_factory`
+
+Viele Tabellen haben ID-Felder, die im Modell als `optional=True` markiert sind (wegen `default_factory=lambda: str(uuid.uuid4())`), aber in der DB als `NOT NULL` definiert sind. Dies ist **erwartbar und korrekt**, da:
+- Pydantic-Felder mit `default_factory` sind technisch optional (können beim Erstellen weggelassen werden)
+- Die Datenbank erwartet jedoch immer einen Wert (NOT NULL)
+
+**Betroffene Tabellen:** AccessRule, AuthEvent, DataNeutraliserConfig, DataNeutralizerAttributes, Mandate, Role, ChatDocument, FileData, FileItem, Prompt
+
+---
+
+## Weitere Typ-Mismatches (möglicherweise erwartbar)
+
+### Role.description
+- **DB:** `jsonb` (dict) - nullable
+- **Modell:** `str` - optional
+- **Hinweis:** Möglicherweise wird hier ein mehrsprachiges Dictionary gespeichert, während das Modell einen String erwartet. Prüfen, ob eine Custom Serialisierung verwendet wird.
+
+### ActionItem.expectedDocumentFormats
+- **DB:** `jsonb` (dict) - nullable
+- **Modell:** `List[...]` - optional
+- **Hinweis:** Ähnlich wie bei ChatWorkflow - JSONB vs. List
+
+### AutomationDefinition.executionLogs
+- **DB:** `jsonb` (dict) - nullable
+- **Modell:** `List[...]` - optional
+- **Hinweis:** Ähnlich wie bei ChatWorkflow - JSONB vs. List
+
+### ChatMessage.documents
+- **DB:** `jsonb` (dict) - nullable
+- **Modell:** `List[...]` - optional
+- **Hinweis:** Ähnlich wie bei ChatWorkflow - JSONB vs. List
+
+---
+
+## Empfohlene Maßnahmen
+
+### Priorität 1 (Kritisch - Datenintegrität):
+1. **UserInDB.privilege**: Feld hinzufügen oder entfernen
+2. **ChatLog**: `actionNumber`, `roundNumber`, `taskNumber` hinzufügen oder aus Modell entfernen
+3. **Token**: Required-Felder (`userId`, `authority`, `tokenAccess`) sollten `NOT NULL` in DB sein
+4. **Timestamp-Felder**: Alle Timestamp-Felder sollten `double precision` sein, nicht `text`
+
+### Priorität 2 (Wichtig - Typ-Konsistenz):
+1. **JSONB vs. List**: Prüfen und korrigieren der Serialisierung für alle JSONB-Felder, die Listen enthalten sollen
+2. **UserInDB.roleLabels**: Prüfen, ob es wirklich eine Liste oder ein Dictionary ist
+
+### Priorität 3 (Optional - Code-Qualität):
+1. **ID-Felder**: Optional können die Modelle angepasst werden, um explizit `NOT NULL` zu reflektieren (aber nicht notwendig)
+
+---
+
+## Technische Details
+
+### Typ-Mapping-Probleme
+
+Das Vergleichstool mappt PostgreSQL-Typen wie folgt:
+- `character varying` / `varchar` / `text` → `str`
+- `boolean` / `bool` → `bool`
+- `integer` / `int` / `bigint` → `int`
+- `double precision` / `float8` → `float`
+- `jsonb` / `json` → `dict`
+
+**Problem:** JSONB kann sowohl Dictionaries als auch Arrays enthalten. Das Tool interpretiert JSONB immer als `dict`, auch wenn es tatsächlich ein Array ist. Dies führt zu falschen Mismatch-Meldungen bei Listen-Feldern.
+
+**Lösung:** Für eine genauere Analyse müsste das Tool die tatsächlichen JSONB-Werte prüfen oder die Datenbank-Schema-Definitionen genauer analysieren.
diff --git a/z-archive/feat-file-tree-release-notes.md b/z-archive/feat-file-tree-release-notes.md
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+# Feature Branch Notes - `feat/file-tree-system`
+
+Date: 2026-03-17
+Repos: `gateway`, `frontend_nyla`
+
+## Release Notes (Kurzfassung)
+
+- Filesystem-Funktionen wurden deutlich erweitert: Batch-Delete und Batch-Move fuer Files/Folders laufen effizient ueber Backend-Endpunkte und DB-Operationen.
+- Folder/File-Tree-Verhalten wurde zwischen `Dateien` und `AI Workspace` vereinheitlicht, inklusive Multi-Select und Drag&Drop-Workflows.
+- `Dateien`-Ansicht ist wieder strikt backend-getrieben fuer Sortierung, Filter und Pagination (kein Client-Side-Fallback mehr).
+- Chat-UX wurde gestrafft: kompaktere CHATS-Liste und optimierter Umgang mit Prompt-Inhalten.
+- Langer Paste-Text im Workspace-Input wird als Datei behandelt statt den Prompt zu ueberfrachten.
+- Agent-/Workspace-Dokumentfluss wurde stabilisiert (sauberere Ablage und Metadatenkette im Backend-Kontext).
+- Mehrere Stabilitaets- und Integrationsanpassungen in Voice/Commcoach/Billing-nahen Bereichen runden das Branch-Inkrement ab.
+
+---
+
+## PR Text - `gateway`
+
+### Title
+`feat: file system + agent/voice revisions (batch ops, workspace docs, stt/tts)`
+
+### Body
+```md
+## Summary
+
+This PR consolidates backend changes for file system handling, workspace-agent document persistence, and voice/service revisions.
+
+- adds/updates file-system APIs for efficient folder/file operations (including batch-oriented endpoints/DB handling)
+- improves workspace agent file persistence flow so downloaded/generated artifacts are stored with proper metadata and structured placement
+- extends/adjusts route and interface layers for file, voice, billing, and service-center integrations
+- includes commcoach/service-agent updates to stabilize chat/voice-related backend behavior
+
+## Main areas touched
+
+- File management:
+ - `modules/routes/routeDataFiles.py`
+ - `modules/interfaces/interfaceDbManagement.py`
+ - `modules/datamodels/datamodelFiles.py`
+- Agent/service runtime:
+ - `modules/serviceCenter/services/serviceAgent/mainServiceAgent.py`
+ - `modules/serviceCenter/services/serviceAgent/sandboxExecutor.py`
+ - `modules/serviceCenter/services/serviceChat/mainServiceChat.py`
+- Voice/Commcoach:
+ - `modules/routes/routeVoiceGoogle.py`
+ - `modules/connectors/connectorVoiceGoogle.py`
+ - `modules/interfaces/interfaceVoiceObjects.py`
+ - `modules/features/commcoach/*`
+- Billing/other integrations:
+ - `modules/routes/routeBilling.py`
+ - `modules/interfaces/interfaceDbBilling.py`
+ - `modules/serviceCenter/services/serviceBilling/stripeCheckout.py`
+
+## Test plan
+
+- [ ] verify batch delete/move endpoints (`/api/files/batch-delete`, `/api/files/batch-move`) with mixed file/folder payloads
+- [ ] verify folder recursive delete behavior and conflict/circular checks on folder moves
+- [ ] verify agent-generated/downloaded documents are stored with correct filename/extension and expected metadata
+- [ ] run relevant backend smoke tests for workspace chat + commcoach voice flows
+- [ ] regression-check billing route changes
+```
+
+---
+
+## PR Text - `frontend_nyla`
+
+### Title
+`feat: unified folder/file tree + workspace/files UX and backend-driven table behavior`
+
+### Body
+```md
+## Summary
+
+This PR delivers the frontend part of the file-tree/workspace enhancement with consistent state handling and backend-driven table interactions.
+
+- unifies folder/file tree behavior across Files page and AI Workspace
+- improves tree interactions (multi-select, drag/drop, action handling, visual behavior)
+- adds batch-aware file/folder operations via new API usage
+- updates workspace prompt behavior (long paste as file attachment)
+- compacts CHATS list presentation and adjusts metadata layout
+- keeps table sort/filter/pagination aligned with backend refetch mechanism
+
+## Main areas touched
+
+- Tree + file context:
+ - `src/components/FolderTree/FolderTree.tsx`
+ - `src/components/FolderTree/FolderTree.module.css`
+ - `src/contexts/FileContext.tsx`
+ - `src/api/fileApi.ts`
+- Files page/table integration:
+ - `src/pages/basedata/FilesPage.tsx`
+ - `src/components/FormGenerator/FormGeneratorTable/FormGeneratorTable.tsx`
+ - `src/hooks/useFiles.ts`
+- Workspace UX:
+ - `src/pages/views/workspace/FileBrowser.tsx`
+ - `src/pages/views/workspace/WorkspaceInput.tsx`
+ - `src/pages/views/workspace/WorkspacePage.tsx`
+ - `src/pages/views/workspace/ConversationList.tsx`
+- Additional related adjustments:
+ - `src/hooks/useCommcoach.ts`
+ - `src/hooks/useSpeechAudioCapture.ts`
+ - `src/hooks/useTtsPlayback.ts`
+ - `src/api/billingApi.ts`
+ - `src/pages/billing/BillingDataView.tsx`
+ - `src/pages/views/commcoach/*`
+
+## Test plan
+
+- [ ] Files page: select folder in tree -> table shows correct folder scope
+- [ ] Files page: sorting/filtering/pagination trigger backend refetch correctly
+- [ ] Tree: multi-select with CTRL/SHIFT, drag selected items, delete files/folders via separate batch actions
+- [ ] Workspace: drag file/folder refs into prompt and validate attachment behavior
+- [ ] Workspace input: paste long text (>=1000 chars) creates file attachment instead of inline prompt text
+- [ ] CHATS list: no redundant second status line; last activity shown on left
+- [ ] run production build (`npm run build`) and smoke-test key views
+```
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