This commit introduces a new unsubscribe feature to allow contacts to opt-out
from marketing automation.
Key changes include:
- Database schema migration: Added (UUID) to the model.
- Data population: Implemented a script to assign unique tokens to existing contacts.
- API endpoint: Created a public GET endpoint to handle opt-out requests.
- Automation: New contacts automatically receive an unsubscribe token upon creation.
- Integration: The full unsubscribe link is now returned via the provisioning API
for storage in SuperOffice UDFs (ProgID: SuperOffice:9).
- Documentation: Updated and
to reflect the new feature and its integration requirements.
- Added for quick overview and next steps.
✦ In dieser Sitzung haben wir den End-to-End-Test der SuperOffice-Schnittstelle erfolgreich von der automatisierten Simulation bis zum produktiven Live-Lauf
mit Echtdaten abgeschlossen.
- Implemented comprehensive E2E test covering full roundtrip and manual overrides.
- Enhanced to detect manual Vertical changes in SuperOffice and sync them to Company Explorer.
- Updated to handle industry overrides from CRM and auto-persist Person/Contact data for robust cascade updates.
Completed the full GTM Engine implementation:\n\n- Implemented 'Dual Opener' (Primary/Secondary) generation in ClassificationService and DB.\n- Updated Frontend Inspector to display both openers.\n- Hardened analysis process (fixed duplicate scrapes, improved metric prompt).\n- Created robust, API-level E2E test script (test_opener_api.py).\n- Created a standalone health_check.py for diagnostics.\n- Updated all relevant documentation (README, GEMINI.md).
Completed the GTM engine setup:\n\n- Implemented 'Dual Opener' generation (Primary/Secondary) in ClassificationService.\n- Migrated DB to support two opener fields.\n- Updated API and Frontend to handle and display both openers.\n- Fixed bug creating duplicate website_scrape entries.\n- Hardened metric extraction by improving the LLM prompt and adding content length checks.
Updated all Notion Verticals with sharpened Pains/Gains based on internal strategy (Ops vs Infra focus). Updated SuperOffice Connector README to reflect the 'Static Magic' architecture.
This commit restores the full functionality of the script within the module. Several instances were resolved by implementing missing methods in (e.g., , , , , , , ) and correcting argument passing.
The data extraction logic in was adjusted to correctly parse the structure returned by the SuperOffice API (e.g., and ).
A dedicated SuperOffice API health check script () was introduced to quickly verify basic API connectivity (reading contacts and persons). This script confirmed that read operations for and entities are functional, while the endpoint continues to return a , which is now handled gracefully as a warning, allowing other tests to proceed.
The now successfully executes all SuperOffice-specific POC steps, including creating contacts, persons, sales, projects, and updating UDFs.
- Integrated centralized logging system in all modules.
- Extracted all IDs and ProgIds into a separate .
- Refactored and for cleaner dependency management.
- Included updated discovery and inspection utilities.
- Verified end-to-end workflow stability.
- **Company Explorer Sync**: Added `explorer_client.py` and integrated Step 9 in `main.py` for automated data transfer to the intelligence engine.
- **Holiday Logic**: Implemented `BusinessCalendar` in `utils.py` using the `holidays` library to automatically detect weekends and Bavarian holidays, ensuring professional timing for automated outreaches.
- **API Discovery**: Created `parse_ce_openapi.py` to facilitate technical field mapping through live OpenAPI analysis.
- **Project Stability**: Refined error handling and logging for a smooth end-to-end workflow.
1. Umfassende Entitäten-Erstellung: Wir haben erfolgreich Methoden implementiert, um die Kern-SuperOffice-Entitäten per API zu erstellen:
* Firmen (`Contact`)
* Personen (`Person`)
* Verkäufe (`Sale`) (entspricht D365 Opportunity)
* Projekte (`Project`) (entspricht D365 Campaign), inklusive der Verknüpfung von Personen als Projektmitglieder.
2. Robuste UDF-Aktualisierung: Wir haben eine generische und fehlertolerante Methode (update_entity_udfs) implementiert, die benutzerdefinierte Felder (UDFs) für sowohl Contact- als
auch Person-Entitäten aktualisieren kann. Diese Methode ruft zuerst das bestehende Objekt ab, um die Konsistenz zu gewährleisten.
3. UDF-ID-Discovery: Durch eine iterative Inspektionsmethode haben wir erfolgreich alle internen SuperOffice-IDs für die Listenwerte deines MA Status-Feldes (Ready_to_Send, Sent_Week1,
Sent_Week2, Bounced, Soft_Denied, Interested, Out_of_Office, Unsubscribed) ermittelt und im Connector hinterlegt.
4. Vollständiger End-to-End Test-Workflow: Unser main.py-Skript demonstriert nun einen kompletten Ablauf, der alle diese Schritte von der Erstellung bis zur UDF-Aktualisierung umfasst.
5. Architekturplan für Marketing Automation: Wir haben einen detaillierten "Butler-Service"-Architekturplan für die Marketing-Automatisierung entworfen, der den Connector für die
Textgenerierung und SuperOffice für den Versand und das Status-Management nutzt.
6. Identifikation des E-Mail-Blockers: Wir haben festgestellt, dass das Erstellen von E-Mail-Aktivitäten per API in deiner aktuellen SuperOffice-Entwicklungsumgebung aufgrund fehlender
Lizenzierung/Konfiguration des E-Mail-Moduls blockiert ist (500 Internal Server Error).
This commit extends the SuperOffice connector to support the creation and linking of Sale \(Opportunity\) and Project \(Campaign\) entities, providing a comprehensive foundation for both sales and marketing automation workflows.
Key achievements:
- **`SUPEROFFICE_INTEGRATION_PLAN.md`**: Updated to include strategic mapping of D365 concepts \(Opportunity, Campaign\) to SuperOffice entities \(Sale, Project\).
- **`connector-superoffice/superoffice_client.py`**:
- Implemented `create_sale` method to generate new opportunities, correctly mapping `Title` to SuperOffices
1. Analyse der Änderungen:
* superoffice_client.py: Implementierung der Methoden create_contact (Standardfelder) und create_person (inkl. Firmenverknüpfung).
* auth_handler.py: Härtung der Authentifizierung durch Priorisierung von SO_CLIENT_ID und Unterstützung für load_dotenv(override=True).
* main.py: Erweiterung des Test-Workflows für den vollständigen Lese- und Schreib-Durchstich (Erstellung von Demo-Firmen und Personen).
* README.md: Aktualisierung des Status Quo und der verfügbaren Client-Methoden.
