Überarbeite den Prompt für die Generierung der Atomic Opener.
Die Opener werden nun auf genau zwei Sätze begrenzt, um Prägnanz zu gewährleisten.
Der Ton ist faktenbasierter und leitet direkter zu den operativen Herausforderungen über,
anstatt generische Lobhudelei zu verwenden.
✦ 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.
1. E2E-Test erfolgreich: Das neue Test-Skript (test_e2e_full_flow.py) hat den kompletten Prozess automatisiert verifiziert:
* Provisionierung: Anlage eines Test-Unternehmens ("Klinikum Landkreis Erding (E2E Test)") über die API.
* Discovery & Analyse: Das System hat die Website gefunden, gescrapt und die Branche ("Healthcare - Hospital") korrekt
klassifiziert.
* Fehlerbehebung (Crash-Fix): Während des Tests wurde ein kritischer AttributeError im Backend identifiziert (Absturz bei
fehlenden Einheiten) und von mir behoben. Seitdem läuft die Analyse ohne Unterbrechung durch.
* Opener-Generierung: Es wurden erfolgreich zwei hoch-personalisierte Einleitungssätze (Primary & Secondary Opener) generiert.
* SuperOffice-Payload: Der finale Abgleich lieferte die korrekte Rolle ("Wirtschaftlicher Entscheider") für den
"Geschäftsführer" zurück.
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.
- Restored missing method implementations in ClassificationService (classify, extract_metrics)
- Fixed Standardization Logic not being applied in metric cascade
- Bumped version to v0.7.4 in config.py
- Removed duplicate API endpoint in app.py
- Updated MIGRATION_PLAN.md
- **Standardization & Formula Logic:** Fixed NameError/SyntaxError in formula parser; added support for comments and capitalized placeholders.
- **Source URL Tracking:** Extended DB schema and cascade logic to store and track specific source URLs.
- **Frontend & UI:**
- Added 'Standardized Potential' display in Inspector.
- Added clickable source link with icon.
- Fixed Settings tab layout collapse (flex-shrink-0).
- **Export Capabilities:**
- Single-company JSON export now includes full quantitative metadata.
- New global CSV export endpoint /api/companies/export.
- **System Integrity:**
- Fixed Notion sync typo ('Stanardization').
- Corrected Nginx proxy routing and FastAPI route ordering.
- Ensured DB persistence via explicit docker-compose volume mapping.
- Implemented a "Re-evaluate Wikipedia" button in the UI.
- Added a backend endpoint to trigger targeted Wikipedia metric extraction.
- Hardened the LLM metric extraction prompt to prevent hallucinations.
- Corrected several database path errors that caused data loss.
- Updated application version to 0.6.4 and documented the ongoing issue.
- Implemented Impressum scraping with Root-URL fallback and enhanced keyword detection.
- Added 'clean_json_response' helper to strip Markdown from LLM outputs, preventing JSONDecodeErrors.
- Improved numeric extraction for German formatting (thousands separators vs decimals).
- Updated Inspector UI with Polling logic for auto-refresh and display of AI Dossier and Legal Data.
- Added Manual Override for Website URL.
- Ported robust Wikipedia extraction logic (categories, first paragraph) from legacy system.
- Implemented database-driven Robotics Category configuration with frontend settings UI.
- Updated Robotics Potential analysis to use Chain-of-Thought infrastructure reasoning.
- Added Manual Override features for Wikipedia URL (with locking) and Website URL (with re-scrape trigger).
- Enhanced Inspector UI with Wikipedia profile, category tags, and action buttons.
This commit introduces the foundational elements for the new "Company Explorer" web application, marking a significant step away from the legacy Google Sheets / CLI system.
Key changes include:
- Project Structure: A new directory with separate (FastAPI) and (React/Vite) components.
- Data Persistence: Migration from Google Sheets to a local SQLite database () using SQLAlchemy.
- Core Utilities: Extraction and cleanup of essential helper functions (LLM wrappers, text utilities) into .
- Backend Services: , , for AI-powered analysis, and logic.
- Frontend UI: Basic React application with company table, import wizard, and dynamic inspector sidebar.
- Docker Integration: Updated and for multi-stage builds and sideloading.
- Deployment & Access: Integrated into central Nginx proxy and dashboard, accessible via .
Lessons Learned & Fixed during development:
- Frontend Asset Loading: Addressed issues with Vite's path and FastAPI's .
- TypeScript Configuration: Added and .
- Database Schema Evolution: Solved errors by forcing a new database file and correcting override.
- Logging: Implemented robust file-based logging ().
This new foundation provides a powerful and maintainable platform for future B2B robotics lead generation.
