- Implement relational data structure in Notion as per the plan.
- Add scripts for initial data import (import_product.py) and distribution to related databases (distribute_product_data.py).
- Create helper scripts for reading Notion content.
- Update Notion_Dashboard.md and GEMINI.md with the latest implementation status, database IDs, and key lessons learned from the MVP phase, including API constraints and schema-first principles.
- Added logic to automatically flatten list-wrapped JSON responses from LLM in Impressum extraction.
- Fixed 'Unknown Legal Name' issue by ensuring property access on objects, not lists.
- Finalized v0.3.0 features and updated documentation with Lessons Learned.
- Increased logging verbosity in to track raw input to LLM and raw LLM response.
- This helps diagnose why Impressum data extraction might be failing for specific company websites.
- Enforced fresh scrape on 'Analyze' request to bypass stale cache.
- Implemented 2-Hop Impressum scraping strategy (via Kontakt page).
- Refined numeric extraction for German locale (thousands separators).
- Updated documentation with Lessons Learned.
- Updated version to v0.3.0 (UI & Backend) to clear potential caching confusion.
- Enhanced Impressum scraper to extract VAT ID (Umsatzsteuer-ID).
- Implemented 2-Hop scraping strategy: Looks for 'Kontakt' page if Impressum isn't on the start page.
- Added VAT ID display to the Legal Data block in Inspector.
- 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.
