Refactors the GTM orchestrator prompts (phases 2-9) to use a question-based strategic framework derived from the internal marketing blueprint. This new 'Meta-Framework' approach ensures strategic depth and prevents content pollution from irrelevant examples when analyzing new product categories.
- Updates orchestrator prompts in .
- Adds documentation in explaining how to modify the new strategy logic.
- Includes minor fixes to the Node.js and dependency updates in .
- Implemented semantic classification for Products (e.g. 'Cleaning', 'Logistics') and Battlecards (e.g. 'Price', 'Support').
- Created 'import_competitive_radar.py' for full 4-database relational import to Notion.
- Updated Orchestrator with new prompts for structured output.
- Cleaned up obsolete scripts.
- Extended import_relational_radar.py to include a 'Products' database.
- Implemented full dual-way relations for Companies <-> Landmines, References, Products.
- Updated documentation to reflect the 4-database architecture.
- Added import_relational_radar.py for bidirectional database structure in Notion.
- Added refresh_references.py to populate analysis data with grounded facts via scraping.
- Updated documentation for Competitive Radar v2.0.
Improves the competitor reference analysis (Step 8) by replacing the previous LLM-only approach with a grounded, scraping-based method.
- Implemented a new scraper to actively search for and parse competitor reference/case study pages.
- The analysis is now based on actual website content, significantly increasing the accuracy and reliability of the results and preventing model hallucinations.
- Updated documentation to reflect the new 'Grounded References' architecture.
Resolved multiple issues preventing the 'competitor-analysis' app from running and serving its frontend:
1. **Fixed Python SyntaxError in Prompts:** Corrected unterminated string literals and ensure proper multi-line string formatting (using .format() instead of f-strings for complex prompts) in .
2. **Addressed Python SDK Compatibility (google-generativeai==0.3.0):**
* Removed for and by adapting the orchestrator to pass JSON schemas as direct Python dictionaries, as required by the older SDK version.
* Updated with detailed guidance on handling / imports and dictionary-based schema definitions for older SDKs.
3. **Corrected Frontend Build Dependencies:** Moved critical build dependencies (like , , ) from to in .
* Updated to include this pitfall, ensuring frontend build tools are installed in Docker.
4. **Updated Documentation:**
* : Added comprehensive lessons learned regarding dependencies, Python SDK versioning (specifically and imports for ), and robust multi-line prompt handling.
* : Integrated specific details of the encountered errors and their solutions, making the migration report a more complete historical record and guide.
These changes collectively fix the 404 error by ensuring the Python backend starts correctly and serves the frontend assets after a successful build.
- Fixed TypeError in SessionBrowser by adding defensive checks for the sessions array.
- Implemented mandatory URL persistence: The research URL is now saved in DB, shown in UI, and included in reports.
- Added 'Start New Analysis' button to the session browser for better UX flow.
- Updated documentation to reflect v2.6.1 changes.
- Replaced the basic session list with a dedicated, card-based Session Browser page.
- Each session card now displays product name, category, description, and a thumbnail placeholder for better usability.
- Updated the backend DB manager to extract this rich information from the existing JSON data store.
- Refactored the frontend (App.tsx, types.ts) to support the new UI and data structure.
- Added new component SessionBrowser.tsx and its corresponding CSS.
- Updated documentation to reflect the v2.6 changes.
- 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.
- 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.
- Added documentation for Notion setup and resources (notion_integration.md).
- Added scripts for authentication test, database creation, and product insertion.
- Successfully tested connection and data mapping for 'RoboPlanet Product Master'.
- Added section on 'Hardware / DSL-Leitung' explaining the detected 17m branch line (Stichleitung) causing signal reflections and timeouts.
- Clarified that 'IP Flapping' was caused by stale caching of the previous day's IP, exacerbated by incorrect DNS settings (8.8.8.8).
- Finalized troubleshooting steps for Synology and FritzBox configuration.
- Documented the critical finding of hardcoded DNS (8.8.8.8) in Synology Network Interface settings overriding global DSM settings.
- Added comprehensive checklist for Synology, FritzBox, and Client configuration to ensure DNS stability and NAT loopback functionality.
- Updated log analysis section with 'NETWORK_WAIT' and 'ALERT' scenarios.
- Updated 'duckdns_setup.md' with critical instructions for configuring FritzBox DNS Rebind Protection to enable internal access (NAT Loopback).
- Added steps for clearing client-side DNS cache (Windows).
- Included Cloudflare DNS switch in documentation reflecting recent monitor script changes.
