- market_db_manager.py: Created SQLite manager for saving/loading projects.
- server.cjs: Added API routes for project management.
- geminiService.ts: Added client-side DB functions.
- StepInput.tsx: Added 'Past Runs' sidebar to load previous audits.
- App.tsx: Added auto-save functionality and full state hydration logic.
- StepOutreach.tsx: Improved UI layout by merging generated campaigns and suggestions into one list.
- Implement a central reverse proxy (Nginx) with Basic Auth on port 8090.
- Create a unified landing page (dashboard) to access B2B Assistant and Market Intelligence.
- Update frontends with relative API paths and base paths for subdirectory routing (/b2b/, /market/).
- Optimize Docker builds with .dockerignore and a Python-based image for market-backend.
- Enable code sideloading for Python logic via Docker volumes.
- Fix TypeScript errors in general-market-intelligence regarding ImportMeta.
- Implementierung der rollenbasierten Campaign-Engine mit operativem Fokus (Grit).
- Integration von Social Proof (Referenzkunden) in die E-Mail-Generierung.
- Erweiterung des Deep Tech Audits um gezielte Wettbewerber-Recherche (Technographic Search).
- Fix des Lösch-Bugs in der Target-Liste und Optimierung des Frontend-States.
- Erweiterung des Markdown-Exports um transparente Proof-Links und Evidenz.
- Aktualisierung der Dokumentation in readme.md und market_intel_backend_plan.md.
- Integrated ICP-based lookalike sourcing.
- Implemented Deep Tech Audit with automated evidence collection.
- Enhanced processing terminal with real-time logs.
- Refined daily logging and resolved all dependency issues.
- Documented final status and next steps.
- Refactored market_intel_orchestrator.py for direct Gemini API (v1) calls.\n- Updated model to gemini-2.5-pro for enhanced capabilities.\n- Implemented minimal stdout logging for improved traceability within Docker.\n- Optimized Dockerfile and introduced market-intel.requirements.txt for leaner, faster builds.\n- Ensured end-to-end communication from React frontend through Node.js bridge to Python backend is fully functional.
Behebt den TypeError beim Aufruf von GenerationConfig in der älteren Version der google-generativeai Bibliothek, indem das nicht unterstützte Argument entfernt wird.