- market_db_manager.py: Made DB_PATH configurable via environment variable.
- Dockerfile.b2b: Included market_db_manager.py in the B2B container image.
- docker-compose.yml: Configured separate DB paths and volumes for Market Intel and B2B Assistant.
- B2B Server: Added API routes for project management (list, load, save, delete).
- B2B UI: Implemented auto-save and a 'Project History' modal for loading past runs.
- 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.
- market_intel_orchestrator.py: Updated generate_outreach_campaign to identify all relevant roles, generate top 5, and return remaining as suggestions. Added specific_role mode.
- types.ts: Added OutreachResponse interface.
- geminiService.ts: Updated to handle new response structure and specificRole parameter.
- StepOutreach.tsx: Added sidebar section for Suggested Roles with on-demand generation buttons.
- market_intel_orchestrator.py: Updated analyze_company to NOT abort if homepage scraping fails (e.g. 403 Forbidden). Instead, it sets a placeholder and proceeds using external search signals.
- market_intel_orchestrator.py: Updated get_website_text to use a modern, realistic User-Agent to reduce blocking.
- market_intel_orchestrator.py: Adjusted Gemini prompt to handle missing homepage content gracefully.
- market_intel_orchestrator.py: Rewrote prompt in generate_search_strategy to explicitly distinguish between 'Your Company (Context)' and 'Reference Client (Seed)'. This fixes the issue where the AI was searching for competitors to the user's company instead of the reference client.
- market_intel_orchestrator.py: Clarified prompt in identify_competitors.
- market_intel_orchestrator.py: Added RAW JSON debug logging to stderr to diagnose missing fields.
- StepReport.tsx: Added Search Strategy ICP, Digital Signals, and Target Pages to both the UI view and the Markdown export.
- StepReport.tsx: Fixed 'Back' button behavior to prevent state reset (uses new onBack prop).
- App.tsx: Passed handleBack to StepReport onBack prop.
- types.ts: Extended SearchStrategy interface with optional fields for the new signals.
- Added searchStrategyICP, digitalSignals, and targetPages to the JSON output in market_intel_orchestrator.py.
- Updated the prompt and fallback error handling to include the new fields.
- Added new steps (7, 8, 9) for Search Strategy ICP, Digital Signals, and Target Pages to the b2b_marketing_orchestrator.py.
- Updated STEP_PROMPTS_DE and STEP_PROMPTS_EN with corresponding prompts.
- Extended STEP_TITLES for both German and English languages.
- Modified step_keys lists in format_context_for_prompt and next_step functions.
- Updated b2b_marketing_assistant_plan.md to reflect the new report sections.
- Consolidated architecture overview in readme.md\n- Updated deployment and development sections in b2b_marketing_assistant_plan.md and market_intel_backend_plan.md
- 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.
- Upgrade backend to use gemini-2.5-flash with sanitized HTML parsing (no token limit).
- Implement robust retry logic and increased timeouts (600s) for deep analysis.
- Add file-based logging for prompts and responses.
- Fix API endpoint (v1) and regex parsing issues.
- Frontend: Optimize PDF export (landscape, no scrollbars), fix copy-paste button, add 'Repeat Step 6' feature.
- Update documentation to 'Completed' status.
- Added Dockerfile and nginx.conf for frontend production build.
- Added docker-compose.yml to orchestrate backend and frontend.
- Updated geminiService.ts to support relative API paths via Nginx proxy.
- Updated documentation with deployment instructions for Synology/Docker.
- 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.
- Updated readme.md with new step 3 audit details.
- Updated market_intel_backend_plan.md with current status and achievements.
- Fixed SerpAPI key file path in orchestrator.
- Documented the transition to direct REST API calls and enhanced terminal UX.
- Added to parse industries from Markdown.
- Added to find local/national/international lookalikes.
- Added for deep tech audit (website search, scraping, AI analysis).
- Updated prompt engineering for better results grounding.
- 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.
Erfasst den erfolgreichen Umstieg auf Docker, der das 'cygrpc'-Problem gelöst hat. Dokumentiert den aktuellen '404 model not found'-Fehler und definiert den nächsten Schritt: das Testen des Modellnamens 'gemini-1.0-pro'.
Erfasst den aktuellen Stand des Projekts, einschließlich des Wechsels zu Docker zur Lösung des 'cygrpc'-Problems und des zuletzt aufgetretenen 'TypeError'. Detailliert die nächsten Schritte für die nächste Sitzung.
Behebt den TypeError beim Aufruf von GenerationConfig in der älteren Version der google-generativeai Bibliothek, indem das nicht unterstützte Argument entfernt wird.
Korrigiert den Docker-Buildfehler durch explizite Verwendung des pip-Executables aus der virtuellen Umgebung, um Probleme mit der systemweiten Paketverwaltung zu umgehen.
Erstellt ein mehrstufiges Dockerfile, um die Python- und Node.js-Umgebung für den Backend-Service zu kapseln. Dies soll die 'cygrpc'-Kompatibilitätsprobleme durch eine saubere, kontrollierte Build-Umgebung lösen.
