Oliver/ai_qc
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Author SHA1 Message Date
nickviljoen
3f4cc149ad Process multi-page PDF reference assets with LLM summarization 
PDF brand guidelines were previously ignored - QC checks received no
content from uploaded PDFs. Now on upload, all pages are text-extracted,
summarized by Gemini into a structured brand guidelines summary, and
a cover image is extracted. QC checks receive the full summary in their
prompt and the cover image as visual reference.

- New backend/pdf_processor.py: text extraction, cover image, LLM summary
- brand_guidelines_db.py: summary/cover path tracking, cleanup on delete
- api_server.py: background processing on upload, summary-aware content
  retrieval, PDF cover image support, status/reprocess endpoints, startup
  backfill for existing unprocessed PDFs
- web_ui.html: processing status badges and upload feedback for PDFs

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-03-26 22:02:47 +02:00
nickviljoen
8c9401bf3c Add combined check, client-scoped assets, UI restructure, reporting, and report consolidation 
- Create visual_readability_contrast combined check merging text readability
  and background contrast into a single LLM call for L'Oreal Static profile
- Update loreal_static.json to use combined check (2 checks, 100-point scale)
- Add client_id filtering to brand guidelines (upload, fetch, backfill migration)
- Restructure settings modal from 5 tabs to 4: Profile, Create New Profile,
  Reference Assets, Reporting (removed Model Selection, merged Tools into Profile)
- Add GET /api/profile_usage_stats endpoint with summary cards and recent analyses
- Add POST /api/consolidate_reports endpoint generating HTML summary with
  pass/fail highlighting from multiple selected reports
- Add report selection checkboxes and consolidation controls to saved files list

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-03-04 19:10:32 +02:00
nickviljoen
3fec052c12 Create frontend and backend folder structure for deployment 
Organized the application into separate frontend and backend directories for cleaner deployment and better separation of concerns.

Frontend Directory (frontend/):
- index.html: Single-page web interface (renamed from web_ui.html)
- README.md: Frontend deployment guide
- Total size: ~113 KB (self-contained)
- Smart base path detection (works at / or /ai_qc/)
- No configuration changes required

Backend Directory (backend/):
- All Python files (api_server.py, llm_config.py, etc.)
- visual_qc_apps/: 33 QC check modules
- profiles/: 6 QC profile configurations
- brand_guidelines/: Reference asset storage
- config/: Environment configurations
- scripts/: Deployment automation
- uploads/, output/: Data directories
- requirements.txt, ai_qc.service, apache_config.conf
- Complete documentation

New Documentation:
- FOLDER_STRUCTURE.md: Comprehensive guide to new structure
- frontend/README.md: Frontend deployment instructions
- backend/BACKEND_README.md: Backend deployment guide

Deployment Mapping:
- frontend/ → /var/www/html/ai_qc/ (web root)
- backend/ → /opt/ai_qc/ (application directory)

Benefits:
- Clear separation of concerns
- Backend code not in web-accessible directory
- Independent frontend/backend updates
- Matches server's existing patterns (/opt/veo3, /opt/voice2text)
- Industry-standard architecture
- Easy to deploy and maintain

Original files preserved in root directory for reference.
Ready for production deployment following MIGRATION_GUIDE.md.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-06 11:55:53 +02:00