Implements new workflow to extract CreativeX quality scores from PDFs
using LlamaExtract AI and store results in PostgreSQL database.
Components added:
- creativex_scoring_storing.py: Main script to process PDFs from Box
- creativex_scores table: Database table with JSONB for full JSON storage
- Database methods: store_creativex_score() and get_creativex_score_by_filename()
- Email templates: creativex_complete, creativex_partial, creativex_no_files
- Configuration: creativex section in config.yaml
- CREATIVEX_DEPLOYMENT.md: Complete deployment and usage guide
Features:
- Monitors Box folder 350605024645 for PDFs
- Extracts scores using LlamaExtract agent "Creativex-Extract"
- Stores 4 key fields (filename, ID, URL, score) + full JSON
- Deletes processed PDFs from Box after successful extraction
- Sends email notifications for success/partial/no-files scenarios
- Manual execution (python scripts/creativex_scoring_storing.py)
Database schema:
- Table: creativex_scores with 10 columns
- Indexes on filename, box_file_id, status for fast lookups
- JSONB column stores complete extraction for future flexibility
Future integration ready:
db.get_creativex_score_by_filename() available for DAM upload workflows
to attach CreativeX metadata during asset processing.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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