Media Workflow

Overview

Automatski izvršava kompletan workflow obrade WhatsApp medija:

1. Process media → Transkribuje audio, OCR-uje slike
2. Integrate → Ubacuje procesirani sadržaj u chat.md fajlove
3. Report → Daje summary šta je obrađeno

Što radi:

• Poziva

  gastrohem-media-processor

  za audio/slike
• Poziva

  chat-integrator

  za integraciju u chat.md
• Sve u jednom koraku!

Output:

• .json

  audio transkripcije

• .md

  image summaries
• Ažuriran

  chat.md

  sa svim medijima integriranim
• Backup

  chat.md.backup

  prije izmjena

When to Use This Skill

User says:

• "Process and integrate media"
• "Do complete media workflow"
• "Process today's WhatsApp media"
• "Process and merge media for 24.10"

Default behavior: Uses today's date, processes all departments

Workflow

Simple Usage

Process and integrate for today (DEFAULT):

python .claude/skills/media-workflow/scripts/run_workflow.py

Process and integrate for specific date:

python .claude/skills/media-workflow/scripts/run_workflow.py --scan-date 24.10

Process and integrate specific folder:

python .claude/skills/media-workflow/scripts/run_workflow.py --folder "gastrohem whatsapp/administracija/20.10 - 27.10/24.10"

Dry run (preview changes):

python .claude/skills/media-workflow/scripts/run_workflow.py --dry-run

What Happens

Step 1: Media Processing

• Finds all folders for target date/folder
• Transcribes audio files in parallel (3 max)
• Creates

  .json

  audio transcriptions
• Performs OCR on images
• Creates

  .md

  image summaries

Step 2: Integration

• Extracts timestamps from filenames
• Parses existing chat.md entries
• Merges new + existing entries chronologically
• Creates backup:

  chat.md.backup

• Writes updated

  chat.md

Step 3: Report

• Summary of processed media
• List of integrated entries
• Any errors or skipped files

Script Reference

run_workflow.py

Purpose: Master workflow script

Arguments:

• --scan-date DD.MM

  - Process all departments for this date

• --folder PATH

  - Process specific folder

• --base-path PATH

  - Base path (default: "gastrohem whatsapp")

• --dry-run

  - Preview changes without writing

• --no-backup

  - Skip backup creation

• --output-json FILE

  - Save workflow results to JSON

What it does:

1. Runs

   gastrohem-media-processor

   script
2. Waits for media processing to complete
3. Runs

   chat-integrator

   script
4. Aggregates and reports results

Best Practices

1. Run daily - Process media daily to avoid backlog
2. Use --dry-run first - Preview changes before committing (especially first time)
3. Check results - Review integrated content for accuracy
4. Backups are automatic - Backup created before any chat.md modifications

Error Handling

If audio transcription fails:

• Skill continues with remaining files
• Reports failed files in summary

If image OCR fails:

• Skill continues with remaining files
• Reports failed files in summary

If integration fails:

• Backup remains intact
• Error logged with details

Example Workflow

User: "Process media"

Claude:

1. Runs:

   python .claude/skills/media-workflow/scripts/run_workflow.py

2. Step 1: Processes media for today (26.10)
   • Finds 3 folders: administracija/26.10, finansije/26.10, adis-chat/26.10
   • Transcribes 2 audio files →

     .json

   • OCRs 3 images →

     .md

3. Step 2: Integrates into chat.md
   • Merges 5 entries into 3 chat.md files
   • Creates backups
4. Step 3: Reports
   • "Processed 2 audio + 3 images across 3 folders"
   • "Integrated 5 entries into chat.md"
   • "✅ Complete workflow finished successfully"

Performance

• Total time: ~10-15 sec for típical daily folder
  • Media processing: ~5-8 sec (parallel)
  • Integration: ~2-3 sec
  • Overhead: ~1-2 sec

Output Structure

After running workflow on folder

24.10

:

gastrohem whatsapp/administracija/20.10 - 27.10/24.10/
├── chat.md                    # Updated with integrated media
├── chat.md.backup             # Backup before integration
├── image.png
├── image.png.md               # OCR summary
├── WhatsApp Audio *.mp3
└── WhatsApp Audio *.mp3.json  # Audio transcription