Gastrohem Media Processor

Overview

Automatski procesira WhatsApp media fajlove (audio i slike) u Gastrohem dnevnim folderima.

Što radi:

• Transkribuje audio fajlove paralelno (3x brže) → kreira

  .json

  fajlove
• Identifikuje slike koje trebaju OCR → kreira

  .md

  fajlove sa prirodnim sažetkom
• Default: Koristi današnji datum automatski
• Skenira SVE odjele odjednom za dati datum

Performance:

• Audio: Do 3 fajla istovremeno (paralelno)
• Slike: Batch OCR (sve odjednom sa Claude vision)
• Scan: Nalazi sve foldere za datum u <1 sekundi

Note: Skill kreira

.json

za audio i

.md

za slike - dodavanje u

chat.md

je odvojen korak.

When to Use This Skill

User says:

• "Process media"
• "Process today's media"
• "Transcribe audio files"
• "Process media for 24.10"
• "OCR images in today's folders"

Default behavior: Uses today's date, scans all departments automatically.

Workflow

Simple Usage

Process all media for today (DEFAULT):

python .claude/skills/gastrohem-media-processor/scripts/process_media.py

• Uses today's date automatically (26.10 danas)
• Scans ALL departments for folders matching today's date
• Transcribes audio in parallel
• Lists images needing OCR

Process specific date:

python .claude/skills/gastrohem-media-processor/scripts/process_media.py --scan-date 24.10

Process specific folder:

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

What Happens

Audio Processing:

1. Finds all audio files (

   .mp3

   ,

   .ogg

   ,

   .m4a

   ,

   .wav

   ,

   .opus

   )
2. Skips files that already have

   .json

   transcriptions
3. Transcribes in parallel (3 concurrent processes)
4. Creates JSON:

   {audio_filename}.json

   {
     "speakers": [],
     "chunks": [...],
     "text": "Full transcribed text here"
   }
   

Image Processing:

1. Finds all images (

   .png

   ,

   .jpg

   ,

   .jpeg

   ,

   .webp

   ,

   .bmp

   )
2. Checks which images DON'T have

   .md

   files
3. Returns list of images needing OCR
4. Claude reads images in parallel and creates natural summaries with Gastrohem-relevant info
5. Creates markdown:

   {image_filename}.md

   # image.png
   
   **Poslao:** Mahir Kadic
   **Datum:** 26.10.2025 13:58
   
   ---
   
   [Natural language summary focusing on Gastrohem-relevant information:
    contacts, names, emails, phone numbers, business details, etc.]
   

Script Reference

Three Separate Scripts

The skill now uses three modular scripts for better organization:

1. process_audio.py

Purpose: Audio transcription only (parallelized)

Usage:

python scripts/process_audio.py "path/to/folder" [--max-workers 3] [--output-json results.json]

Arguments:

• folder

  - Path to folder containing audio files

• --max-workers N

  - Max parallel processes (default: 3)

• --no-skip-existing

  - Re-transcribe files with existing JSON

• --output-json FILE

  - Save results to JSON

What it does:

• Finds audio files (

  .mp3

  ,

  .ogg

  ,

  .m4a

  ,

  .wav

  ,

  .opus

  )
• Skips files with existing

  .json

  transcriptions
• Transcribes in parallel (max 3 concurrent)
• Creates JSON files:

  {audio_filename}.json

Requirements:

insanely-fast-whisper

in PATH

---

2. process_images.py

Purpose: Image OCR helper functions

Usage:

# List images needing OCR
python scripts/process_images.py "path/to/folder" [--output-json images.json]

# Use in Python for batch processing
from process_images import save_ocr_md, batch_save_ocr, get_images_needing_ocr

Key functions:

• get_images_needing_ocr(folder_path)

  - Returns list of images without

  .md

  files

• save_ocr_md(image_file, summary, sender)

  - Save natural summary to

  .md

  file

• batch_save_ocr(ocr_results)

  - Save multiple OCR results at once

Markdown structure:

# image.png

**Poslao:** Mahir Kadic
**Datum:** 26.10.2025 13:58

---

Natural language summary focusing on Gastrohem-relevant information:
contacts, names, emails, phone numbers, business details, etc.

---

3. process_media.py

Purpose: Master script combining audio + images

Usage:

# Scan all folders for a specific date
python scripts/process_media.py --scan-date DD.MM [--output-json results.json]

# Process a specific folder
python scripts/process_media.py --folder "path/to/folder" [--output-json results.json]

Arguments:

• --scan-date DD.MM

  - Scan all departments for this date

• --folder PATH

  - Process specific folder

• --base-path PATH

  - Base path (default:

  gastrohem whatsapp

  )

• --no-skip-existing

  - Re-process all files

• --output-json FILE

  - Save results to JSON

What it does:

• Calls

  process_audio.py

  for audio files
• Calls

  process_images.py

  to find images needing OCR
• Returns combined results

Best Practices

1. Use

   --scan-date

   for daily processing - Automatically finds all folders for a specific date across all departments
2. Process audio in parallel - The script now handles up to 3 audio files simultaneously for faster processing
3. Batch OCR images - Read all images in parallel using Claude's vision for maximum efficiency
4. Save results to JSON - Use

   --output-json

   to keep a record of processing results
5. Process regularly - Process media files daily to avoid backlog
6. Separate chat.md updates - This skill creates JSON files; updating

   chat.md

   is a separate workflow

Error Handling

If transcription fails:

• Check that

  insanely-fast-whisper

  is installed
• Verify the audio file is not corrupted
• Check that the device (mps) is available
• Manually transcribe if necessary

If image OCR is unclear:

• Request higher quality image from sender
• Focus on extracting key information rather than perfect transcription
• Note any illegible portions in the context field

Example Workflows

User: "Process media"

Claude:

1. Runs:

   python .claude/skills/gastrohem-media-processor/scripts/process_media.py

2. Script uses today's date (26.10), scans all departments
3. Finds 3 folders: administracija/26.10, finansije/26.10, adis-chat/26.10
4. Transcribes 5 audio files in parallel →

   .json

   files created
5. Returns list of 3 images needing OCR
6. Claude reads all 3 images in parallel, creates natural summaries →

   .md

   files created
7. Reports: "Processed 5 audio and 3 images across 3 folders."

---

User: "Process media for 24.10"

Claude:

1. Runs:

   python .claude/skills/gastrohem-media-processor/scripts/process_media.py --scan-date 24.10

2. Same workflow for 24.10 date

Performance Improvements (Nove Optimizacije)

1. Paralelizacija Audio Transkripicja:

• Do 3 audio fajla se transkribuju istovremeno
• Koristi

  ThreadPoolExecutor

  za paralelno izvršavanje
• 3x brže nego prije

2. Batch OCR za Slike:

• Sve slike se mogu pročitati odjednom (parallel Read tool calls)
• Svaka slika dobija svoj

  .md

  fajl:

  image.png.md

• Prirodan sažetak sa fokusom na Gastrohem-relevantne informacije (kontakti, imena, brojevi, poslovni detalji)
• Helper funkcija

  save_ocr_md()

  za lako čuvanje

3. Automatski Scan Svih Foldera:

• Default: Koristi današnji datum (nije potrebno specificirati)
• Automatski pronalazi sve foldere za taj datum u SVIM odjelima
• Procesira sve odjednom

Struktura Skripti:

• process_audio.py

  - Audio only (paralelno)

• process_images.py

  - Image OCR helper functions

• process_media.py

  - Master skripta (kombinuje oba)

Tipična brzina:

• Audio: ~3-5 sec po fajlu (paralelno, 3 max)
• Slike: ~2-3 sec po slici (batch)
• Scan svih odjela: <1 sekunda