3fec052c12
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>
52 lines
No EOL
2.3 KiB
Python
Executable file
52 lines
No EOL
2.3 KiB
Python
Executable file
import os
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import sys
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# Add parent directory to path to import shared modules
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from visual_qc_apps.flask_app_template import FlaskAppTemplate
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class TextReadabilityApp(FlaskAppTemplate):
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"""
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Text Readability Check
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"""
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def __init__(self):
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# Define the hardcoded prompt
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prompt = """You are performing a visual quality‐control check on a Point of Sale (POS) advertisement. Your task is to determine whether the text on the advertisement is readable from the appropriate viewing distance:
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• For large media (Floor‐Standing Display Units, posters, etc.): The text must be clearly readable from about 3 meters away.
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• For smaller media (wobblers, shelf talkers, etc.): The text must be clearly readable from about 1 meter away.
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STEPS TO EVALUATE:
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1. Identify all text elements in the advertisement, excluding any terms and conditions.
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2. Examine the text size, font style, and contrast with the background.
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3. For each text element, assess whether it would be readable from the appropriate viewing distance.
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4. Pay special attention to:
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a. Text size - Is it large enough to be read from a distance?
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b. Font choice - Is the font clear and easily readable?
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c. Contrast - Does the text stand out clearly against its background?
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d. Spacing - Is there sufficient spacing between letters, words, and lines?
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5. Consider any potential obstacles to readability such as:
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a. Decorative fonts that sacrifice legibility for style
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b. Overlapping elements that obscure text
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c. Poor contrast that makes text blend into the background
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d. Text that is too small relative to viewing distance
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YOUR OUTPUT:
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• State whether the text elements "pass" or "fail" the readability checkpoint.
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• If they fail, provide 1–2 concise recommendations for improving text readability.
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• Include a JSON code block with these fields:
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{
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"text_readability": "Pass" or "Fail",
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"readability_score": "High", "Medium", or "Low",
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"recommendations": ["Recommendation 1", "Recommendation 2"] (only if "Fail")
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}"""
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# Initialize the Flask app with the prompt
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super().__init__(__name__, prompt)
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# Run the app if executed directly
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if __name__ == "__main__":
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app = TextReadabilityApp()
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app.run(debug=True) |