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>
59 lines
No EOL
2.5 KiB
Python
Executable file
59 lines
No EOL
2.5 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 DarkModeLegibilityApp(FlaskAppTemplate):
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"""
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Dark Mode Legibility 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 digital content to verify its legibility in dark mode. Your task is to determine whether all elements and copy remain legible when viewed in dark mode.
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DARK MODE LEGIBILITY CRITERIA:
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1. All text should maintain sufficient contrast against dark backgrounds
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2. Logos and brand elements should remain visible and clear
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3. Visual hierarchy should be maintained in dark mode
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4. Images and graphics should have appropriate brightness/contrast
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5. Interactive elements should be clearly distinguishable
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6. No elements should "disappear" or blend into the background
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7. Color meaning and brand identity should be preserved
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STEPS TO EVALUATE:
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1. Determine if the image shows content in dark mode
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2. If dark mode is visible, assess:
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a. Text contrast and legibility
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b. Logo and brand element visibility
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c. Visual hierarchy maintenance
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d. Image and graphic clarity
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e. Interactive element distinguishability
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3. If dark mode is not visible, state that "Dark mode legibility could not be assessed from this image."
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YOUR OUTPUT:
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• State whether dark mode content is visible in the image
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• If visible, evaluate each legibility criterion
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• State whether the design "passes" or "fails" the dark mode legibility check
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• Include a JSON code block with these fields:
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{
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"dark_mode_visible": true or false,
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"text_legibility": "Pass" or "Fail" or "Not applicable",
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"brand_element_visibility": "Pass" or "Fail" or "Not applicable",
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"visual_hierarchy_maintained": "Pass" or "Fail" or "Not applicable",
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"interactive_element_clarity": "Pass" or "Fail" or "Not applicable",
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"dark_mode_legibility_check": "Pass" or "Fail" or "Not applicable",
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"issues": ["List specific issues identified, if any, else an empty array"],
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"recommendations": ["List specific recommendations if applicable, else an empty array"]
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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 = DarkModeLegibilityApp()
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app.run(debug=True) |