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A comprehensive collection of AI-powered Python tools with extensive customization options for cartoon generation, text processing, image analysis, and code assistance.

• Advanced cartoon generation with customizable styles, resolutions, and art styles
• Multiple output formats (PNG, JPEG, WebP, TIFF, GIF)
• Style presets (classic, vintage, vibrant, monochrome)
• Custom color palettes and artistic options
• Thumbnail generation and quality enhancement
• Animated GIF creation from cartoon sequences

• Multi-provider AI support (OpenAI, Anthropic, Gemini)
• Story generation with genre, character, and theme customization
• Code generation with framework integration and documentation
• Article writing with SEO optimization and tone control
• Style presets for different writing purposes
• Reading time estimation and content analysis

• Comprehensive image analysis (objects, scenes, colors, quality)
• Advanced image processing with filter presets and custom effects
• Batch processing capabilities for multiple images
• Quality assessment with improvement recommendations
• Comparison grid generation for before/after visualization
• Annotation tools for analysis results

• AI-powered code generation with customizable complexity levels
• Comprehensive code review with quality scoring
• Test generation with coverage estimation
• Code optimization and refactoring suggestions
• Multi-language support (Python, JavaScript, Java, Go)
• Documentation generation and code explanation

1. Clone the repository:

git clone https://github.com/GizzZmo/AI-driven-Python-code.gitcd AI-driven-Python-code

2. Install dependencies:

pip install -r requirements.txt

3. Set up API keys (optional for demo):

export OPENAI_API_KEY="your-openai-key"export GEMINI_API_KEY="your-gemini-key"export ANTHROPIC_API_KEY="your-anthropic-key"

Run the comprehensive examples:

python examples.py

Or use individual components:

fromCartoonGeneratorimportCartoonGeneratorgenerator=CartoonGenerator(api_key="your-api-key")# Generate cartoon with custom optionscartoon=generator.generate_cartoon(prompt="Space adventure with robots",page_count=6,strips_per_page=3,resolution=(1920,1080),style='vibrant',color_palette=['#FF6B6B','#4ECDC4','#45B7D1'],art_style='anime',custom_options={'mood':'adventurous','target_audience':'teen'    })# Save with advanced optionsgenerator.save_pages(cartoon,"./output",format='PNG',apply_filters=True,enhance_quality=True,create_thumbnails=True)# Create animated GIFgenerator.create_gif_animation(cartoon,"./animation.gif")

fromTextGeneratorimportTextGeneratorgenerator=TextGenerator(provider="openai",api_key="your-key")# Generate a storystory=generator.generate_story(prompt="A robot discovers emotions",genre="sci-fi",length="short",characters=["ARIA-7","Dr. Chen"],setting="Neo-Tokyo 2157",themes=["consciousness","humanity"],target_audience="teen")# Generate codecode=generator.generate_code(description="REST API for todo list",language="python",include_tests=True,frameworks=["flask","sqlalchemy"])# Generate articlearticle=generator.generate_article(topic="Future of AI",article_type="informative",target_audience="tech professionals",keywords=["AI","machine learning"])

fromImageAnalyzerimportImageAnalyzeranalyzer=ImageAnalyzer(api_key="your-key")# Analyze imageanalysis=analyzer.analyze_image("image.jpg",analysis_types=['object_detection','scene_analysis','color_analysis'],save_annotations=True)# Process with filtersprocessed=analyzer.process_image("image.jpg",filters=['enhance','dramatic'],resize=(800,600),output_format='PNG')# Batch processingresults=analyzer.batch_process(input_dir="./images",output_dir="./processed",operations={'analyze': {'types': ['scene_analysis']},'process': {'filters': ['enhance'],'format':'PNG'}    })

fromCodeAssistantimportCodeAssistantassistant=CodeAssistant(api_key="your-key")# Generate codegenerated=assistant.generate_code(description="Calculate fibonacci numbers",language="python",include_tests=True,complexity_level="intermediate")# Review codereview=assistant.review_code(code_string,language="python",review_type="comprehensive")# Generate teststests=assistant.generate_tests(code_string,test_framework="pytest",coverage_goal=90)# Explain codeexplanation=assistant.explain_code(code_string,explanation_level="beginner",include_examples=True)

• Resolution: Custom dimensions (e.g.,(1920, 1080))
• Style presets:classic,vintage,vibrant,monochrome
• Art styles:cartoon,anime,realistic,sketch
• Color palettes: Custom hex color arrays
• Output formats:PNG,JPEG,WebP,TIFF
• Quality settings: Enhancement and filter options
• Animation: GIF creation with custom duration and loops

• Providers:openai,anthropic,gemini
• Style presets:creative,analytical,conversational,technical
• Content types: Stories, code, articles, documentation
• Languages: Multiple language support
• Frameworks: Integration with popular libraries
• Complexity levels:beginner,intermediate,advanced

• Analysis types: Object detection, scene analysis, color analysis, quality assessment
• Filter presets:enhance,vintage,dramatic,soft,sharp
• Custom filters: Brightness, contrast, saturation, blur parameters
• Output formats: Multiple image formats with quality control
• Batch operations: Process multiple images simultaneously

• Languages: Python, JavaScript, Java, Go
• Review types:quick,comprehensive,security,performance
• Test frameworks:pytest,unittest,jest,junit
• Complexity analysis: Cyclomatic complexity and maintainability scoring
• Optimization goals: Performance, readability, memory usage

AI-driven-Python-code/├── CartoonGenerator.py      # Advanced cartoon generation├── TextGenerator.py         # Multi-provider text generation├── ImageAnalyzer.py         # Comprehensive image analysis├── CodeAssistant.py         # AI-powered code assistance├── examples.py             # Comprehensive usage examples├── requirements.txt        # Project dependencies├── README.md              # Documentation└── examples_output/       # Generated demo files    ├── cartoons/         # Cartoon generation outputs    ├── images/           # Image analysis and processing    ├── text/             # Generated text content    └── code/             # Code generation and analysis

Support for multiple AI providers with seamless switching:

• OpenAI GPT models
• Anthropic Claude
• Google Gemini
• Local model integration

Efficient handling of multiple files:

• Parallel processing capabilities
• Progress tracking and error handling
• Configurable output organization

Automated quality metrics:

• Image quality scoring
• Code complexity analysis
• Content readability assessment
• Performance optimization suggestions

Flexible output formats:

• Multiple image formats with compression control
• Code export with documentation
• Analysis reports in various formats
• API-ready data structures

• Classic: Balanced brightness, contrast, and saturation
• Vintage: Muted colors with sepia tones
• Vibrant: Enhanced colors and contrast
• Monochrome: Grayscale conversion

• Creative: High temperature for imaginative content
• Analytical: Low temperature for factual content
• Conversational: Balanced for dialogue
• Technical: Precise for documentation

• Enhance: Improved brightness and clarity
• Vintage: Retro aesthetic with sepia
• Dramatic: High contrast and saturation
• Soft: Subtle blur for dreamy effect
• Sharp: Enhanced edge definition

The library provides comprehensive metrics:

• Generation time tracking
• Quality scores (0-100 scale)
• Complexity analysis for code
• Coverage estimation for tests
• Resource usage monitoring

• Input validation for all parameters
• Secure API key handling
• Error handling with detailed logging
• Rate limiting support
• Content filtering options

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Follow existing code style
5. Submit a pull request

This project is licensed under the MIT License - see theLICENSE file for details.

Theexamples.py script demonstrates:

• ✅40+ customization options across all modules
• ✅Multiple output formats and quality settings
• ✅Batch processing capabilities
• ✅Integration examples between modules
• ✅Error handling and validation
• ✅Performance optimization techniques

Runpython examples.py to see all features in action!

This repository includes a comprehensive GitHub Actions workflow system:

• CI: Continuous integration testing across Python 3.8-3.11
• Code Quality: Automated linting, formatting, and style checks
• Security & Dependencies: Vulnerability scanning and dependency management
• Release: Automated package building and publishing
• Dependencies: Monthly automated dependency updates

• ✅Multi-Python testing (3.8, 3.9, 3.10, 3.11)
• ✅Code quality enforcement (Black, Flake8, isort, Pylint)
• ✅Security scanning (Bandit, Safety, Semgrep, CodeQL)
• ✅Automated releases with PyPI publishing
• ✅Docker container support
• ✅Dependency vulnerability tracking

• Trigger dependency updates:workflow_dispatch on Dependencies workflow
• Force security scan:workflow_dispatch on Security workflow
• Create release: Push a tag likev1.0.0

For questions, issues, or feature requests:

• Open an issue on GitHub
• Check the examples for usage patterns
• Review the comprehensive docstrings in each module

Note: This library includes mock implementations for demonstration. Replace API calls with actual service integrations for production use.