Pyvisionai

Added
- Added new `-m/--model` parameter to `describe-image` command for model selection
- Added new `-s/--source` parameter to `describe-image` command for specifying image path
- Added comprehensive test coverage for CLI parameters:
- Tests for both `-m/--model` and `-u/--use-case` parameters
- Tests for both `-s/--source` and `-i/--image` parameters
- Tests for parameter precedence
- Tests for default model behavior
- Tests for deprecation warnings

Changed
- Updated CLI parameter handling to support both new and legacy model selection
- Updated CLI parameter handling to support both new and legacy image path specification
- Enhanced help messages with clearer model descriptions
- Improved error messages and help text for CLI commands
- Updated documentation to reflect new CLI parameters
- Added friendly guidance message for `-u/--use-case` users to consider using `-m/--model`
- Added friendly guidance message for `-i/--image` users to consider using `-s/--source`
- Enhanced parameter handling with proper precedence rules

Note
- The `-u/--use-case` parameter continues to be fully supported for backward compatibility
- The `-i/--image` parameter continues to be fully supported for backward compatibility
- We recommend using `-m/--model` and `-s/--source` for better consistency across commands
- Both parameter pairs will be maintained to ensure a stable user experience
- Users can choose either option based on their preference and existing scripts

Added
Claude Vision Integration
- Added `ClaudeVisionModel` class for Anthropic's Claude Vision API integration
- Implemented robust retry logic and error handling for Claude API calls
- Added handling for rate limits and server errors
- Added specific handling for API overload conditions (Error 529)
- Implemented exponential backoff for retries
- Added support for custom prompts with Claude Vision
- Added `describe_image_claude` function to main API

Testing Framework
- Added Claude-specific test markers (`pytest.mark.claude`)
- Added comprehensive test suite for Claude Vision model:
- Unit tests for initialization, configuration, and error handling
- Integration tests with real API calls
- Rate limit and retry logic tests
- Custom prompt handling tests
- CLI interface tests

Documentation
- Added Claude Vision model documentation in `docs/getting_started.md`
- Updated API documentation with Claude Vision integration details
- Added environment setup instructions for Anthropic API key
- Enhanced testing documentation with Claude-specific examples
- Updated CLI help messages with Claude Vision options

Configuration
- Added `ANTHROPIC_API_KEY` environment variable support
- Added Claude Vision model configuration in factory system
- Added retry strategy configuration for API calls

Enhanced
- Improved error handling with specific error types for API issues
- Enhanced retry logic for rate limits and server errors
- Updated model factory to support Claude Vision
- Improved test fixtures for better test isolation
- Enhanced documentation with more comprehensive examples

Fixed
- Proper handling of empty responses from Claude API
- Correct error propagation for authentication issues
- Improved rate limit handling with exponential backoff

Added
- Added Homebrew support for easy installation:
- Created Homebrew formula with all dependencies
- Added support for both cloud (OpenAI) and local (Ollama) models
- Automated installation of system dependencies (poppler, libreoffice)
- Added post-installation verification and helpful setup instructions
- Comprehensive documentation for Homebrew users

Changed
- Improved installation process with better dependency management
- Enhanced system compatibility checks
- Updated documentation with Homebrew installation instructions

Added
- Added retry mechanism for handling transient failures:
- Implemented RetryManager with configurable strategies
- Added support for exponential, linear, and constant backoff
- Added comprehensive logging for retry attempts
- Added proper error handling and delay management


Changed
- Improved error handling in model selection:
- Enhanced connection error handling for API calls
- Added graceful fallback when default model is unavailable
- Improved error messages with detailed failure context
- Enhanced test coverage:
- Added tests for retry mechanism with various strategies
- Added tests for model fallback scenarios
- Added mocked API tests for connection failures

Fixed
- Fixed model selection to properly handle connection failures
- Fixed retry delays to prevent excessive wait times
- Fixed logging to capture all retry and fallback attempts

Added
- Implemented Model Factory pattern for vision models:
- Added VisionModel base class with abstract methods
- Added ModelFactory for centralized model management
- Added concrete implementations for GPT4 and Llama models
- Added comprehensive logging for model lifecycle
- Added configuration validation for each model type

Changed
- Refactored model initialization to use factory pattern
- Improved error handling in model creation and validation
- Standardized model interface across all implementations
- Enhanced logging with model-specific context

Documentation
- Added docstrings for new model classes
- Updated logging documentation
- Added model factory usage examples

Added
- Implemented comprehensive logging across all extractors:
- Added structured logging for PDF processing stages
- Added progress tracking for DOCX file conversions and page processing
- Added detailed logging for PPTX slide extraction and conversion
- Added HTML processing status and element detection logging

Changed
- Standardized logging patterns across all extractors:
- Consistent start/completion messages
- Clear error reporting with context
- Progress indicators for multi-step operations
- Performance metrics logging
- Replaced print statements with proper logger calls
- Added logging initialization in all core modules
- Standardized log message format and levels:
- INFO for progress and success
- WARNING for non-critical issues
- ERROR for operation failures

Improved
- Enhanced benchmark testing reliability:
- Added self-contained benchmark test fixtures
- Improved test independence from environment
- Added comprehensive validation of benchmark metrics
- Removed dependency on pre-existing log files
- Added performance metrics logging for both CLI and API interfaces

Documentation
- Added logging configuration examples
- Updated docstrings with logging details
- Added benchmark metrics documentation