All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
0.0.2 - 2025-01-31
- Support for "all" rows in config with increased batch size to 1000
- Schema-based element validation framework (removing default elements)
- XML formatting for mock responses and enhanced response validation
- Ellipsis support in QueryGenerationPipe for truncated outputs
- Initialization module for assets/scripts package
- Moved metadata to the top of QueryGenerationPipe
- Enhanced XML validation and extraction logic in TemplateValidator
- Streamlined logging by using the base Pipe class method
- Unified method signatures and removed redundant returns
- Improved code documentation and organization
- Removed unwanted "NoneNoneNone..." output on successful export command
- No notable updates
0.0.1 - 2025-01-27
- Initial release with core functionality implemented
- Basic pipeline architecture for data processing
- CLI commands for dataset management
- Documentation suite with installation and usage guides
- Updated Python version requirements and dependencies
- Simplified installation process in README
- Removed deprecated configuration files
- Streamlined error handling in query processing
- Optimized exception handling flow
- Enhanced logging clarity
-
Diplomatic cable generation system:
- Chain of Thought (CoT) template framework
- Eight-stage processing pipeline (thinking through review)
- Validation rules and constraints framework
- Ethical guidelines for content generation
- Professional tone enforcement
- Structured JSON/XML output formats
- Temporal range validation (2015-2025)
-
Enhanced pipeline architecture:
- QueryGenerationPipe with dynamic templating
- ResponseGenerationPipe with Ollama integration
- FileUploadHfApiPipe for Hugging Face API uploads
- ExportTablesPipe with schema validation
- LoadTemplatesPipe and SeedTemplatesPipe for template management
- NormalizeTextPipe for text standardization
- AsyncIO support for concurrent processing
-
Provider system:
- OllamaProvider with async request handling
- Base Provider class with validator support
- Pydantic validation integration
- Tenacity retry mechanism
- Configuration validation framework
-
Processing optimizations:
- Increased batch size to 500 for improved throughput
- Configured max workers (10) for parallel processing
- Enhanced memory management with periodic cleanup
- Streamlined database session handling
- Improved caching with LRU implementation
-
Configuration management:
- Migrated from TOML to YAML format
- Centralized provider configurations
- Enhanced path resolution system
- Dynamic variable validation
- Environment-based configuration controls
- Error handling improvements:
- Enhanced SQLAlchemy integration
- Streamlined exception handling
- Improved transaction management
- Better logging granularity
- Enhanced data validation
- Moved sensitive data from config files to environment variables
- Implemented strict content generation guidelines
- Added comprehensive input validation
- Enhanced error message sanitization
- Template framework improvements:
- Review and feedback stage (Stage 8) integration
- Standardized [CONSTRAINTS] headers with @category prefixes
- Unified validation rules across all stages
- Enhanced metadata and input configurations
- Performance optimizations:
- Increased batch processing capacity to 500 items
- Configured parallel processing with 10 workers
- Enhanced memory management
- Improved database operation efficiency
- Streamlined error handling in batch processing
- Enhanced template path resolution
- Improved validation consistency
- AI Integration features:
- OllamaProvider with async capabilities
- Template-based generation system
- Response validation framework
- Dynamic configuration management
- Architecture improvements:
- Migrated to async/await patterns
- Enhanced session management
- Optimized database operations
- Improved configuration structure
- Database lock handling
- Template rendering issues
- Configuration validation
- Core infrastructure:
- Flask-based HTTP server
- LLaMA model integration
- CUDA support system
- System requirement validations
- Enhanced logging system:
- Rich console output
- Structured error tracking
- Performance monitoring
- Debug information management
- CUDA detection and initialization
- WSL compatibility issues
- Error handling flow
- Foundation components:
- Basic pipeline architecture
- Database integration
- Configuration management
- Logging framework
- CLI command structure
- Documentation structure:
- Installation guides
- Architecture documentation
- API documentation
- Deployment guides
- Initial setup issues
- Configuration handling
- Path resolution problems
- Project initialization:
- Basic project structure
- Core dependencies
- Initial documentation
- Testing framework
- Development environment setup
- Build configuration
- Project organization
- Project planning documentation:
- Technical requirements analysis
- Architecture design decisions
- Development roadmap
- Environment specifications
- Development tooling:
- Devcontainer configurations
- Cross-platform build setup
- Testing framework selection
- Code quality tools
- Development approach:
- Selected MediatR for event architecture
- Chose Serilog for logging
- Adopted SQLite for data storage
- Implemented Python best practices
- Initial project concept:
- Research on LLMs and data processing
- Feasibility studies
- Technology stack evaluation
- Development methodology selection
- Repository initialization:
- Basic directory structure
- License and README
- Git configuration
- Development guidelines
- Project direction:
- Focused on Python ecosystem
- Selected key dependencies
- Defined coding standards
- Established version control workflow