- Added support for customizable AI context and model selection in job search analysis.
- Improved logging to provide detailed information about AI analysis status and parameters.
- Updated README to mask sensitive LinkedIn credentials for security.
- Refactored AI analysis integration to streamline data preparation and result embedding.
- Added LinkedIn jobs parsing strategy to support job extraction from LinkedIn.
- Updated job search parser to include new site strategy and improved argument parsing for max pages and exclusion of rejected results.
- Enhanced README documentation to reflect new features and usage examples.
- Refactored existing strategies for consistency and improved error handling.
- Updated `ai-utils.js` to improve AI response parsing and added timeout handling for API requests.
- Modified `linkedin-parser` to refine search keyword handling and improve post extraction reliability.
- Enhanced location filtering logic and added more robust selectors for extracting post data.
- Improved logging for debugging purposes, including detailed extraction results and fallback mechanisms.
- Created core modules: `ai-analyzer`, `core-parser`, and `job-search-parser`.
- Implemented LinkedIn and job search parsers with integrated AI analysis.
- Added CLI tools for AI analysis and job parsing.
- Included comprehensive README files for each module detailing usage and features.
- Established a `.gitignore` file to exclude unnecessary files.
- Introduced sample data for testing and demonstration purposes.
- Set up package.json files for dependency management across modules.
- Implemented logging and error handling utilities for better debugging and user feedback.
