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| # Changelog | |
| All notable changes to the AskVeracity fact-checking and misinformation detection system will be documented in this file. | |
| ## [0.4.2] - 2025-04-28 | |
| ### Added | |
| - Added performance metrics (Accuracy: 50.0%-57.5%, Safety Rate: 82.5%-85.0%) to app's About section | |
| ### Changed | |
| - Updated claim examples in app.py input placeholder | |
| - Updated app_screenshot.png to reflect current UI changes | |
| ## [0.4.1] - 2025-04-25 | |
| ### Updated | |
| - Updated architecture.md to improve accuracy of system description | |
| - Updated README.md to better reflect current system functionality | |
| - Removed references to deprecated source credibility assessment | |
| - Clarified documentation of domain quality boost in RSS feed processing | |
| ## [0.4.0] - 2025-04-24 | |
| ### Added | |
| - Added safety rate metric to performance evaluation | |
| - Measures how often the system avoids making incorrect assertions | |
| - Tracks when system correctly abstains from judgment by using "Uncertain" | |
| - Included in overall metrics and per-class metrics | |
| - New safety rate visualization chart in performance evaluation | |
| - Added safety flag to detailed claim results | |
| ### Updated | |
| - Enhanced `evaluate_performance.py` script to track and calculate safety rates | |
| - Updated documentation to explain the safety rate metric and its importance | |
| - Improved tabular display of performance metrics with safety rate column | |
| ## [0.3.0] - 2025-04-23 | |
| ### Added | |
| - Performance evaluation script (`evaluate_performance.py`) in root directory | |
| - Performance results visualization and storage in `results/` directory | |
| - Enhanced error handling and fallback mechanisms | |
| - Refined relevance scoring with entity and verb matching with keyword fallback for accurate evidence assessment | |
| - Enhanced evidence relevance with weighted scoring prioritization and increased gathering from 5 to 10 items | |
| - Added detailed confidence calculation for more reliable verdicts with better handling of low confidence cases | |
| - Category-specific RSS feeds for more targeted evidence retrieval | |
| - OpenAlex integration for scholarly evidence (replacing Semantic Scholar) | |
| ### Changed | |
| - Improved classification output structure for consistent downstream processing | |
| - Added fallback mechanisms for explanation generation and classification | |
| - Improved evidence retrieval and classification mechanism | |
| - Streamlined architecture by removing source credibility and semantic analysis complexity | |
| - Improved classification mechanism with weighted evidence count (55%) and quality (45%) | |
| - Updated documentation to reflect the updated performance metrics, enhanced evidence processing pipeline, improved classification mechanism, and streamlined architecture | |
| ### Fixed | |
| - Enhanced handling of non-standard response formats | |
| ## [0.2.0] - 2025-04-22 | |
| ### Added | |
| - Created comprehensive documentation in `/docs` directory | |
| - `architecture.md` for system design and component interactions | |
| - `configuration.md` for setup and environment configuration | |
| - `data-handling.md` for data processing and flow | |
| - `changelog.md` for version history tracking | |
| - Updated app description to emphasize misinformation detection capabilities | |
| ### Changed | |
| - Improved directory structure with documentation folder | |
| - Enhanced README with updated project structure | |
| - Clarified misinformation detection focus in documentation | |
| ## [0.1.0] - 2025-04-21 | |
| ### Added | |
| - Initial release of AskVeracity fact-checking system | |
| - Streamlit web interface in `app.py` | |
| - LangGraph ReAct agent implementation in `agent.py` | |
| - Multi-source evidence retrieval system | |
| - Wikipedia integration | |
| - Wikidata integration | |
| - News API integration | |
| - RSS feed processing | |
| - Google's FactCheck Tools API integration | |
| - OpenAlex scholarly evidence | |
| - Truth classification with LLM | |
| - Explanation generation | |
| - Performance tracking utilities | |
| - Rate limiting and API error handling | |
| - Category detection for source prioritization | |
| ### Features | |
| - User-friendly claim input interface | |
| - Detailed results display with evidence exploration | |
| - Category-aware source prioritization | |
| - Robust error handling and fallbacks | |
| - Parallel evidence retrieval for improved performance | |
| - Support for various claim categories: | |
| - AI | |
| - Science | |
| - Technology | |
| - Politics | |
| - Business | |
| - World news | |
| - Sports | |
| - Entertainment | |
| ## Unreleased | |
| ### Planned Features | |
| - Enhanced visualization of evidence relevance | |
| - Support for user feedback on verification results | |
| - Streamlined fact-checking using only relevant sources | |
| - Source weighting for improved result relevance | |
| - Improved verdict confidence for challenging / ambiguous claims | |
| - Expanded fact-checking sources | |
| - Improved handling of multilingual claims | |
| - Integration with additional academic databases | |
| - Custom source credibility configuration interface | |
| - Historical claim verification database | |
| - API endpoint for programmatic access |