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…ação no dashboard
- Added SentimentCache class to manage sentiment analysis caching, reducing redundant calculations. - Integrated caching into DashboardAnalytics for sentiment analysis by profile. - Updated get_sentiment_by_profile and get_date_range_data methods to utilize caching. - Enhanced data filtering capabilities with content type options (both, caption, comments). - Modified data_loader to format full text with clear sections for captions and comments. - Updated app.py to reflect changes in sentiment analysis methods and display cache status. - Reindexing script now clears sentiment cache before reindexing. - Added cache invalidation and statistics retrieval methods to SentimentCache.
…reate exports folder
…board and reports
- Updated `get_sentiment_by_profile` to handle None profiles, allowing analysis for all profiles. - Improved sentiment analysis and engagement trend calculations. - Refactored `generate_policy_recommendations` to accept profile filters and engagement thresholds. - Enhanced HTML generation for policy recommendations with better sentiment visualization. - Added debug logging for recommendations generation. - Updated dependencies in `pyproject.toml` to include `reportlab` for PDF generation. - Improved error handling and messaging in recommendation generation.
…r improved readability
…ndations and reporting
- Created a new test file `test_nltk_stopwords.py` to verify the integration with NLTK's stopwords for the Portuguese language. - Implemented functionality to check for existing stopwords and download them if necessary. - Added basic statistics output for the total number of stopwords and examples. - Combined NLTK stopwords with custom technical terms for enhanced filtering. - Included a filtering test on a sample text to demonstrate the effectiveness of the combined stopwords.
…TXT, and PDF formats
…anced delete functionality
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Analise de sentimento
Geração de relatório
Recomendação de Políticas