Pyquantify

- Extract keywords from text data to identify important terms and phrases.
- Export extracted keywords to a file for further analysis or visualization.
- Calculate the 'cosine similarity' between two data sources to identify how similar or dissimilar they are.
- Updated command descriptions for better clarity.
- Summarization now utilize a caching mechanism for faster retrieval of previously summarized text.
- Git is now a command instead of a flag for better clarity.

- Updated lang detection library, it now uses langid instead of langdetect
- This allows it to work on Windows operating system as well.

New Features:

1. Sentiment Analysis
- Introducing a new feature: Sentiment Analysis!
- Analyze sentiment data within the application.
- Export sentiment analysis results for further analysis.

Enhancements:

2. Command Grouping
- Grouped 'generate-wordcloud' and 'generate-word-frequency-chart' commands for a more streamlined user experience.

Bug Fixes:

3. Analyze Command Fix
- Language detection is now performed using an alternative library instead of the multinomial NB model.
- Resolves the issue where the 'analyze' command was not functioning as expected.

- Resolved an issue preventing the "analyze" command from executing.

- Perform semantic analysis on raw data, files, or websites using the pyquantify CLI.
- Explore various linguistic and statistical metrics for English text.
- Introducing the generate_freq_plot command.
- Analyze and visualize the frequency distribution of the top 20 words in your data.
- Option to export the frequency plot as an image file.
- Introducing the generate_wordcloud command.
- Generate visually appealing word clouds from your data.
- Option to export the wordcloud as an image file.
- Search for a specific word in the morphological table.
- Display morphological information for the searched word.
- Option to limit the displayed rows and export the analysis results.
- Generate abstractive summaries of the provided text and export it as a text file