EmotionAnalyzer is a project to leverages Python and Google AI to analyze the sentiments expressed in work emails. This tool enhances communication efficiency and fosters a positive work culture by detecting emotions and providing actionable insights.
- Sentiment Analysis: Utilizes AI algorithms to detect emotions such as appreciation, frustration, urgency, etc.
- Sentiment Analysis trend: Utilizes charts to present the sentiment's predominance.
- Actionable Insights: Provides advice and recommendations based on the emotional context of the emails.
Open a terminal and run:
$ pip install -r requirements
$ streamlit app.pyTo analyze work emails and retrieve emotional insights, follow these steps:
- Input the subject and body of the email into the designated fields.
- Click the 'Analyze' button to initiate sentiment analysis.
- Review the generated emotional insights and recommendations.
- Respond to emails empathetically based on the analysis results.
Contributions to EmotionAnalyzer are welcome! Whether you're interested in adding new features, fixing bugs, or improving documentation, please follow these guidelines:
- Fork the repository and create a new branch for your contribution.
- Ensure adherence to PEP 8 guidelines and maintain code cleanliness.
- Submit a pull request detailing the changes introduced by your contribution.
This project is licensed under the MIT License - see the LICENSE file for details.
- Special thanks to the developers of Google AI for providing powerful tools and resources.
- Inspired by the growing importance of emotional intelligence in professional settings.