Sweedney-The Mental Health Booster
Sweedney is an AI chatbot that offers emotional support to students, using Gemini's natural language understanding to foster meaningful conversations and encourage self-reflection.
Created on 2nd October 2024
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Sweedney-The Mental Health Booster
Sweedney is an AI chatbot that offers emotional support to students, using Gemini's natural language understanding to foster meaningful conversations and encourage self-reflection.
Describe your project
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In-Scope:
- An AI chatbot providing mental health support through empathetic conversations and psychological prompts.
- Integration of Gemini's natural language processing for understanding user emotions.
- Real-time responses and user interaction via a web-based interface.
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Out of Scope:
- Diagnosis or treatment of mental health conditions.
- Emergency support services or crisis intervention.
- Integration with third-party mental health resources.
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Future Opportunities:
- Expansion to mobile platforms for broader accessibility.
- Incorporation of machine learning for personalized user experiences.
- Collaboration with mental health professionals for enhanced content and resources.
Challenges we ran into
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API Integration Issues:
We faced challenges integrating Gemini’s API due to incorrect API key configurations, which led to authentication failures.
Solution: We reviewed the API documentation thoroughly and confirmed our API key was correctly set in the environment variables. Testing with sample requests helped ensure proper integration. -
Handling User Input:
Initially, the chatbot struggled with understanding certain user inputs, leading to irrelevant responses.
Solution: We refined the input parsing logic and added data validation to ensure user inputs were formatted correctly. Additionally, we trained the model with diverse example dialogues to enhance its understanding. -
User Experience Feedback:
Early user testing revealed that the chat interface felt cluttered, making it difficult to navigate.
Solution: Based on feedback, we simplified the UI, focusing on a clean design that enhances readability and usability. We also implemented a loading indicator to improve response feedback during interactions. -
Scalability Concerns:
We were concerned about handling multiple user sessions simultaneously, which could lead to performance issues.
Solution: We optimized server performance by implementing asynchronous handling of chat requests and using efficient data structures to manage user sessions.
By addressing these challenges through careful debugging, user feedback, and optimizations, we were able to create a more robust and user-friendly chatbot experience.
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