Mind-Mate is an AI-powered application designed to support mental health through empathetic conversation, daily mood tracking, guided breathing exercises, and personalized activity suggestions.
Leveraging advanced language AI models, it provides users with a safe space to reflect, decompress, and find gentle encouragement-anytime, anywhere.
Access the application here
- Frontend: React-based UI located in
/app/frontend - Backend: FastAPI-based server located in
/app/backend - AI Integration: Gemini, HuggingFace
- DataStore: Firebase
- Hosting: GCP (Google Cloud)
Mind Mate follows a multi-agent architecture where specialized AI agents handle different aspects of mental wellness:
- Main Coordinator Agent - Central conversational interface with users
- Mood Analysis Agent - Processes emotional detection and sentiment analysis
- Activity Recommendation Agent - Matches current mood and suggest personalised receommendation
- Progress Tracking Agent - Analyzes long-term trends and generates insights
Prerequisites
-
Python 3.10+
-
Node.js (for frontend)
This project is configured to deploy to Google Cloud Platform (GCP) using Cloud Run for both frontend and backend services.
For detailed deployment instructions, see the DEPLOYMENT.md file.
- Mood Collages: Automatically generate visually appealing collages that capture a user’s mood history and positive journal notes, incorporating AI-driven image selection for more meaningful representations.
- Mood Journals: Introduce a personalised journaling feature that allows users to record their thoughts and emotions, with options to easily export or delete entries.
- Gamification and Achievements: Motivate users with mood-boosting challenges, streaks, and badges for positive journaling, completing recommended activities, or showing progress in self-care routines.
- Performance: Improving application processing by tailoring asynchronous background processing for heavy tasks.
- Voice Input: Let users log moods and journal notes via voice commands, making mood tracking more accessible and engaging.
- Dynamic Visualisation: Enhance accessibility by offering customisable visual elements and multiple display options to suit different user preferences and needs.
This project was developed by a team of six members. Team members and their contributions are as follows:
Team Members:
- Sonali Goel (Team Lead | Backend Engineer) | Website | GitHub | LinkedIn |
- Arzu Caner (Frontend Developer) | GitHub | LinkedIn | YouTube |
- Sonika Janagill (Backend and GCP Engineer) | GitHub | LinkedIn |
We would like to express our gratitude to the entire team for their contributions to our project.