(The code is in the branch 'master') An AI-powered system designed to enhance mental health support by providing real-time emotional analysis and personalized interventions through user interaction.
The global mental health landscape faces significant challenges, with rising mental health illnesses and suicide rates. Traditional communication methods between mental health professionals and individuals are limited, causing delays and inadequate support. This project leverages AI-powered emotional analysis to provide immediate, personalized care and early detection of suicidal ideation, offering a transformative solution for mental health support.
- Facilitate Discussion on Mental Health: Establish an online platform for open emotional expression with AI-driven guidance.
- Empower Self-Management: Provide tailored resources and actionable advice using AI technology.
- Personalized Assistance: Analyze individual circumstances with AI to create personalized reports and recommendations.
- On-Demand Support: Ensure 24/7 availability of the application for immediate access to support.
- AI Development: Develop a sophisticated AI system for natural, empathetic conversations.
- User-Friendly Design: Create an intuitive application interface for seamless user experience.
- Personalized Adaptation: Implement algorithms for sensitive responses to mental health conditions.
- Iterative Enhancement: Conduct testing and refine the application based on user feedback.
- Integration of NLP, AI, vector search databases, and PDF text extraction.
- Features like natural conversations, personalized detection of mental health states, and seamless data processing.
- Fast and stable internet connectivity.
- Compatibility with required libraries and frameworks.
- Minimum: Windows 10, Intel Core i5, 8GB RAM, 256GB SSD, Python 3.7+
- Recommended: Windows 10, Intel Core i7, 16GB RAM, 512GB SSD, Python 3.7+, GPU with 4GB VRAM
- Minimum: macOS Mojave, Intel Core i5, 8GB RAM, 256GB SSD, Python 3.7+
- Recommended: macOS Catalina, Intel Core i7 or Apple M-Series, 16GB RAM, 512GB SSD, Python 3.7+
- Compatible with libraries like PyPDF2, OpenAI's Python library, FAISS.
- Use IDEs like Visual Studio Code, PyCharm, or Jupyter Notebooks.
- Implement robust security measures for handling sensitive data, including secure storage for API keys and access tokens.
- Clone the repo:
git clone https://github.com/HarSen0604/Medical-Chatbot.git
- Navigate to the directory:
cd Medical-Chatbot
- Install the required packages:
pip install -r requirements.txt
- Add your OpenAI key to
app.py
. - Run the application:
python app.py
- Click on the link shown in the terminal.