A deep learning-based chatbot designed to analyze mental health conditions based on user inputs. The model detects emotions such as anxiety, depression, stress, and more using NLP techniques.

• Emotion Detection: Identifies various mental health states from text input.
• AI-Powered Chatbot: Provides supportive and engaging responses based on detected emotions.
• RoBERTa-Based Model: Fine-tuned on mental health-related datasets for accurate predictions.
• Streamlit UI: Simple web interface for easy interaction.
• Google Drive Integration: Loads models directly from Google Drive without storing them on GitHub.

• Python
• Hugging Face Transformers
• PyTorch
• Google Drive API
• gdown
• Streamlit
• GitHub
• Streamlit Cloud
• NLTK
• SpaCy

1. Clone the repository:

   git clone https://github.com/LUFFY-KingofCoder/mental_health_chatbot.git
   cd mental_health_chatbot

2. Install dependencies:

   pip install -r requirements.txt

3. Run the chatbot:

   streamlit run chatbot.py

Since GitHub has size limits, the model is stored in Google Drive. To use it:

1. Ensure gdown is installed:

   pip install gdown

2. Update chatbot.py with the correct Google Drive folder link.

• Open the chatbot in a browser using the Streamlit interface.
• Enter text, and the chatbot will analyze the emotional state.

• Managing large model files with GitHub LFS limitations.
• Fine-tuning RoBERTa for multi-class emotion classification.
• Ensuring real-time response efficiency on Streamlit Cloud.

• Enhance chatbot response personalization.
• Improve model accuracy with more mental health datasets.
• Deploy on a dedicated server for better performance.

Shashank Ghosh
GitHub: LUFFY-KingofCoder
LinkedIn: Shashank Ghosh