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  AI Mental Health Chatbot

🧠 About the Project

🎯 Inspiration

Mental health is an essential part of our well-being, yet many people hesitate to seek help due to stigma, lack of access, or fear of judgment. Inspired by the need for a safe, anonymous, and accessible support system, I decided to build a Mental Health Chatbot. The goal was simple: create a chatbot that could provide thoughtful, empathetic responses to users seeking mental health support.

🏗 How I Built It

The chatbot is powered by Groq’s LLaMA 3.3-70B Versatile model, ensuring intelligent and meaningful conversations. Here's the tech stack I used:

• LangChain for orchestrating LLM-based interactions
  
• ChromaDB for storing and retrieving knowledge from mental health resources
  
• PyPDFLoader to process and extract text from research papers and documents
  
• Sentence Transformers for embedding text and improving search accuracy
  
• Gradio for a simple, user-friendly chat interface
  
• Google Colab for cloud-based execution and testing
  

The chatbot reads mental health-related PDFs, stores key insights in a vector database, and retrieves relevant information when users ask questions.

🚀 What I Learned

This project was an exciting challenge, and I learned a lot:
✅ How to use LangChain for building intelligent retrieval-based applications
✅ The power of vector databases (ChromaDB) for storing and searching text
✅ How embeddings (Sentence Transformers) improve search accuracy
✅ The importance of designing empathetic and responsible AI responses

🛠 Challenges I Faced

• Balancing AI responses: Ensuring that the chatbot remains supportive while making it clear that it is not a replacement for professional help.
  
• Optimizing embeddings: Finding the right model for accurate search results.
  
• Handling PDF parsing: Some documents were structured poorly, making text extraction difficult.
  

Despite the challenges, seeing the chatbot respond meaningfully to users made it all worthwhile!

Built With

• chromadb
• gradio
• groqapi
• langchain
• llama3.3-70b
• pypdfloader
• python