This project introduces a comprehensive chatbot designed to educate users about the VA loan process. Leveraging advanced natural language processing techniques, the chatbot integrates insights and information from seven leading books on VA loans, authored by various experts in the field. By providing a user-friendly interface and real-time, accurate responses, the chatbot aims to demystify the complexities surrounding VA loans and assist veterans and their families in making informed decisions.
- Expert Knowledge Base: Incorporates knowledge from seven authoritative books on the VA loan process, ensuring users receive well-rounded and expert advice.
- Real-time Assistance: Powered by a state-of-the-art conversational AI, the chatbot delivers instant responses to user inquiries, ranging from basic questions to detailed explanations.
- User-friendly Interface: Designed with simplicity in mind, enabling easy navigation and interaction for all users regardless of their technical expertise.
- Customized Learning: Tailors information delivery based on user queries, ensuring relevance and fostering a personalized learning experience.
The chatbot utilizes the Retrieval-Augmented Generation (RAG) technique, combining the power of a large language model with a vector-based retrieval system. This approach allows the chatbot to understand user queries in depth and fetch the most relevant information from the embedded books' content, ensuring accurate and contextual responses.
- Installation: Ensure you have Python and necessary libraries installed. All required libraries are listed in the
requirements.txtfile. - Launching the Chatbot: Run
main.pyto start the chatbot. Access it through a web interface, providing an intuitive platform for users to ask questions. - Ask Away: Simply type in your question related to the VA loan process, and the chatbot will provide you with the information extracted from the embedded expert books.
Contributions are welcome! If you have suggestions for improving the chatbot or want to add more resources to its knowledge base, please feel free to fork the repository and submit your pull requests.