This project will develop an advanced AI-powered chatbot designed to facilitate seamless interaction with PDF documents.
Users can upload files of up to 200MB and pose questions to the chatbot, enabling them to explore and extract valuable insights from the content of the documents.
This application will utilize AWS Bedrock, Amazon S3, AWS EC2, Docker, Langchain and Streamlit tools and technologies.
The chatbot will understand and respond to user inquiries intelligently, making it a powerful tool for both educational and professional settings.
PyPDF divides the PDF content into vectors for machine-learning-friendly representation of the PDF's content.
The application processes the vector from Amazon S3 for similarities using Jurassic-2 Mid llm model to generate an answer that will respond to the user.
Streamlit creates a visually appealing and user-friendly interface for a smooth and interactive experience.
Students can use this application to enhance their ability to engage with academic articles and literature.
This project represents a significant advancement in educational technology and paves the way for improved student capabilities in navigating and relating to scholarly articles.
Through this project, we have developed an innovative PDF chatbot application designed to reduce the time spent on research and reading.