This thesis delves into the forefront of Natural Language Processing (NLP) by leveraging cutting-edge Transformer models. Through the utilization of technologies like PyPDF2, python-dotenv, faiss-cpu, Streamlit, and Langchain, a robust NLP framework is constructed. Langchain serves as the cornerstone, enhancing both language generation and comprehension. PyPDF2 facilitates seamless integration with PDF documents, while python-dotenv ensures secure management of environment variables. By combining state-of-the-art libraries with transformative AI models, this study showcases the profound impact on document processing, virtual assistants, and beyond, pushing the boundaries of NLP towards more natural and dynamic interactions.