Research papers are rich sources of knowledge, yet accessing and extracting pertinent data from them can be arduous and time-consuming. Traditional methods like manual searching and skimming through documents are often inefficient, particularly when dealing with a large volume of papers. Moreover, staying updated with the latest developments in a field requires constant monitoring of new research publications, further adding to the workload. To tackle these challenges head-on, we propose the development of a PDF-driven chatbot powered by Google Gemini, an advanced natural language processing (NLP) platform. This chatbot aims to alleviate the struggles faced by researchers and students in accessing and extracting relevant information from academic papers. Through its conversational interface, users can interact directly with research papers, posing questions, requesting summaries, and extracting specific information in real-time. Leveraging the capabilities of Google Gemini, the chatbot can understand user queries, analyze PDF documents, and efficiently provide relevant answers and insights.