No-Net AI: Smart PDF Assistant

No-Net AI: This project is a PDF-based AI Q&A system that combines a FastAPI backend with a Gradio frontend, allowing users to upload PDFs and ask questions about their content. The backend processes uploaded files by extracting text using the PyMuPDF library and then utilizes Ollama’s Mistral AI model to generate relevant answers. FastAPI handles file management, text extraction, and API interactions efficiently, ensuring smooth processing of user queries. The system operates locally, providing privacy and fast inference without relying on external cloud services. The Gradio-powered frontend offers a simple and interactive web interface, enabling users to upload PDFs and receive AI-generated responses instantly. Users can type questions related to the document, and the system dynamically fetches answers by analyzing the extracted text. The backend and frontend communicate via API requests, ensuring a seamless user experience. Additionally, error handling is implemented to manage cases like file upload failures, missing documents, and invalid responses from the AI model. The entire system is designed for accessibility, privacy, and ease of use, making AI-powered document analysis available to both technical and non-technical users. With its offline capability, this project serves as a secure and efficient AI assistant for document-based inquiries.