This project is an interactive Q&A application designed to provide insights from PDF documents. The project uses Llama3, a large language model, and the Groq API to deliver accurate and efficient responses. Users can upload PDF documents, ask questions, and receive relevant answers based on the content of the uploaded PDF.

• Python: The primary programming language used for the backend logic.
• Streamlit: For building the interactive web application interface.
• LangChain: To manage and orchestrate the language model interactions.
• FAISS: A library for efficient similarity search and clustering of dense vectors, used for handling embeddings.
• Groq API: To leverage advanced computational resources for model inference.
• Hugging Face Embeddings: For embedding generation and processing.

The user is not responsible for any type of content produced by the model. The responses generated by the model are based on the provided PDF documents and the capabilities of the underlying language model.