RAG PDF Chatbot

What is RAG PDF Chatbot ?

RAG PDF Chatbot is an AI-powered tool that enables users to interact with PDF documents through a conversational interface. It leverages Retrieval-Augmented Generation (RAG) technology to analyze and extract content from PDF files, allowing users to ask questions, summarize information, and engage with the document dynamically.

Features

• AI-driven PDF analysis: Automatically processes and understands PDF content to provide relevant answers.
• Text extraction and summarization: Extracts key information and provides concise summaries of PDF documents.
• Multi-PDF support: Can analyze and reference multiple PDF files simultaneously.
• Contextual understanding: Maintains context during conversations to deliver accurate and relevant responses.
• Language versatility: Supports multiple languages for a global user base.
• User-friendly interface: Offers a simple chat-like interface for easy interaction.
• Fast processing: Delivers quick responses even for large or complex PDFs.

How to use RAG PDF Chatbot ?

1. Launch the chatbot: Open the RAG PDF Chatbot application or access it through your preferred platform.
2. Upload your PDF: Select and upload the PDF document you wish to work with.
3. Start conversing: Ask questions or provide prompts related to the PDF content.
4. Receive responses: The chatbot will analyze the PDF and deliver relevant answers or summaries.
5. Refine your query: If needed, adjust your questions to get more specific or detailed information.

Frequently Asked Questions

What does RAG stand for?
RAG stands for Retrieval-Augmented Generation, a technology that combines document retrieval with AI generation to provide accurate and context-specific responses.

Can I upload multiple PDF files at once?
Yes, RAG PDF Chatbot supports multi-PDF uploads, allowing you to reference and analyze multiple documents in a single session.

Are there any file size limits for PDF uploads?
Yes, while the chatbot can handle large PDFs, there may be file size restrictions depending on the platform or deployment. Check the documentation for specific limits.