RAG with multiple types of loaders like text, pdf and web
Query deep learning documents to get answers
Extract text from images using OCR
Extract key entities from text queries
Search documents and retrieve relevant chunks
Next-generation reasoning model that runs locally in-browser
Analyze PDFs and extract detailed text content
Extract text from multilingual invoices
Employs Mistral OCR for transcribing historical data
Extract and query terms from documents
Fetch contextualized answers from uploaded documents
Multimodal retrieval using llamaindex/vdr-2b-multi-v1
Extract PDFs and chat to get insights
Multi Loader RAG is an AI-powered tool designed to extract text from scanned documents. It leverages Retrieval-Augmented Generation (RAG) technology to search documents for answers. The application supports multiple types of loaders, including text, PDF, and web content, making it versatile for various document handling tasks.
• Multiple Loader Support: Handles text files, PDF documents, and web content seamlessly.
• Intelligent Search: Uses AI to efficiently search for specific information within documents.
• Scanned Document Compatibility: Capable of extracting text from scanned documents for analysis.
• Cross-Document Search: Enables searching across multiple documents to find relevant answers.
• Customizable: Allows users to fine-tune search parameters for better results.
• Efficient Processing: Designed for fast and accurate text extraction and retrieval.
What types of documents does Multi Loader RAG support?
Multi Loader RAG supports text files (.txt), PDF documents (.pdf), and web content.
Can I search across multiple documents at once?
Yes, Multi Loader RAG allows you to search across multiple documents to find the most relevant answers.
How accurate is Multi Loader RAG with scanned documents?
Multi Loader RAG is designed to work with scanned documents and provides high accuracy in text extraction and search, though results may vary based on document quality.