Find relevant text chunks from documents based on queries
Parse and extract information from documents
Extract key entities from text queries
Extract text from documents or images
Find relevant passages in documents using semantic search
Extract named entities from medical text
Extract text from images using OCR
Traditional OCR 1.0 on PDF/image files returning text/PDF
Search and summarize documents with natural language queries
Multimodal retrieval using llamaindex/vdr-2b-multi-v1
Convert images with text to searchable documents
Extract text from documents
Compare different Embeddings
Rag Community Tool Template is a pre-built framework designed to simplify the creation of applications that utilize Retrieval-Augmented Generation (RAG) systems. It provides a structured foundation for developers and users to extract text from scanned documents and find relevant chunks of text based on specific queries. This template is particularly useful for building custom tools that automate document analysis and information retrieval tasks.
What document formats does the tool support?
Rag Community Tool Template supports PDF, JPEG, PNG, TIFF, and other common document and image formats.
Can I use my own AI model with the template?
Yes, the template is compatible with multiple AI models, allowing you to integrate your preferred model for text extraction and analysis.
How do I improve the accuracy of text extraction?
To improve accuracy, ensure high-quality scanned documents, use specific and well-defined search queries, and refine your AI model configuration as needed.