Find relevant text chunks from documents based on queries
Search documents using text queries
Extract text from document images
Extract and query terms from documents
Extract text from images with OCR
GOT - OCR (from : UCAS, Beijing)
Multimodal retrieval using llamaindex/vdr-2b-multi-v1
Fetch contextualized answers from uploaded documents
Analyze scanned documents to detect and label content
Extract text from images using OCR
Find similar text segments based on your query
Query deep learning documents to get answers
Process text to extract entities and details
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.