Find relevant text chunks from documents based on queries
Extract text from PDF files
Identify and extract key entities from text
Multimodal retrieval using llamaindex/vdr-2b-multi-v1
Using Paddleocr to extract information from billing receipt
Process documents and answer queries
Query deep learning documents to get answers
Extract named entities from text
Extract key entities from text queries
Extract PDFs and chat to get insights
Answer questions based on provided text
Process and extract text from receipts
Upload and analyze documents for text extraction and Q&A
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.