# RAG File Upload Retrieval-Augmented Generation (RAG) with file uploads, you'll typically need to integrate a file upload mechanism with a RAG pipeline that processes and indexes the uploaded data. This allows users to query the uploaded files using natural language. **Custom AI Assistants and Document Processing** Our platform enables the development of custom AI assistants that can efficiently process and utilize knowledge from a variety of uploaded documents stored locally. This feature enhances both data security and accessibility, ensuring that your information is protected while being readily available for AI processing when needed. The platform supports a wide range of file formats, including: * **PDF**: Widely used for documents due to its consistent formatting across different devices. * **DOCX**: Commonly used for text documents with complex formatting, originating from Microsoft Word. * **TXT**: A simple format for text files without any special formatting, making it versatile for basic document storage. * **CSV**: Used for storing data in a comma-separated values format, perfect for spreadsheets and databases. By integrating seamlessly with your local storage, our AI assistants can access and interpret these formats to provide enhanced services and insights, while also ensuring that your data remains within your control. This blend of functionality and security makes our platform a reliable choice for organizations looking to leverage AI in processing diverse document types. 1. **File Upload:**\ Users can upload files in PDF, DOCX, TXT, or CSV formats through a local storage interface. * **Validation:**\ The system checks each file's format and size to ensure they meet the specified limits. * Increased training file size from 1MB to 5MB per document * Increased number of upload-able files from 10 to 20 files * **Indexing:**\ Files are indexed and divided into sections for easy retrieval within a knowledge base designed for Retrieval-Augmented Generation (RAG). 2. **Training & Indexing:** * Extracts, preprocesses, and indexes document contents. * Offers configurable chunking strategies (e.g., semantic, fixed size). * Enhances retrieval context through metadata extraction. * OCR Document scraping training functionality 3. **Query & Retrieval:** * Retrieves relevant document snippets during assistant interactions. * Ensures AI can utilize uploaded knowledge for accurate responses. 4. **UI/UX Requirements:** * Users can view, manage, and delete uploaded files. * Allows file refreshing or reprocessing as needed. 5. **Security & Compliance:** * Access controls limit file uploads to authorized users. * Encryption and local storage policies meet CNX App Sec compliance standards. ### File Upload Options in iX Hello iX Hello provides two modes for using the File Upload options: * **Basic Mode**: This mode is designed for users who prefer a straightforward, easy-to-use interface. It offers essential features for quick file uploads without additional configuration or complexity. * **Studio Mode**: This mode is suitable for advanced users who require more control and customization over the file upload process. It includes enhanced features and settings that allow for more detailed adjustments. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.ixhello.com/ixhc/general/rag-file-upload.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.