This Retrieval-Augmented Generation (RAG) application empowers users to interact with their PDF documents by leveraging Google's Gemini AI. It intelligently combines document retrieval with advanced generative AI capabilities to provide accurate, context-aware answers directly from the content of uploaded PDFs.

1 Open Issue Need Help Last updated: Jul 17, 2025

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AI Summary: This task requires expanding the existing PDF-only RAG application to support additional document formats like Word (.docx, .doc), PowerPoint (.pptx, .ppt), and text (.txt) files in a phased approach. This involves adding appropriate parsers to the backend (Python), updating the frontend file upload interface and MIME type handling, implementing robust file type validation on both client and server sides, and adding comprehensive testing. Future phases could include support for Excel, Markdown, RTF, HTML, and EPUB files.

Complexity: 4/5
enhancement good first issue backend frontend

This Retrieval-Augmented Generation (RAG) application empowers users to interact with their PDF documents by leveraging Google's Gemini AI. It intelligently combines document retrieval with advanced generative AI capabilities to provide accurate, context-aware answers directly from the content of uploaded PDFs.

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