PDF RAG
RAG pipeline with PDF OCR, vector search and chat UI
Listed in categories:
Developer ToolsArtificial IntelligenceAPI
Description
RAG Kickstart template is a production-ready template designed for building Retrieval-Augmented Generation (RAG) applications. It offers a comprehensive setup for document processing, vector storage, and AI-powered question answering, all integrated with a user-friendly interface.
How to use PDF RAG?
To use the RAG Kickstart template, clone the repository, set up the required environment variables, and build the application using Docker. Once set up, you can upload documents through the web interface and start interacting with the AI-powered chat interface.
Core features of PDF RAG:
1️⃣
PDF document processing with OCR
2️⃣
Multi-document conversation context with filtering
3️⃣
Click-to-view document references with highlighting
4️⃣
Milvus DB support for billions of vectors
5️⃣
Slick web interface for large document processing
Why could be used PDF RAG?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Processing and answering questions from large PDF documents | ✅ | |
| # 2 | Creating interactive chat interfaces for document lookup | ✅ | |
| # 3 | Utilizing AI to enhance document search and retrieval capabilities | ✅ | |
Who developed PDF RAG?
The maker of this product is a team of developers focused on creating innovative solutions for document processing and AI applications. They emphasize open-source development and community collaboration.