Multi-source RAG system with GPT-4 Turbo, news & academic papers integration

About This Workflow

What This Workflow Does

This workflow is an enterprise-grade RAG (Retrieval-Augmented Generation) system that integrates GPT-4 Turbo with news and academic papers to provide a comprehensive knowledge graph. It retrieves and aggregates information from multiple sources, allowing users to generate informed responses and make data-driven decisions. The workflow supports advanced natural language processing and knowledge retrieval capabilities.

Who Should Use This

This workflow is designed for developers, researchers, and knowledge engineers who want to leverage the power of GPT-4 Turbo and multi-source information retrieval in their projects. It is also suitable for businesses and organizations looking to build AI-powered knowledge management systems.

Key Features

• Retrieves and aggregates information from news articles, academic papers, and other sources
• Utilizes GPT-4 Turbo for advanced natural language processing and generation capabilities
• Supports multi-source knowledge retrieval and integration
• Enables users to generate informed responses and make data-driven decisions
• Can be easily customized and extended to fit specific use cases and requirements

How to Get Started

To use this workflow, simply import it into your n8n instance and configure the settings to fit your specific needs. You can connect your desired data sources, such as news APIs or academic databases, and adjust the workflow to retrieve and process the information accordingly.