Graph RAG UI: Powerful Chat with your Docs!
🛠️ Learn how to set up a powerful, open-source RAG (Retrieval-Augmented Generation) user interface on your local machine! 🚀 In this detailed tutorial, we'll walk you through the entire process of installing and configuring a customisable RAG UI that supports both hybrid and graph RAG pipelines. Whether you're working with OpenAI, Azure, or local models like OLLama, this guide covers everything from API key setup to document upload and chat functionality. Graph RAG UI: Chat with your Docs
👨💻 What you'll learn:
Cloning the repository and setting up your environment
Configuring API keys for RAG and Graph RAG
Installing necessary Python packages
Running the interface locally and troubleshooting common errors
Uploading documents and interacting with them through the chat UI
🔧 Key Features:
Hybrid and Graph RAG pipeline support
Complex reasoning and multimodal QA capabilities
Easy-to-use interface with document preview and reference features
Don't miss out on this chance to leverage AI for enhanced document retrieval and interaction. Follow along and get started today!
🔗 Links and Commands:
Repository link: https://github.com/Cinnamon/kotaemon/
Full commands in the video description!
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Timestamps:
0:00 Introduction
0:46 Initial Setup and Repository Cloning
1:18 API Key Configuration
2:08 Installing Necessary Packages
2:21 Running the Interface Locally
2:31 Uploading and Indexing Documents
4:36 Exploring Graph RAG and Troubleshooting
5:39 Final Thoughts and Next Steps
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