Welcome to the RAG Workbench Cookbook! This repository contains examples and tutorials from our team, partners, and community to help you learn and make the most of RAG Workbench. Please feel free to submit a pull request if you have content you would like to share using RAG Workbench.
Start with the RAG Workbench: Getting Started Tutorial. This notebook will guide you through the basic setup and introduce you to key concepts.
Check out our collection of step-by-step guides that cover essential concepts and features of RAG Workbench:
- Getting Started
- Integrate Real-Time User Feedback
- Hyperparameter Optimization
- Evaluation Metrics
- Distributed Tracing
- Demo: Evaluate LLM-generated PR Titles
Explore our easy-to-follow guides for popular frameworks like OpenAI, LlamaIndex, LangChain, and more. These examples come with pre-configured auto-instrumentation, eliminating the need for manual tracing of your RAG system:
Please refer to our official documentation. The documentation provides comprehensive guides, API references, and troubleshooting tips.
We value your feedback and are here to help you with any questions or issues you may encounter while using RAG Workbench or following the tutorials in this cookbook. If you have any suggestions, questions, or need assistance, please don't hesitate to reach out to us on Discord.
Happy debugging!