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+# Evaluating RAGs!
+
+In this repo we provide a streamlined approach to evaluating Retrieval-Augmented Generation (RAG) systems. It includes tools for assessing response accuracy, relevance, and overall performance, helping you optimize and refine RAG models with ease.
+
+---
+
+## 📬 Stay Updated with Our Newsletter!
+Get a FREE Data Science eBook 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. [Subscribe now!](https://join.dailydoseofds.com)
+
+[![Daily Dose of Data Science Newsletter](https://github.com/patchy631/ai-engineering/blob/main/resources/join_ddods.png)](https://join.dailydoseofds.com)
+
+---
+
+## 📢 Contribute to the AI Engineering Hub!
+We welcome contributors! Whether you want to add new tutorials, improve existing code, or report issues, your contributions make this community thrive. Here’s how to get involved:
+1. **Fork** the repository.
+2. Create a new branch for your contribution.
+3. Submit a **Pull Request** and describe the improvements.
+
+---
+
+## 📜 License
+This repository is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## 💬 Connect
+For discussions, suggestions, and more, feel free to [create an issue](https://github.com/patchy631/ai-engineering/issues) or reach out directly!
+
+Happy Coding! 🎉