evaluating RAG with RAGAs (#197)

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README.md

@@ -59,6 +59,7 @@ If you're looking for in-depth tutorial-like examples, checkout the [tutorials](
 | [Contextual-Compression-with-RAG](/examples/Contextual-Compression-with-RAG/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Contextual-Compression-with-RAG/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#)   [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/enhance-rag-integrate-contextual-compression-and-filtering-for-precision-a29d4a810301/) |
 | [Instruct-Multitask](./examples/instruct-multitask) | <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/instruct-multitask/main.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54)](./examples/instruct-multitask/main.py)  [![LLM](https://img.shields.io/badge/local-llm-green)](#)   [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/multitask-embedding-with-lancedb-be18ec397543)|
 | [Evaluating Prompts with Prompttools](/examples/prompttools-eval-prompts/) | <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/prompttools-eval-prompts/main.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>   [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)|  |
+| [Evaluating RAG with RAGAs](./examples/Evaluating_RAG_with_RAGAs/) | <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Evaluating_RAG_with_RAGAs/Evaluating_RAG_with_RAGAs.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>   [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|  |
 | [AI Agents: Reducing Hallucination](/examples/reducing_hallucinations_ai_agents/) | <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/reducing_hallucinations_ai_agents/main.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54)](./examples/reducing_hallucinations_ai_agents/main.py) [![JS](https://img.shields.io/badge/javascript-%23323330.svg?style=for-the-badge&logo=javascript&logoColor=%23F7DF1E)](./examples/reducing_hallucinations_ai_agents/index.js) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#) |[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/how-to-reduce-hallucinations-from-llm-powered-agents-using-long-term-memory-72f262c3cc1f/)|
 | [AI Trends Searcher with CrewAI](./examples/AI-Trends-with-CrewAI/) |<a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/AI-Trends-with-CrewAI/CrewAI_AI_Trends.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>  [![LLM](https://img.shields.io/badge/openai-api-white)](#)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/track-ai-trends-crewai-agents-rag/)|
 | [SuperAgent Autogen](/examples/SuperAgent_Autogen) |<a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/SuperAgent_Autogen/main.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)||

examples/Evaluating_RAG_with_RAGAs/README.md

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+# Evaluating RAG with RAGAs and GPT-4o
+<a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Evaluating_RAG_with_RAGAs/Evaluating_RAG_with_RAGAs.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
+
+
+Ragas is a **framework for evaluating Retrieval Augmented Generation (RAG) pipelines**.
+
+Ragas provides you with the tools/metrics based on the latest research for evaluating LLM-generated text to give you insights about your RAG pipeline. Ragas can be integrated with your CI/CD to provide continuous checks to ensure performance.
+
+GPT4-o is used as an LLM to generate responses out of semantically close context chunks.
+
+![flow](../../assets/rag_evaluation_flow.png)
+
+Try it out on Colab - <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Evaluating_RAG_with_RAGAs/Evaluating_RAG_with_RAGAs.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>