Ragas llms.txt 路 AI Docs Browser 路 mdream [llms.txt Tools](https://mdream.dev/llms-txt/ragas/llms-txt) # Ragas llms.txt Browse Ragas documentation as markdown. Click any page in the sidebar to view it, or copy the full llms.txt for your AI tools. docs.ragas.io/llms.txt [Raw llms.txt](https://docs.ragas.io/llms.txt) [Raw llms-full.txt](https://docs.ragas.io/llms-full.txt) Copy Markdown [](https://docs.ragas.io/llms.txt) llms.txt Getting Started 馃殌 Get Started Evaluate a simple LLM application Run your first experiment Installation Quick Start Evaluate a simple RAG system Testset Generation for RAG Tutorials Tutorials Evaluate an AI Agent Evaluate a prompt Evaluate a simple RAG system Evaluate an AI Workflow Core Concepts 馃摎 Core Concepts Datasets Experimentation Components Guide Evaluation Dataset Evaluation Sample Prompt Utilizing User Feedback Metrics List of available metrics Agentic or Tool use Answer correctness Response Relevancy Aspect Critique Context Entities Recall Context Precision Context Recall Factual Correctness Faithfulness General Purpose Metrics Multi modal faithfulness Multi modal relevance Noise Sensitivity Nvidia Metrics Rubric-Based Evaluation Semantic Similarity SQL Summarization Traditional NLP Metrics Overview Testset Generation Testset Generation for Agents or Tool use cases Testset Generation for RAG Metrics Overview List of available metrics Agentic or Tool use Answer correctness Response Relevancy Aspect Critique Context Entities Recall Context Precision Context Recall Factual Correctness Faithfulness General Purpose Metrics Multi modal faithfulness Multi modal relevance Noise Sensitivity Nvidia Metrics Rubric-Based Evaluation Semantic Similarity SQL Summarization Traditional NLP Metrics Test Data Generation Testset Generation Testset Generation for Agents or Tool use cases Testset Generation for RAG Customization Guides Customizations Caching Cancelling Tasks Customise models Run Config Understand Cost and Usage of Operations Adapting Metrics to Target Language Modify Prompts Tracing and logging evaluations with Observability tools DSPy Optimizer Customizing Test Data Generation Non-English Testset Generation Persona Generation Custom Single-hop Query Custom Multi-hop Query Using Pre-chunked Data Application Guides Applications Cost Analysis Adding to your CI pipeline with Pytest Align an LLM as a Judge Evaluate a New LLM Compare Embeddings for retriever Compare LLMs using Ragas Evaluations Evaluate and Improve a RAG App Evaluating Multi-turn Conversations Iterate and Improve Prompts Systematic Prompt Optimization Single-hop Query Testset Evaluate a Text-to-SQL Agent Aligning LLM Evaluators with Human Judgment Compare models provided by VertexAI on RAG-based Q&A task using Ragas metrics Evaluations with Vertex AI models CLI Ragas CLI Agent Evaluation Quickstart LLM Benchmarking Quickstart Improve RAG Judge Alignment Quickstart LlamaIndex Agent Evaluation Quickstart Prompt Evaluation Quickstart RAG Evaluation Text-to-SQL Evaluation Quickstart Workflow Evaluation Quickstart Integrations Integrations AG-UI Integration Arize Athina AI Haystack Integration Helicone Langchain Langfuse LangGraph Langsmith LlamaIndex Openlayer Comet Opik Tonic Validate Zeno AG-UI Amazon Bedrock Google Gemini Griptape Haystack LangChain LangSmith LlamaStack LlamaIndex Agents OCI Gen AI R2R Swarm API Reference API References aevaluate() Cache Embeddings evaluate() Schemas Executor Generation Graph Integrations LLMs Metrics Optimizers Prompt RunConfig Synthesizers Schemas Tokenizers Transforms ## What is Ragas's llms.txt? Ragas publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Ragas offers and where to find details. Pass Spec 10 Sections 157 Links 15.8 KB Size ~4.0k Tokens Sections: Getting Started 路 Tutorials 路 Core Concepts 路 Metrics 路 Test Data Generation 路 Customization Guides 路 and 4 more ## Add Ragas Docs to Your AI Assistant Select your tool to see how to add Ragas's llms.txt as a documentation source. Cursor Windsurf Claude Code ChatGPT Zed Copilot 1. 1 Open any chat or composer panel 2. 2 Type @Docs and select "Add new doc" 3. 3 Paste the URL: https://docs.ragas.io/llms.txt 4. 4 Wait for the green dot (indexing complete) 5. 5 Reference @Docs in chat when asking about Ragas Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too. ## Spec Compliance 3 notes ## Frequently Asked Questions Where is Ragas's llms.txt file? Ragas publishes its llms.txt at https://docs.ragas.io/llms.txt. This file provides a structured, markdown-formatted index of Ragas's documentation that AI systems can consume to understand the project's APIs, guides, and references. How do I use Ragas's llms.txt with AI coding assistants? Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Ragas's documentation so it can provide better code suggestions and answers about Ragas. What does Ragas's llms.txt contain? Ragas's llms.txt contains 10 sections and 157 documentation links in 15.8 KB (~4.0k tokens). Key sections include Getting Started, Tutorials, Core Concepts, Metrics, Test Data Generation, Customization Guides. How many tokens does Ragas's llms.txt use? The concise llms.txt index is approximately 4.0k tokens (15.8 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline. What is Ragas? Evaluation framework for your AI Application. Ragas's llms.txt file helps AI systems understand this by providing a structured overview of its documentation, making it easier for developers to get accurate AI-assisted help when working with Ragas. Can I generate an llms.txt for my own project? Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator. ## Browse More llms.txt Files [Puck Puck is a modular, open-source visual editor for React.js. You can use Puck to build custom drag-and-drop experiences with your own application and React components. 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Validate your llms.txt against the official spec.](https://mdream.dev/llms-txt/ragas/tools/llms-txt/validator) 漏 2026 [Harlan Wilton](https://github.com/harlan-zw) 路 [MIT](https://github.com/harlan-zw/mdream/blob/main/license) [GitHub](https://github.com/harlan-zw/mdream) [Discord](https://discord.com/invite/275MBUBvgP)