Ragas

Open Source

LLM Evaluation Updated Feb 15, 2026

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Compared with 9 other LLM Evaluation agents Open source Self-hostable Updated Feb 2026

💰 Open Source 🔄 Updated Feb 2026 🖥️ Self-hostable

💰 Pricing

Open Source

Pricing not publicly listed.

🎯 Use Cases

Benchmarking different RAG pipeline configurations Evaluating the impact of retrieval model improvements Assessing the quality of generated answers in QA systems Fine-tuning language models for better RAG performance

⚖️ Pros & Cons

✅ Pros

Open-source and self-hostable, providing flexibility
Specialized for RAG evaluation with tailored metrics
Easy integration into existing workflows

❌ Cons

Requires technical expertise to set up and use effectively
Limited to RAG pipelines, not general LLM evaluation
Documentation or community support may be sparse

Overview

Ragas is an open-source framework designed to evaluate Retrieval Augmented Generation (RAG) pipelines by providing metrics and tools to assess the quality of retrieval and generation components. It helps developers measure the effectiveness of their RAG systems in terms of relevance, accuracy, and coherence. The tool is particularly useful for fine-tuning and benchmarking RAG-based applications.

Problem It Solves

It solves the problem of objectively evaluating the performance of RAG pipelines, which is critical for improving retrieval accuracy and generated output quality.

Target Audience: Developers and teams working with llm evaluation automation.

Inputs

• User configuration
• API credentials (if required)
• Task parameters

Outputs

• Automated task results
• Status reports
• Generated content or actions

Example Workflow

1 User configures the agent with required parameters
2 Agent receives input data or trigger
3 Agent processes the request using its core logic
4 Agent interacts with external services if needed
5 Results are returned to the user

Sample System Prompt


              You are Ragas, an AI assistant. Help the user accomplish their task efficiently.

Tools & Technologies

LLM APIs Python

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FAQs

Is this agent open-source?: Yes
Can this agent be self-hosted?: Yes
What skill level is required?: Intermediate

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