vignesh2027

LLM Evaluation Framework — AI skill for Claude Code

AI community

Production-grade LLM Evaluation & Benchmarking Framework - GPT-4, Claude, Gemini, Mistral.

How to install LLM Evaluation Framework

This entry records only its repository, not the path inside it, so there is no exact command to give. Open vignesh2027/LLM-Evaluation-Framework and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What LLM Evaluation Framework does

Production-grade LLM Evaluation & Benchmarking Framework - GPT-4, Claude, Gemini, Mistral. Accuracy, latency, cost, hallucination, reasoning metrics.

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README

LLM Evaluation Framework

The most complete open-source LLM evaluation suite.
Measure accuracy, latency, cost, hallucination, and reasoning quality across any LLM — side by side.

📋 Table of Contents

✨ Why This Framework?
🎯 Key Features
🏗 Architecture
🚀 Quick Start
📦 Installation
🔑 API Keys Setup
💻 CLI Reference
🐍 Python API
🌐 REST API Reference
📊 Streamlit Dashboard
📏 Evaluation Metrics
🏆 Supported Benchmarks
🤖 Supported Models & Pricing
🗄 Database & Storage
📄 PDF Report Generation
🐳 Docker Deployment
🧪 Testing
🤗 HuggingFace Dataset
📁 Project Structure
🔧 Configuration Reference
🤝 Contributing
📜 License
⭐ Star History

✨ Why This Framework?

*"You can't improve what you can't measure."* — Peter Drucker

The LLM landscape is evolving at breakneck speed. New models appear every week, each claiming to be state-of-the-art. But how do you **actually know** which model is best for *your* use case?

Most existing benchmarking tools: