The Framework for Multilingual Low-Resource Language Evaluation.
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# EKA-EVAL Demo
EKA-EVAL Demo
Evaluation Framework for Low-Resource Multilingual Large Language Models
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# Overview
**EKA-EVAL** is a unified framework for evaluating **Large Language Models (LLMs)** across **low-resource multilingual languages**.
Most existing evaluation frameworks focus heavily on **English and high-resource languages**, while requiring complex CLI workflows and configuration files.
**EKA-EVAL solves this with a Zero-Code Web Interface**, enabling researchers to run multilingual evaluations directly from a browser.
### What the framework provides
| Capability | Description |
| -------------------------- | ------------------------------------------------- |
| 🌍 Multilingual Benchmarks | 55+ benchmarks including 23 multilingual datasets |
| 🖥 Zero-Code UI | Run evaluations without editing configs or code |
| 📊 Visual Analytics | Interactive charts and model comparisons |
| 🤖 AI Diagnostics | Automatic analysis of model failures |
| ⚡ Modular Framework | Easily extend with new models and datasets |
The **eka-eval-demo repository** provides the **complete UI-based evaluation platform**, combining a **React frontend** with a **FastAPI backend**.
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# Zero-Code Evaluation Interface
The **web interface** allows users to perform full evaluations without writing code.
### Workflow
```
Select Model → Choose Benchmarks → Configure Parameters → Run Evaluation → Analyze Results
```
Users can:
• select multilingual benchmarks
• configure prompts and inference parameters
• monitor evaluation progress
• visualize benchmark performance
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# UI Features
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## Benchmark Selection Dashboard
Users can build evaluation suites by selecting benchmarks from multiple categories.
Supported domains include:
| Category | Examples |
| --------------- | ------------ |
| Reasoning | ARC, MM …