A framework for evaluating large language models (LLMs) across a variety of tasks.
An interactive marimo notebook on ICICLE AI Tapis services, a hands-on RAG playground that shows every step, from embeddings and chunking to retrieval, grounded prompting and LLM-as-judge evals. Built for newcomers to RAG who want to see how each piece works.
Production-grade open-source LLM evaluation platform with G-Eval, LLM-as-a-Judge, RAG evaluation, and customizable AI evaluation pipelines.
Production-grade LLM-as-Judge evaluation framework with position, verbosity & self-enhancement bias mitigation. FastAPI + Streamlit + Python SDK.
Refactored Python package for evaluating AI-generated lecture summaries using ROUGE, G-Eval and statistical analysis.
제 8회 미래에셋증권 X 네이버클라우드 AI/Data 페스티벌
This repository provides a solution for generating detailed and thoughtful questions based on workout plans and evaluating their quality using the G-Eval metric. It is designed to assist fitness enthusiasts, trainers, and developers working with structured workout plans in improving the clarity, relevance, and usability of their questions.
Calibrated LLM-as-a-judge evaluation pipeline on AWS Bedrock Claude Sonnet 4.6 scores Claude Haiku 4.5 on AlpacaEval via DeepEval G-Eval with versioned rubrics, persisted chain-of-thought, and blind human calibration
Ši repozitorija skirta bakalauro darbui, kurio tikslas - tirti ir įgyvendinti lietuviškų pasirenkamojo atsakymo klausimų (MCQ) generavimo bei vertinimo procesą naudojant LLM.
DeepEval — independent third-party profile of a public API surface, by API Evangelist. DeepEval is an open-source LLM evaluation framework — built and maintained by Confident AI — for testing and benchmarking large language model applications. It is structured like Pytest but specialized for LLM systems, providing 40+ research-backed metrics (G-Eva
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