Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊

Python client library for improving your LLM app accuracy

The fastest java expression compiler/evaluator

A framework to build scenario simulation projects where human and LLM based agents can participant in, with a user-friendly web UI to visualize simulation, support automatically evaluation on agent action level.

The TypeScript LLM Evaluation Library

This library implements various metrics (including Kaggle Competition, Medicine) for evaluating ML, DL, AI models, and algorithms. 📐📊📈📉📏

NLP tool for wide-range model reliability evaluations

CSH Evals, the modern way.

IELTS listening, speaking, reading and writing modules practice and evaluation with IELTS band calculation based on speech and text analysis and evaluation.

ARGAEL is an open-source Java desktop application designed to maximize the experience and efficiency of the process of annotating and evaluating arguments in large text corpora.

The official repository for the paper "Paraphrase Detection: Human vs. Machine Content".

3cb: Catastrophic Cyber Capabilities Benchmarking of Large Language Models

A functional chess game implemented in python, with pygame as a supporting graphics module.

Official Python client for the Mandoline API

Official Node.js client for the Mandoline API

Moodle plugin for evaluations with Moodle. This is the evaluation activity plugin.

Do a program evaluation that really counts! That will help other students and will put really make universities and colleges take students experiences to heart!

Evaluations for homeschoolers

You can build a robust opinion mining and website evaluation system on AWS. The combination of data collection, preprocessing, sentiment analysis, and rating calculation ensures that you can efficiently analyze user feedback and generate meaningful insights to evaluate websites.

Machine learning algorithms applied to explore Enron email dataset and figure out patterns about people involved in the scandal.