🐢 Open-Source Evaluation & Testing for AI & LLM systems
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Updated
Aug 1, 2025 - Python
🐢 Open-Source Evaluation & Testing for AI & LLM systems
Deliver safe & effective language models
MIT-licensed Framework for LLMs, RAGs, Chatbots testing. Configurable via YAML and integrable into CI pipelines for automated testing.
A Python library for verifying code properties using natural language assertions.
An automated approach for exploring and testing conversational agents using large language models. TRACER discovers chatbot functionalities, generates user profiles, and creates comprehensive test suites for conversational AI systems.
Open-source tools, SDKs, and resources for AetherLab AI quality control platform
🚀 ARM64 Browser Automation for Claude Code - SaaS testing on 80 Raspberry Pi budget. The first solution that works where Playwright/Puppeteer fail on ARM64. Autonomous testing without human debugging.
This repository contains a study comparing the web search capabilities of four AI assistants: Gemini 2.0 Flash, ChatGPT-4 Turbo, DeepSeekR1, and Grok 3
Modular and extensible Python framework for applying synthetic inference and controlled perturbations to AI model inputs, labels, and hyperparameters. Evaluate robustness, sensitivity, and stability of algorithms under realistic variations and adverse scenarios.
Agentic Workflow Evaluation: Text Summarization Agent. This project includes an AI agent evaluation workflow using a text summarization model with OpenAI API and Transformers library. It follows an iterative approach: generate summaries, analyze metrics, adjust parameters, and retest to refine AI agents for accuracy, readability, and performance.
A pytest-based framework for testing multi AI agents (mAIa) system. It provides a flexible and extensible platform for creating and running complex multi-agent simulations and capturing the results.
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