🐢 Open-Source Evaluation & Testing for AI & LLM systems
Evaluation and Tracking for LLM Experiments
A single interface to use and evaluate different agent frameworks
🤖 A curated list of resources for testing AI agents - frameworks, methodologies, benchmarks, tools, and best practices for ensuring reliable, safe, and effective autonomous AI systems
Visual dashboard to evaluate multi-agent & RAG-based AI apps. Compare models on accuracy, latency, token usage, and trust metrics - powered by NVIDIA AgentIQ
Train a reinforcement learning agent using PPO to balance a pole on a cart in the CartPole-v0 environment using Gymnasium and Stable-Baselines3. Includes model training, evaluation, and rendering using Python and Jupyter Notebook.
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