The LLM Evaluation Framework
- evaluation-metrics
- evaluation-framework
- llm-evaluation
- llm-evaluation-framework
Repository Index
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Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
Evaluation code for various unsupervised automated metrics for Natural Language Generation.
- natural-language-generation
- natural-language-processing
- nlg
- nlp
A clinical decision-evidence benchmark: pull the one fact an answer rests on, and see whether the assistant's action moves with the evidence. Built on HealthBench.
FactCircuit: an auditable claim-and-evidence verification loop with immutable provenance, staged checks, bounded retrieval, and reproducible evaluation.
- accuracy-decline
- ai-safety
- audit-trail
- fact-checking
🔥 The first-ever interactive streaming video generation benchmark.
- avatar-performance
- interaction-streaming-video
- real-time-video-editing
- streaming-video-generation
An agent that compiles git maintenance chores into reusable programs, then decides whether to replay them by running checks rather than by guessing the task looks familiar
- agent-architecture
- git-automation
- llm-agents
- program-synthesis
Fault-injected tool environments with side-effect grading for evaluating and post-training LLM agents