ai-evaluation

Overview

A community-built evaluation framework for AI workflows, written in Python. It provides tools to assess and validate outputs from AI models and pipelines.

Best for

Best for
Developers seeking a simple, open-source evaluation framework for AI workflows

Use cases

• Testing and scoring LLM responses against expected criteria
• Monitoring performance of AI systems in production
• Validating outputs from custom AI workflows

Notes

A community-built evaluation framework for AI workflows, written in Python. It provides tools to assess and validate outputs from AI models and pipelines.

105 stars on GitHub. Last updated 2026-05-29. Licensed Apache-2.0.

Use cases

• Testing and scoring LLM responses against expected criteria
• Monitoring performance of AI systems in production
• Validating outputs from custom AI workflows

Pros

• Open source and free to use
• Lightweight Python implementation
• Focused specifically on AI evaluation

Cons

• Small community with only 105 stars
• Limited documentation and examples
• May lack advanced features found in larger frameworks

Indexed from awesome-llmops and enriched against its public facts.