{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/6"}],"enrichment":{"capability":"Evaluates generative AI application outputs using built-in and custom evaluators that measure quality, safety, and performance through mathematical metrics, NLP scores, and AI-assisted assessment.","skillfed_tags":["generative-ai","evaluation-framework","azure-sdk"],"use_cases":["Score model responses on quality dimensions (relevance, coherence, fluency) before deploying to production","Run safety evaluations (violence, hate, sexual content) on generated text to catch harmful outputs","Compare multiple model variants using consistent metrics across a fixed test dataset","Build custom evaluators for domain-specific quality criteria (e.g., medical accuracy, legal compliance)","Track evaluation results over time in Azure AI Foundry to monitor model drift or improvement"],"what_it_does":"Azure AI Evaluation is a Python SDK for measuring the quality and safety of generative AI application outputs. It provides a collection of built-in evaluators\u2014including NLP-based metrics like BLEU and ROUGE, AI-assisted quality assessors like Groundedness and Relevance, and safety evaluators for violence, sexual content, and self-harm\u2014alongside an API for running multiple evaluators together on datasets or live applications. You define column mappings to route your data to the right evaluator inputs, and the SDK returns scores and insights that help you understand your model's capabilities and limitations.\n\nThe package is designed for teams building on Azure who need systematic, repeatable evaluation of generative AI systems. It integrates with Azure AI Foundry for result tracking and supports both code-based and prompt-based custom evaluators, so you can extend it beyond the built-in metrics. Dependencies include Azure identity and storage libraries, OpenAI for some AI-assisted evaluators, and common data tools like pandas and httpx.","worth_installing":"Yes, if you are building generative AI applications on Azure and need systematic evaluation. The SDK is actively maintained, has no known vulnerabilities, and provides both out-of-the-box evaluators and extensibility for custom metrics. Requires Python 3.9+, Azure credentials for AI-assisted evaluators, and familiarity with the Azure ecosystem; not a lightweight choice for simple scoring tasks outside Azure."},"id":"azure-ai-evaluation","links":{"html":"https://skillfed.io/packages/azure-ai-evaluation","md":"https://skillfed.io/packages/azure-ai-evaluation.md","pypi":"https://pypi.org/project/azure-ai-evaluation/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-29","license_spdx":null,"license_treatment":"permissive","name":"azure-ai-evaluation","python_support":"supports_current","summary":"Microsoft Azure Evaluation Library for Python"},"popularity":{"monthly_downloads":341597,"position":7401,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.18.3"}