# SigmaEval Documentation

> An open-source Python framework for statistical, end-to-end testing of Gen AI apps, agents, and bots

## Docs

- [How it Works](https://docs.sigmaeval.com/core-concepts/how-it-works.md): Understand the core evaluation process of SigmaEval, from defining success and simulating user interactions to judging and analyzing the results.
- [Statistical Foundations](https://docs.sigmaeval.com/core-concepts/statistical-foundations.md): Discover the statistical methods that power SigmaEval's conclusions, including one-sided binomial tests for proportions and bootstrap hypothesis tests for medians.
- [Why SigmaEval?](https://docs.sigmaeval.com/core-concepts/why-sigmaeval.md): Learn about the challenges of testing Gen AI applications and why a statistical, end-to-end evaluation framework like SigmaEval is necessary.
- [End-to-End Testing of Conversational AI](https://docs.sigmaeval.com/index.md): SigmaEval is an open-source Python framework for the end-to-end testing of conversational AI, chatbots, virtual assistants, and other LLM-based applications.
- [Quickstart](https://docs.sigmaeval.com/quickstart.md): Get started with SigmaEval in minutes with this hands-on tutorial
- [Tutorial: Testing Conversational AI with pytest and SigmaEval](https://docs.sigmaeval.com/tutorial.md): Learn how to write an end-to-end test for an AI Chatbot using pytest and SigmaEval

## OpenAPI Specs

- [openapi](https://docs.sigmaeval.com/api-reference/openapi.json)