# MGdaasLab/WHartTest

WHartTest 是一款AI驱动的测试自动化平台，实现从需求到可执行测试用例的自动化生成与管理，帮助测试团队提升效率与覆盖率。 (WHartTest is an AI-driven test automation platform that automates the generation and management of executable test cases from requirements, helping testing teams improve efficiency and coverage.)

Repository: https://github.com/MGdaasLab/WHartTest
Canonical: https://ross.abutalabs.com/products/wharttest
Homepage: https://wharttest.mgdaas.com/
Language: Python
License: NOASSERTION
License Family: other
Topics: ai-testing, test-case-generation, ai-test-platform, automated-testing, intelligent-testing, browser-automation
Last push: 2026-08-21T02:24:40+00:00

## Health v2 (maintenance only)
Score: 83/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 98, release rhythm 98, longevity 25
- inputs: {"age_days": 352, "days_push": 13, "days_rel": 13, "gap_med": 10, "n_releases_24m": 20}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1013, forks 159 (observed 2026-08-28T04:03:13.726269+00:00)

## What it is
WHartTest is an AI-driven test automation platform built on Django 5.2 + DRF with a Vue frontend, generating and managing executable test cases from requirements. It combines LangChain/LangGraph agents, MCP tool calling, and RAG knowledge bases to cover functional, API, and UI (Playwright-based) automated testing.

## Use cases
- generate test cases from requirement documents with ai
- manage functional test cases with mind map view
- automate api testing with ai-generated assertions
- run ui automation tests with playwright
- build a rag knowledge base of product docs for test generation
- chat with an ai agent to analyze requirements and call test tools
- track automated test task execution and failure analysis

## When to choose
- your QA team wants AI-assisted test case generation and management in one platform
- you need combined functional, API, and UI automation with AI analysis of failures
- you want a self-hosted test platform with LLM, MCP, and knowledge base integration

## When to avoid
- you need a fully hardened public-facing service - the Skills module has high system privileges and public deployment is discouraged
- you only need simple unit testing or CI test runners without AI features
- you require a permissively licensed solution - the license is non-standard (NOASSERTION)

## Facets
- artifact type: application
- maturity: active
- function: testing, e2e-testing, rag, agent-framework, mcp, llm-inference, web-framework, chatbot
- domain: testing, artificial-intelligence, large-language-models, web-development, developer-tools, self-hosted
- platform: python, self-hosted, browser
- tags: test-case-generation, ai-testing, test-management, ui-automation, api-testing, playwright, langchain, langgraph, django, vue, requirements-management, knowledge-base, automation, retrieval-augmented-generation, docker, web-server

## Member repositories
- MGdaasLab/WHartTest (main) score 83

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:13.726269+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:11:37.390706+00:00, confidence not recorded.
  - readme: https://github.com/MGdaasLab/WHartTest (fetched 2026-08-28T04:03:13.726269+00:00, sha 29cc57f77367)
  - homepage: https://wharttest.mgdaas.com/ (fetched 2026-08-29T13:11:04.821732+00:00, sha 5306c385d1e7)
- Data as of 2026-08-30T08:39:29.467469+00:00.