Ross ROSS = Recommend OSS · open-source software intelligence for agents

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.) observed · 2026-08-28

github.com/MGdaasLab/WHartTest · homepage · Python · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

83/100

  • Activity 98
  • Release rhythm 98
  • Longevity 25

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 10
  • age_days: 352
  • days_rel: 13
  • days_push: 13
  • n_releases_24m: 20

Full methodology

Adoption not part of the score

1013 stars · 159 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

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

application · maturity active

testing e2e-testing rag agent-framework mcp llm-inference web-framework chatbot testing artificial-intelligence large-language-models web-development developer-tools self-hosted python self-hosted browser 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

2 sources

Member repositories

RepositoryRoleHealth v2
MGdaasLab/WHartTestmain83

For agents

markdown · JSON · MCP: product_card(name="MGdaasLab/WHartTest")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem