TestPilot is a tool for automatically generating unit tests for npm packages written in JavaScript/TypeScript using a large language model (LLM).
Note that TestPilot represents an early exploration in the use of LLMs for test generation, and has been made available in open source as a basis for research and exploration. For day-to-day use the test generation features in Copilot Chat are likely to yield better results.
TestPilot generates tests for a given function f
by prompting the LLM with a
skeleton of a test for f
, including information about f
embedded in code
comments, such as its signature, the body of f
, and examples usages of f
automatically mined from project documentation. The model's response is then
parsed and translated into a runnable unit test. Optionally, the test is run and
if it fails the model is prompted again with additional information about the
failed test, giving it a chance to refine the test.
Unlike other systems for LLM-based test generation, TestPilot does not require any additional training or reinforcement learning, and no examples of functions and their associated tests are needed.
A research paper describing TestPilot in detail is available on arXiv and IEEExplore.
In general, to be able to run TestPilot you need access to a Codex-style LLM
with completion API. Set the TESTPILOT_LLM_API_ENDPOINT
environment variable to
the URL of the LLM API endpoint you want to use, and
TESTPILOT_LLM_AUTH_HEADERS
to a JSON object containing the headers you need to
authenticate with the API.
Typical values for these variables might be:
TESTPILOT_LLM_API_ENDPOINT='https://api.openai.com/v1/engines/code-cushman-001/completions'
TESTPILOT_LLM_AUTH_HEADERS='{"Authorization": "Bearer <your API key>", "OpenAI-Organization": "<your organization ID>"}'
Note, however, that you can run TestPilot in reproduction mode without access to the LLM API where model responses are taken from the output of a previous run; see below for details.
You can install TestPilot from a pre-built package or from source.
TestPilot is a available as a pre-built npm package, though it is not currently published to the npm registry. You can download a tarball from the repository and install it in the usual way. Note that this distribution only contains the core part of TestPilot, not the benchmarking harness.
The src/
directory contains the source code for TestPilot, which is written in
TypeScript and gets compiled into the dist/
directory. Tests are in test/
;
the benchmark/
directory contains a benchmarking harness for running TestPilot
on multiple npm packages; and ql/
contains the CodeQL queries used to analyze
the results.
In the root directory of a checkout of this repository, run npm build
to
install dependencies and build the package.
You can also use npm run build:watch
to automatically build anytime you make
changes to the code. Note, however, that this will not automatically install
dependencies, and also will not build the benchmarking harness.
Use npm run test
to run the tests. For convenience, this will also install
dependencies and run a build.
If you install TestPilot from source, you can use the benchmarking harness to run TestPilot on multiple packages and analyze the results. This is not currently available if you install TestPilot from a pre-built package.
Basic usage is as follows:
node benchmark/run.js --outputDir <report_dir> --package <package_dir>
This generates tests for all functions exported by the package in
<package_dir>
, validates them, and writes the results to <report_dir>
.
Note that this assumes that package dependencies are installed and any build
steps have been run (e.g., using npm i
and npm run build
). TestPilot also
relies on mocha
, so if the package under test does not already depend on it,
you must install it separately, for example using the command npm i --no-save mocha
.
The run-experiment.yml
workflow runs an experiment on GitHub Actions,
producing the final report as an artifact you can download. The results-all
artifact contains the results of all packages, while the other artifacts contain
the individual results of each package.
The results of TestPilot are non-deterministic, so even if you run it from the same package on the same machine multiple times, you will get different results. However, the benchmarking harness records enough data to be able to replay a benchmark run in many cases.
To do this, use the --api
and --responses
options to reuse the API listings
and responses from a previous run:
node benchmark/run.js --outputDir <report_dir> --package <package_dir> --api <api.json> --responses <prompts.json>
Note that by default replay will fail if any of the prompts are not found in the responses file. This typically happens if TestPilot is refining failing tests, since in this case the prompt to the model depends on the exact failure message, which can be system-specific (e.g., containing local file-system paths), or depend on the Node.js version or other factors.
To work around these limitations, you can pass the --strictResponses false
flag handle treat missing prompts by treating them as getting no response from
the model. This will not, in general, produce the same results as the initial
run, but suffices in many cases.
The CodeQL queries in ql/queries
can be used to analyze the results of running
an experiment. See ql/CodeQL.md
for instructions on how to setup CodeQL and
run the queries.
This project is licensed under the terms of the MIT open source license. Please refer to MIT for the full terms.
TestPilot is a research prototype and is not officially supported. However, if you have questions or feedback, please file an issue and we will do our best to respond.
We thank Aryaz Eghbali (@aryaze) for his work on the initial version of TestPilot.
字节跳动发布的AI编程神器IDE
Trae是一种自适应的集成开发环境(IDE),通过自动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。
全能AI智能助手,随时解答生活与工作的多样问题
问小白,由元石科技研发的AI智能助手,快速准确地解答各种生活和工作问题,包括但不限于搜索、规划和社交互动,帮助用户在日常生活中提高效率,轻松管理个人事务。
实时语音翻译/同声传译工具
Transly是一个多场景的AI大语言模型驱动的同声传译、专业翻译助手,它拥有超精准的音频识别翻译能力,几乎零延迟的使用体验和支持多国语言可以让你带它走遍全球,无论你是留学生、商务人士、韩剧美剧爱好者,还是出国游玩、多国会议、跨国追星等等,都可以满足你所有需要同传的场景需求,线上线下通用,扫除语言障碍,让全世界的语言交流不再有国界。
一键生成PPT和Word,让学习生活更轻松
讯飞智文是一个利用 AI 技术的项目,能够帮助用户生成 PPT 以及各类文档。无论是商业领域的市场分析报告、年度目标制定,还是学生群体的职业生涯规划、实习避坑指南,亦或是活动策划、旅游攻略等内容,它都能提供支持,帮助用户精准表达,轻松呈现各种信息。
深度推理能力全新升级,全面对标OpenAI o1
科大讯飞的星火大模型,支持语言理解、知识问答和文本创作等多功能,适用于多种文件和业务场景,提升办公和日常生活的效率。讯飞星火是一个提供丰富智能服务的平台,涵盖科技资讯、图像创作、写作辅助、编程解答、科研文献解读等功能,能为不同需求的用户提供便捷高效的帮助,助力用户轻松获取信息、解决问题,满足多样化使用场景。
一种基于大语言模型的高效单流解耦语音令牌文本到语音合成模型
Spark-TTS 是一个基于 PyTorch 的开源文本到语音合成项目,由多个知名机构联合参与。该项目提供了高效的 LLM(大语言模型)驱动的语音合成方案,支持语音克隆和语音创建功能,可通过命令行界面(CLI)和 Web UI 两种方式使用。用户可以根据需求调整语音的性别、音高、速度等参数,生成高质量的语音。该项目适用于多种场景,如有声读物制作、智能语音助手开发等。
AI助力,做PPT更简单!
咔片是一款轻量化在线演示设计工具,借助 AI 技术,实现从内容生成到智能设计的一站式 PPT 制作服务。支持多种文档格式导入生成 PPT,提供海量模板、智能美化、素材替换等功能,适用于销售、教师、学生等各类人群,能高效制作出高品质 PPT,满足不同场景演示需求。
选题、配图、成文,一站式创作,让内容运营更高效
讯飞绘文,一个AI集成平台,支持写作、选题、配图、排版和发布。高效生成适用于各类媒体的定制内容,加速品牌传播,提升内容营销效果。
专业的AI公文写作平台,公文写作神器
AI 材料星,专业的 AI 公文写作辅助平台,为体制内工作人员提供高效的公文写作解决方案。拥有海量公文文库、9 大核心 AI 功能,支持 30 + 文稿类型生成,助力快速完成领导讲话、工作总结、述职报告等材料,提升办公效率,是体制打工人的得力写作神器。
OpenAI Agents SDK,助力开发者便捷使用 OpenAI 相关功能。
openai-agents-python 是 OpenAI 推出的一款强大 Python SDK,它为开发者提供了与 OpenAI 模型交互的高效工具,支持工具调用、结果处理、追踪等功能,涵盖多种应用场景,如研究助手、财务研究等,能显著提升开发效率,让开发者更轻松地利用 OpenAI 的技术优势。
最新AI工具、AI资讯
独家AI资源、AI项目落地
微信扫一扫关注公众号