Best AI tools for< Run Tests Locally >

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Momentic is an AI testing tool that offers automated AI testing for software applications. It streamlines regression testing, production monitoring, and UI automation, making test automation easy with its AI capabilities. Momentic is designed to be simple to set up, easy to maintain, and accelerates team productivity by creating and deploying tests faster with its intuitive low-code editor. The tool adapts to applications, saves time with automated test maintenance, and allows testing anywhere, anytime using cloud, local, or CI/CD pipelines.

Momentic is a purpose-built AI tool for modern software testing, offering automation for E2E, UI, API, and accessibility testing. It leverages AI to streamline testing processes, from element identification to test generation, helping users shorten development cycles and enhance productivity. With an intuitive editor and the ability to describe elements in plain English, Momentic simplifies test creation and execution. It supports local testing without the need for a public URL, smart waiting for in-flight requests, and integration with CI/CD pipelines. Momentic is trusted by numerous companies for its efficiency in writing and maintaining end-to-end tests.

Octomind is an AI-powered Playwright end-to-end testing tool for web applications. It automatically discovers, generates, and runs tests to find bugs before customers do. With features like auto-generating tests, running tests to find bugs, maintaining tests automatically, debugging apps, and not requiring code access, Octomind offers a seamless testing experience for developers. It provides real-world wins with testimonials from industry professionals and ensures stability, speed, and a better developer experience.

Carbonate is an AI-driven automated end-to-end testing tool that allows users to create auto-healing browser tests without any coding. By leveraging its unique AI engine, Carbonate generates test scripts from recorded tests, enabling users to run tests using a cloud test runner or within their own CI. With Carbonate, users can create tests in seconds by simply using their application, as the tool automatically detects interactions and records them as part of the test. Carbonate's intelligent AI recorder ensures that tests heal themselves and adapt to changes in the application, providing fast results without the hassle.

Langtail is a platform that helps developers build, test, and deploy AI-powered applications. It provides a suite of tools to help developers debug prompts, run tests, and monitor the performance of their AI models. Langtail also offers a community forum where developers can share tips and tricks, and get help from other users.

UserTesting is a Human Insight Platform that allows organizations to quickly gain a first-person understanding of customer experiences, enabling them to build greater customer empathy. The platform offers comprehensive testing capabilities, insights identification, performance measurement, and insights sharing across organizations. UserTesting empowers users to run tests for free, see what customers experience, and turn feedback into better designs efficiently. With features like AI Insights Hub, integrations, mobile testing, and templates, UserTesting helps users target diverse audiences, validate findings confidently, measure and benchmark performance, and boost consumer trust. Trusted by leading brands, UserTesting provides human insights that drive innovation, improve customer experiences, and enhance product development.

Sofy is a revolutionary no-code testing platform for mobile applications that integrates AI to streamline the testing process. It offers features such as manual and ad-hoc testing, no-code automation, AI-powered test case generation, and real device testing. Sofy helps app development teams achieve high-quality releases by simplifying test maintenance and ensuring continuous precision. With a focus on efficiency and user experience, Sofy is trusted by top industries for its all-in-one testing solution.

Rainforest QA is an AI-powered test automation platform designed for SaaS startups to streamline and accelerate their testing processes. It offers AI-accelerated testing, no-code test automation, and expert QA services to help teams achieve reliable test coverage and faster release cycles. Rainforest QA's platform integrates with popular tools, provides detailed insights for easy debugging, and ensures visual-first testing for a seamless user experience. With a focus on automating end-to-end tests, Rainforest QA aims to eliminate QA bottlenecks and help teams ship bug-free code with confidence.

QA Wolf is an AI-native service that delivers 80% automated end-to-end test coverage for web and mobile apps in weeks, not years. It automates hundreds of tests using Playwright code for web and Appium for mobile, providing reliable test results on every run. With features like 100% parallel run infrastructure, zero flake guarantee, and unlimited test runs, QA Wolf aims to help software teams ship better software faster by taking QA completely off their plate.

PromptPoint Playground is an AI tool designed to help users design, test, and deploy prompts quickly and efficiently. It enables teams to create high-quality LLM outputs through automatic testing and evaluation. The platform allows users to make non-deterministic prompts predictable, organize prompt configurations, run automated tests, and monitor usage. With a focus on collaboration and accessibility, PromptPoint Playground empowers both technical and non-technical users to leverage the power of large language models for prompt engineering.

OptiMonk is a conversion optimization toolset tailored for busy marketers, empowering you to boost sales through website personalization, popups and A/B testing. It offers a range of features including pre-designed templates, actionable CRO tactics, and integrations with popular marketing tools. OptiMonk's AI-powered capabilities enable users to create personalized popups, product descriptions, and A/B tests to maximize conversions.

CroPilot is an AI-powered website optimization tool that helps businesses increase conversions and improve user experience. It offers a range of features including audience targeting, goal-oriented optimization, AI-driven insights, heatmap analysis, automated analytics reporting, and A/B testing. CroPilot is easy to use and integrates seamlessly with popular platforms like WordPress, WooCommerce, and Shopify. It is suitable for businesses of all sizes and can complement existing optimization tools.

More Views AI is an AI tool designed to help YouTube content creators increase their view count by testing different video settings. The tool uses artificial intelligence to analyze video titles, suggest variations, and run A/B tests to determine the best-performing title. It offers features such as automatic A/B toggling, performance tracking, views optimization, AI-generated title suggestions, and thumbnail testing. Users can connect their YouTube account, set up experiments in seconds, and let the algorithm optimize their video titles to attract more views.

Reflect is an AI-powered test automation tool that revolutionizes the way end-to-end tests are created, executed, and maintained. By leveraging Generative AI, Reflect eliminates the need for manual coding and provides a seamless testing experience. The tool offers features such as no-code test automation, visual testing, API testing, cross-browser testing, and more. Reflect aims to help companies increase software quality by accelerating testing processes and ensuring test adaptability over time.

Functionize is an AI-powered test automation platform that helps enterprises improve their product quality and release faster. It uses machine learning to automate test creation, maintenance, and execution, and provides a range of features to help teams collaborate and manage their testing process. Functionize integrates with popular CI/CD tools and DevOps pipelines, and offers a range of pricing options to suit different needs.

HowsThisGoing is an AI-powered application designed to streamline team communication and productivity by enabling users to set up standups in Slack within seconds. The platform offers features such as automatic standups, AI summaries, custom tests, analytics & reporting, and workflow scheduling. Users can easily create workflows, generate AI reports, and track team performance efficiently. HowsThisGoing provides unlimited benefits at a flat price, making it a cost-effective solution for teams of all sizes.

Robin by Mobile.dev is an AI-powered mobile app testing tool that allows users to test their mobile apps with confidence. It offers a simple yet powerful open-source framework called Maestro for testing mobile apps at high speed. With intuitive and reliable testing powered by AI, users can write rock-solid tests without extensive coding knowledge. Robin provides an end-to-end testing strategy, rapid testing across various devices and operating systems, and auto-healing of test flows using state-of-the-art AI models.

SWE Kit is an open-source headless IDE designed for building custom coding agents with state-of-the-art performance. It offers AI-native tools to streamline the coding review process, enhance code quality, and optimize development efficiency. The application supports various agentic frameworks and LLM inference providers, providing a flexible runtime environment for seamless codebase interaction. With features like code analysis, code indexing, and third-party service integrations, SWE Kit empowers developers to create and run coding agents effortlessly.

The website is a comprehensive resource hub for learning and mastering end-to-end testing using the Playwright automation framework. It offers a variety of content such as blog posts, tutorials, videos, and a QA Wiki with definitions of common testing terms. Users can also ask questions related to Playwright and access a Discord forum for discussions. Additionally, there is a browser extension available for generating Playwright locators, and a section dedicated to QA jobs and automation opportunities.

Shortest is an AI-powered natural language end-to-end testing framework built on Playwright. It provides a seamless testing experience by allowing users to write tests in natural language and execute them using Anthropic Claude API. The framework also offers GitHub integration with 2FA support, making it suitable for testing web applications with complex authentication flows. Shortest simplifies the testing process by enabling users to run tests locally or in CI/CD pipelines, ensuring the reliability and efficiency of web applications.

Shortest is a project for local development that helps set up environment variables and services for a web application. It provides a guide for setting up Node.js and pnpm dependencies, configuring services like Clerk, Vercel Postgres, Anthropic, Stripe, and GitHub OAuth, and running the application and tests locally.

An LLM-powered code generation tool that relies on the built-in Node.js API Typescript Template Project to easily generate clean, well-structured CRUD module code from text description. It orchestrates 3 LLM micro-agents (`Developer`, `Troubleshooter` and `TestsFixer`) to generate code, fix compilation errors, and ensure passing E2E tests. The process includes module code generation, DB migration creation, seeding data, and running tests to validate output. By cycling through these steps, it guarantees consistent and production-ready CRUD code aligned with vertical slicing architecture.

The Neo4j GraphRAG package for Python is an official repository that provides features for creating and managing vector indexes in Neo4j databases. It aims to offer developers a reliable package with long-term commitment, maintenance, and fast feature updates. The package supports various Python versions and includes functionalities for creating vector indexes, populating them, and performing similarity searches. It also provides guidelines for installation, examples, and development processes such as installing dependencies, making changes, and running tests.

LitServe is a high-throughput serving engine for deploying AI models at scale. It generates an API endpoint for a model, handles batching, streaming, autoscaling across CPU/GPUs, and more. Built for enterprise scale, it supports every framework like PyTorch, JAX, Tensorflow, and more. LitServe is designed to let users focus on model performance, not the serving boilerplate. It is like PyTorch Lightning for model serving but with broader framework support and scalability.

Polaris establishes a novel, industry‑certified standard to foster the development of impactful methods in AI-based drug discovery. This library is a Python client to interact with the Polaris Hub. It allows you to download Polaris datasets and benchmarks, evaluate a custom method against a Polaris benchmark, and create and upload new datasets and benchmarks.

Scylla is an intelligent proxy pool tool designed for humanities, enabling users to extract content from the internet and build their own Large Language Models in the AI era. It features automatic proxy IP crawling and validation, an easy-to-use JSON API, a simple web-based user interface, HTTP forward proxy server, Scrapy and requests integration, and headless browser crawling. Users can start using Scylla with just one command, making it a versatile tool for various web scraping and content extraction tasks.

Momentum is an open-source behavioral auditor for backend code that helps developers generate powerful insights into their codebase. It analyzes code behavior, tests it at every git push, and ensures readiness for production. Momentum understands backend code, visualizes dependencies, identifies behaviors, generates test code, runs code in the local environment, and provides debugging solutions. It aims to improve code quality, streamline testing processes, and enhance developer productivity.

Aio-pika is a wrapper around aiormq for asyncio and humans. It provides a completely asynchronous API, object-oriented API, transparent auto-reconnects with complete state recovery, Python 3.7+ compatibility, transparent publisher confirms support, transactions support, and complete type-hints coverage.

Instructor is a popular Python library for managing structured outputs from large language models (LLMs). It offers a user-friendly API for validation, retries, and streaming responses. With support for various LLM providers and multiple languages, Instructor simplifies working with LLM outputs. The library includes features like response models, retry management, validation, streaming support, and flexible backends. It also provides hooks for logging and monitoring LLM interactions, and supports integration with Anthropic, Cohere, Gemini, Litellm, and Google AI models. Instructor facilitates tasks such as extracting user data from natural language, creating fine-tuned models, managing uploaded files, and monitoring usage of OpenAI models.

Empirical is a tool that allows you to test different LLMs, prompts, and other model configurations across all the scenarios that matter for your application. With Empirical, you can run your test datasets locally against off-the-shelf models, test your own custom models and RAG applications, view, compare, and analyze outputs on a web UI, score your outputs with scoring functions, and run tests on CI/CD.

JetStream is a throughput and memory optimized engine for Large Language Model (LLM) inference on XLA devices, specifically TPUs. It provides reference engine implementations for Jax and Pytorch models, along with documentation for online inference, serving Gemma using TPUs on GKE, benchmarking, observability, profiling, and standalone local setup. Users can easily set up a local server, run tests, and test core modules. JetStream aims to enhance the performance of LLM inference on XLA devices.

Kwaak is a tool that allows users to run a team of autonomous AI agents locally from their own machine. It enables users to write code, improve test coverage, update documentation, and enhance code quality while focusing on building innovative projects. Kwaak is designed to run multiple agents in parallel, interact with codebases, answer questions about code, find examples, write and execute code, create pull requests, and more. It is free and open-source, allowing users to bring their own API keys or models via Ollama. Kwaak is part of the bosun.ai project, aiming to be a platform for autonomous code improvement.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MFLUX is a line-by-line port of the FLUX implementation in the Huggingface Diffusers library to Apple MLX. It aims to run powerful FLUX models from Black Forest Labs locally on Mac machines. The codebase is minimal and explicit, prioritizing readability over generality and performance. Models are implemented from scratch in MLX, with tokenizers from the Huggingface Transformers library. Dependencies include Numpy and Pillow for image post-processing. Installation can be done using `uv tool` or classic virtual environment setup. Command-line arguments allow for image generation with specified models, prompts, and optional parameters. Quantization options for speed and memory reduction are available. LoRA adapters can be loaded for fine-tuning image generation. Controlnet support provides more control over image generation with reference images. Current limitations include generating images one by one, lack of support for negative prompts, and some LoRA adapters not working.

Promptwright is a Python library designed for generating large synthetic datasets using a local LLM and various LLM service providers. It offers flexible interfaces for generating prompt-led synthetic datasets. The library supports multiple providers, configurable instructions and prompts, YAML configuration for tasks, command line interface for running tasks, push to Hugging Face Hub for dataset upload, and system message control. Users can define generation tasks using YAML configuration or Python code. Promptwright integrates with LiteLLM to interface with LLM providers and supports automatic dataset upload to Hugging Face Hub.

AgentKit is a framework for creating and orchestrating AI Agents, enabling developers to build, test, and deploy reliable AI applications at scale. It allows for creating networked agents with separate tasks and instructions to solve specific tasks, as well as simple agents for tasks like writing content. The framework requires the Inngest TypeScript SDK as a dependency and provides documentation on agents, tools, network, state, and routing. Example projects showcase AgentKit in action, such as the Test Writing Network demo using Workflow Kit, Supabase, and OpenAI.

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