Best AI tools for< Debug Test Scripts >

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 users do. Octomind uses AI agents to analyze web apps, generate test cases, execute tests, and provide debugging details. It aims to reinvent end-to-end testing with AI by offering features like auto-discovering what to test, generating tests automatically, running tests to find bugs, debugging apps, and auto-maintenance. Octomind is built on top of Playwright and offers stability, speed, and a better developer experience for testing web apps.

LambdaTest is a next-generation mobile apps and cross-browser testing cloud platform that offers a wide range of testing services. It allows users to perform manual live-interactive cross-browser testing, run Selenium, Cypress, Playwright scripts on cloud-based infrastructure, and execute AI-powered automation testing. The platform also provides accessibility testing, real devices cloud, visual regression cloud, and AI-powered test analytics. LambdaTest is trusted by over 2 million users globally and offers a unified digital experience testing cloud to accelerate go-to-market strategies.

Testsigma is a cloud-based test automation platform that enables teams to create, execute, and maintain automated tests for web, mobile, and API applications. It offers a range of features including natural language processing (NLP)-based scripting, record-and-playback capabilities, data-driven testing, and AI-driven test maintenance. Testsigma integrates with popular CI/CD tools and provides a marketplace for add-ons and extensions. It is designed to simplify and accelerate the test automation process, making it accessible to testers of all skill levels.

Symflower is an AI-powered unit test generator for Java applications. It helps developers write and maintain test code with ease, saving time and improving code quality. Symflower works with JUnit 4 and JUnit 5 for Java, Spring, and Spring Boot applications.

Snaplet is a data management tool for developers that provides AI-generated dummy data for local development, end-to-end testing, and debugging. It uses a real programming language (TypeScript) to define and edit data, ensuring type safety and auto-completion. Snaplet understands database structures and relationships, automatically transforming personally identifiable information and seeding data accordingly. It integrates seamlessly into development workflows, providing data where it's needed most: on local machines, for CI/CD testing, and preview environments.

Plumb is a no-code, node-based builder that empowers product, design, and engineering teams to create AI features together. It enables users to build, test, and deploy AI features with confidence, fostering collaboration across different disciplines. With Plumb, teams can ship prototypes directly to production, ensuring that the best prompts from the playground are the exact versions that go to production. It goes beyond automation, allowing users to build complex multi-tenant pipelines, transform data, and leverage validated JSON schema to create reliable, high-quality AI features that deliver real value to users. Plumb also makes it easy to compare prompt and model performance, enabling users to spot degradations, debug them, and ship fixes quickly. It is designed for SaaS teams, helping ambitious product teams collaborate to deliver state-of-the-art AI-powered experiences to their users at scale.

Reprompt is a prompt testing tool designed to help developers save time and make data-driven decisions about their prompts. It enables users to analyze more data in less time, easily identify anomalies, and speed up debugging by testing multiple scenarios at once. With Reprompt, users can have confidence in their changes by comparing with previous versions. The tool also offers real-time trading, < 1 sec operations, no commissions, built-in enterprise encryption and security, 256-bit AES encryption, and advanced security standards.

UpTrain is a full-stack LLMOps platform designed to help users with all their production needs, from evaluation to experimentation to improvement. It offers diverse evaluations, automated regression testing, enriched datasets, and precision metrics to enhance the development of LLM applications. UpTrain is built for developers, by developers, and is compliant with data governance needs. It provides cost efficiency, reliability, and open-source core evaluation framework. The platform is suitable for developers, product managers, and business leaders looking to enhance their LLM applications.

TestDriver is an AI-powered testing tool that helps developers automate their testing process. It can be integrated with GitHub and can test anything, right in the GitHub environment. TestDriver is easy to set up and use, and it can help developers save time and effort by offloading testing to AI. It uses Dashcam.io technology to provide end-to-end exploratory testing, allowing developers to see the screen, logs, and thought process as the AI completes its test.

Elixir is an AI tool designed for observability and testing of AI voice agents. It offers features such as automated testing, call review, monitoring, analytics, tracing, scoring, and reviewing. Elixir helps in simulating realistic test calls, analyzing conversations, identifying mistakes, and debugging issues with audio snippets and call transcripts. It provides detailed traces for complex abstractions, streamlines manual review processes, and allows for simulating thousands of calls for full test coverage. The tool is suitable for monitoring agent performance, detecting anomalies in real-time, and improving conversational systems through human-in-the-loop feedback.

Cognition is an applied AI lab focused on reasoning. Their first product, Devin, is the first AI software engineer. Cognition is a small team based in New York and the San Francisco Bay Area.

PseudoEditor is a free, fast, and online pseudocode IDE/editor designed to assist users in writing and debugging pseudocode efficiently. It offers dynamic syntax highlighting, code saving, error highlighting, and a pseudocode compiler feature. The platform aims to provide a smoother and faster writing environment for creating algorithms, resulting in up to 5x faster pseudocode writing compared to traditional programs like notepad. PseudoEditor is the first and only browser-based pseudocode editor/IDE available for free, supported by ads to cover hosting costs.

AICommit is an AI-powered programming assistant for JetBrains IDEs. It is based on OpenAI GPT and provides a range of intelligent coding features, including automated commit message generation, code optimization, code interpretation, documentation generation, code conversion, and translation. AICommit can help you make your coding process more efficient and convenient.

GitHub Next is a research and development team at GitHub that explores the future of software development. The team prototypes tools and technologies that will change the way we build software, and identifies new approaches to building healthy, productive software engineering teams.

aiXcoder is an innovative, intelligent programming robot product. It is provided as a "virtual programming expert" trained with professional code from various fields. Through pair programming with aiXcoder, programmers will feel significant improvements in working efficiency. With the help of aiXcoder, programmers will shake off the traditional "word-by-word" programming operation. aiXcoder could predict programmers' intentions intelligently and complete "the following code snaps" automatically. Programmers just need to confirm the generated code by one button click. Thus, it could improve coding efficiency dramatically.

CodeCompanion.AI is an AI-powered coding companion that helps developers write better code. It provides real-time feedback, suggestions, and documentation, and can even generate code for you. CodeCompanion.AI is designed to make coding faster, easier, and more efficient.

Stately is a visual logic builder that enables users to create complex logic diagrams and code in minutes. It provides a drag-and-drop editor that brings together contributors of all backgrounds, allowing them to collaborate on code, diagrams, documentation, and test generation in one place. Stately also integrates with AI to assist in each phase of the development process, from scaffolding behavior and suggesting variants to turning up edge cases and even writing code. Additionally, Stately offers bidirectional updates between code and visualization, allowing users to use the tools that make them most productive. It also provides integrations with popular frameworks such as React, Vue, and Svelte, and supports event-driven programming, state machines, statecharts, and the actor model for handling even the most complex logic in predictable, robust, and visual ways.

Pythagora is an AI-powered development tool that revolutionizes software development by enabling users to build apps from scratch through natural language communication. It works seamlessly with developers to break down app specifications, select technologies, create project architecture, write code, test, deploy, and more. Pythagora is a VS Code extension powered by GPT Pilot and GPT-4, offering features like code generation, error reading, debugging, version control, and automated testing. With Pythagora, users can create production-ready, modular code without the need for extensive documentation, making software development faster and more efficient.

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.

Refraction is an AI-powered code generation tool designed to help developers learn, improve, and generate code effortlessly. It offers a wide range of features such as bug detection, code conversion, function creation, CSP generation, CSS style conversion, debug statement addition, diagram generation, documentation creation, code explanation, code improvement, concept learning, CI/CD pipeline creation, SQL query generation, code refactoring, regex generation, style checking, type addition, and unit test generation. With support for 56 programming languages, Refraction is a versatile tool trusted by innovative companies worldwide to streamline software development processes using the magic of AI.

Auto Playwright is a tool that allows users to run Playwright tests using AI. It eliminates the need for selectors by determining actions at runtime based on plain-text instructions. Users can automate complex scenarios, write tests concurrently with or before functionality development, and benefit from rapid test creation. The tool supports various Playwright actions and offers additional options for debugging and customization. It uses HTML sanitization to reduce costs and improve text quality when interacting with the OpenAI API.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

AskUI is a reliable, automated end-to-end automation tool that only depends on what is shown on your screen instead of the technology or platform you are running on.

GPT Home is a project that allows users to build their own home assistant using Raspberry Pi and OpenAI API. It serves as a guide for setting up a smart home assistant similar to Google Nest Hub or Amazon Alexa. The project integrates various components like OpenAI, Spotify, Philips Hue, and OpenWeatherMap to provide a personalized home assistant experience. Users can follow the detailed instructions provided to build their own version of the home assistant on Raspberry Pi, with optional components for customization. The project also includes system configurations, dependencies installation, and setup scripts for easy deployment. Overall, GPT Home offers a DIY solution for creating a smart home assistant using Raspberry Pi and OpenAI technology.

AI Town is a virtual town where AI characters live, chat, and socialize. This project provides a deployable starter kit for building and customizing your own version of AI Town. It features a game engine, database, vector search, auth, text model, deployment, pixel art generation, background music generation, and local inference. You can customize your own simulation by creating characters and stories, updating spritesheets, changing the background, and modifying the background music.

This repository provides a comprehensive collection of methodologies, tools, and step-by-step instructions for successful training of large language models (LLMs) and multi-modal models. It is a technical resource suitable for LLM/VLM training engineers and operators, containing numerous scripts and copy-n-paste commands to facilitate quick problem-solving. The repository is an ongoing compilation of the author's experiences training BLOOM-176B and IDEFICS-80B models, and currently focuses on the development and training of Retrieval Augmented Generation (RAG) models at Contextual.AI. The content is organized into six parts: Insights, Hardware, Orchestration, Training, Development, and Miscellaneous. It includes key comparison tables for high-end accelerators and networks, as well as shortcuts to frequently needed tools and guides. The repository is open to contributions and discussions, and is licensed under Attribution-ShareAlike 4.0 International.

Alan AI SDK for iOS is a powerful tool that allows developers to quickly create AI agents for their iOS apps. With Alan AI Platform, users can easily design, embed, and host conversational experiences in their applications. The platform offers a web-based IDE called Alan AI Studio for creating dialog scenarios, lightweight SDKs for embedding AI agents, and a backend powered by top-notch speech recognition and natural language understanding technologies. Alan AI enables human-like conversations and actions through voice commands, with features like on-the-fly updates, dialog flow testing, and analytics.

Alan AI is a comprehensive AI solution that acts as a 'unified brain' for enterprises, interconnecting applications, APIs, and data sources to streamline workflows. It offers tools like Alan AI Studio for designing dialog scenarios, lightweight SDKs for embedding AI Agents, and a backend powered by advanced AI technologies. With Alan AI, users can create conversational experiences with minimal UI changes, benefit from a serverless environment, receive on-the-fly updates, and access dialog testing and analytics tools. The platform supports various frameworks like JavaScript, React, Angular, Vue, Ember, and Electron, and provides example web apps for different platforms. Users can also explore Alan AI SDKs for iOS, Android, Flutter, Ionic, Apache Cordova, and React Native.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

Tools4AI is a Java-based Agentic Framework for building AI agents to integrate with enterprise Java applications. It enables the conversion of natural language prompts into actionable behaviors, streamlining user interactions with complex systems. By leveraging AI capabilities, it enhances productivity and innovation across diverse applications. The framework allows for seamless integration of AI with various systems, such as customer service applications, to interpret user requests, trigger actions, and streamline workflows. Prompt prediction anticipates user actions based on input prompts, enhancing user experience by proactively suggesting relevant actions or services based on context.

CodiumAI Cover Agent is a tool designed to help increase code coverage by automatically generating qualified tests to enhance existing test suites. It utilizes Generative AI to streamline development workflows and is part of a suite of utilities aimed at automating the creation of unit tests for software projects. The system includes components like Test Runner, Coverage Parser, Prompt Builder, and AI Caller to simplify and expedite the testing process, ensuring high-quality software development. Cover Agent can be run via a terminal and is planned to be integrated into popular CI platforms. The tool outputs debug files locally, such as generated_prompt.md, run.log, and test_results.html, providing detailed information on generated tests and their status. It supports multiple LLMs and allows users to specify the model to use for test generation.

Elyra is a set of AI-centric extensions to JupyterLab Notebooks that includes features like Visual Pipeline Editor, running notebooks/scripts as batch jobs, reusable code snippets, hybrid runtime support, script editors with execution capabilities, debugger, version control using Git, and more. It provides a comprehensive environment for data scientists and AI practitioners to develop, test, and deploy machine learning models and workflows efficiently.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

UNav-Sim is an open-source underwater robotics simulator tool that leverages the power of Unreal Engine 5 (UE5) and AirSim to provide highly detailed rendering and simulation capabilities. With UNav-Sim, you can explore underwater terrains, design and test autonomous underwater vehicles (AUVs), and accelerate your learning and experimentation process in the field of underwater robotics.

HuggingFists is a low-code data flow tool that enables convenient use of LLM and HuggingFace models. It provides functionalities similar to Langchain, allowing users to design, debug, and manage data processing workflows, create and schedule workflow jobs, manage resources environment, and handle various data artifact resources. The tool also offers account management for users, allowing centralized management of data source accounts and API accounts. Users can access Hugging Face models through the Inference API or locally deployed models, as well as datasets on Hugging Face. HuggingFists supports breakpoint debugging, branch selection, function calls, workflow variables, and more to assist users in developing complex data processing workflows.

This repository contains code and configurations for the LLM - Detect AI Generated Text competition. It includes setup instructions for hardware, software, dependencies, and datasets. The training section covers scripts and configurations for training LLM models, DeBERTa ranking models, and an embedding model. Text generation section details fine-tuning LLMs using the CLM objective on the PERSUADE corpus to generate student-like essays.

The vscode-pddl extension provides comprehensive support for Planning Domain Description Language (PDDL) in Visual Studio Code. It enables users to model planning domains, validate them, industrialize planning solutions, and run planners. The extension offers features like syntax highlighting, auto-completion, plan visualization, plan validation, plan happenings evaluation, search debugging, and integration with Planning.Domains. Users can create PDDL files, run planners, visualize plans, and debug search algorithms efficiently within VS Code.

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