Best AI tools for< test data generation >

Syntho is a self-service AI-generated synthetic data platform that enables users to create realistic and privacy-preserving synthetic data for various applications, including testing, analytics, and data sharing. It offers a range of features such as AI-generated synthetic data, smart de-identification, test data management, and rule-based synthetic data generation. Syntho's synthetic data is assessed and approved by the data experts of SAS, ensuring high accuracy and quality.

Softbuilder is a software development company focused on creating innovative database tools. Their products include ERBuilder Data Modeler, AbstraLinx, and SB Data Generator. ERBuilder Data Modeler is an easy-to-use database modeling software for high-quality data models. AbstraLinx is a powerful metadata discovery tool for Salesforce. SB Data Generator is a simple and powerful tool to generate and populate selected tables or entire databases with realistic test data.

Keploy is an open-source API test case and data mock generation tool that uses AI to help developers write better tests. It can automatically generate test cases from user traffic, and it can also create realistic data mocks for testing purposes. Keploy integrates with popular testing frameworks like JUnit, go-test, py-test, and jest, and it can be used to test any type of API.

MOSTLY AI is a synthetic data generation platform that provides high-quality, privacy-safe synthetic versions of your datasets for ML, advanced analytics, software testing, and data sharing. With MOSTLY AI, you can generate synthetic data that is statistically similar to your real data, but without the privacy risks. This makes it possible to share data more freely, collaborate more effectively, and develop better AI models.

DataZenith is an AI application that leverages virtual reality (VR) technology to generate realistic and immersive datasets for training AI models. It enables the development of AI algorithms that can understand and interact with virtual environments, improving algorithm accuracy and performance in real-world scenarios. DataZenith offers user-friendly solutions for non-technical users, with features such as realistic VR data generation, addressing edge cases, user-friendly interface, customizable VR environments, and precise VR data annotations.

Fine-Tune AI is a tool that allows users to generate fine-tune data sets using prompts. This can be useful for a variety of tasks, such as improving the accuracy of machine learning models or creating new training data for AI applications.

Teste.ai is an AI-powered platform for creating software test scenarios and cases using top-notch artificial intelligence technology. It offers a comprehensive set of tools based on AI to accelerate the software quality testing journey. With Teste.ai, users can increase productivity, save time, and enhance test coverage by generating complete test plans, scenarios, and step-by-step instructions with just a single requirement or document snippet. The platform provides versatile testing capabilities, including API, Functional, Security, and Performance testing, along with advanced features like data generation, query building, and collaboration tools. Teste.ai leverages artificial intelligence to automate test case generation, improve test documentation, and ensure precise and relevant responses for testing queries.

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.

Magic Regex Generator is an AI-powered tool that simplifies the process of generating, testing, and editing Regular Expression patterns. Users can describe what they want to match in English, and the AI generates the corresponding regex in the editor for testing and refining. The tool is designed to make working with regex easier and more efficient, allowing users to focus on meaningful tasks without getting bogged down in complex pattern matching.

CodeAI is an AI-powered coding assistant that helps developers write better code faster. It uses artificial intelligence to generate code, write unit tests, and document code. CodeAI is designed to help developers of all levels, from beginners to experienced professionals. It is available as a VSCode extension and as a standalone application.

Bland is a platform for building AI phone calling applications at scale. With Bland, you can create phone agents that can automate any task, from lead generation to customer support. Bland's phone agents are powered by a state-of-the-art AI engine that can understand and respond to human speech in real time. This makes them ideal for a wide range of applications, including: - Inbound sales: Bland's phone agents can qualify leads, schedule appointments, and close deals. - Customer support: Bland's phone agents can answer customer questions, resolve issues, and collect feedback. - Data collection: Bland's phone agents can collect data from customers, prospects, and other sources. - Market research: Bland's phone agents can conduct surveys, gather feedback, and test new products and services.

Assessment Systems is an online testing platform that provides cost-effective, AI-driven solutions to develop, deliver, and analyze high-stakes exams. With Assessment Systems, you can build and deliver smarter exams faster, thanks to modern psychometrics and AI like computerized adaptive testing, multistage testing, or automated item generation. You can also deliver exams flexibly: paper, online testing unproctored, online proctored, and test centers (yours or ours). Assessment Systems also offers item banking software to build better tests in less time, with collaborative item development brought to life with versioning, user roles, metadata, workflow management, multimedia, automated item generation, and much more.

Replit is a software creation platform that provides an integrated development environment (IDE), artificial intelligence (AI) assistance, and deployment services. It allows users to build, test, and deploy software projects directly from their browser, without the need for local setup or configuration. Replit offers real-time collaboration, code generation, debugging, and autocompletion features powered by AI. It supports multiple programming languages and frameworks, making it suitable for a wide range of development projects.

GeniA is an open-source engineering Gen AI team member that can be embedded in your everyday and production environments. It is built with enterprise-grade engineering tools under the most challenging security standards and can be accessed right in your team's Slack channel. GeniA can assist with a variety of tasks, including code generation, debugging, and testing.

Confident AI is an open-source evaluation infrastructure for Large Language Models (LLMs). It provides a centralized platform to judge LLM applications, ensuring substantial benefits and addressing any weaknesses in LLM implementation. With Confident AI, companies can define ground truths to ensure their LLM is behaving as expected, evaluate performance against expected outputs to pinpoint areas for iterations, and utilize advanced diff tracking to guide towards the optimal LLM stack. The platform offers comprehensive analytics to identify areas of focus and features such as A/B testing, evaluation, output classification, reporting dashboard, dataset generation, and detailed monitoring to help productionize LLMs with confidence.

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.

Safurai is an AI-powered coding assistant that helps developers write code faster, safer, and better. It offers a range of features, including a textbox for asking questions and getting code suggestions, shortcuts for code optimization and unit testing, the ability to train the assistant on specific projects, and a natural language search for finding code. Safurai is compatible with various IDEs, including Visual Studio Code, IntelliJ, and PyCharm.

Bito AI is an AI-powered code review tool that helps developers write better code faster. It provides real-time feedback on code quality, security, and performance, and can also generate test cases and documentation. Bito AI is trusted by developers across the world, and has been shown to reduce review time by 50%.

Copilot is an AI-powered pair programming tool that helps developers write better code, faster. It suggests code completions, generates entire functions, and even helps refactor code. Copilot is powered by OpenAI's Codex, a large language model that has been trained on a massive dataset of code. Copilot is still in development, but it has already shown great promise for improving developer productivity.

Talk2APIs is a platform that allows developers to easily connect to and use APIs. It provides a variety of tools and services to make API development faster and easier, including a code generator, a documentation generator, and a testing framework. Talk2APIs also offers a marketplace where developers can find and share APIs.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

DataDreamer is an advanced toolkit designed to facilitate the development of edge AI models by enabling synthetic data generation, knowledge extraction from pre-trained models, and creation of efficient and potent models. It eliminates the need for extensive datasets by generating synthetic datasets, leverages latent knowledge from pre-trained models, and focuses on creating compact models suitable for integration into any device and performance for specialized tasks. The toolkit offers features like prompt generation, image generation, dataset annotation, and tools for training small-scale neural networks for edge deployment. It provides hardware requirements, usage instructions, available models, and limitations to consider while using the library.

LLM-jp-eval is a tool designed to automatically evaluate Japanese large language models across multiple datasets. It provides functionalities such as converting existing Japanese evaluation data to text generation task evaluation datasets, executing evaluations of large language models across multiple datasets, and generating instruction data (jaster) in the format of evaluation data prompts. Users can manage the evaluation settings through a config file and use Hydra to load them. The tool supports saving evaluation results and logs using wandb. Users can add new evaluation datasets by following specific steps and guidelines provided in the tool's documentation. It is important to note that using jaster for instruction tuning can lead to artificially high evaluation scores, so caution is advised when interpreting the results.

AutoDev is an AI-powered coding wizard that supports multiple languages, including Java, Kotlin, JavaScript/TypeScript, Rust, Python, Golang, C/C++/OC, and more. It offers a range of features, including auto development mode, copilot mode, chat with AI, customization options, SDLC support, custom AI agent integration, and language features such as language support, extensions, and a DevIns language for AI agent development. AutoDev is designed to assist developers with tasks such as auto code generation, bug detection, code explanation, exception tracing, commit message generation, code review content generation, smart refactoring, Dockerfile generation, CI/CD config file generation, and custom shell/command generation. It also provides a built-in LLM fine-tune model and supports UnitEval for LLM result evaluation and UnitGen for code-LLM fine-tune data generation.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

The DALM (Domain Adapted Language Modeling) toolkit is designed to unify general LLMs with vector stores to ground AI systems in efficient, factual domains. It provides developers with tools to build on top of Arcee's open source Domain Pretrained LLMs, enabling organizations to deeply tailor AI according to their unique intellectual property and worldview. The toolkit contains code for fine-tuning a fully differential Retrieval Augmented Generation (RAG-end2end) architecture, incorporating in-batch negative concept alongside RAG's marginalization for efficiency. It includes training scripts for both retriever and generator models, evaluation scripts, data processing codes, and synthetic data generation code.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

GPT4Point is a unified framework for point-language understanding and generation. It aligns 3D point clouds with language, providing a comprehensive solution for tasks such as 3D captioning and controlled 3D generation. The project includes an automated point-language dataset annotation engine, a novel object-level point cloud benchmark, and a 3D multi-modality model. Users can train and evaluate models using the provided code and datasets, with a focus on improving models' understanding capabilities and facilitating the generation of 3D objects.

NVIDIA Generative AI Examples are state-of-the-art examples that are easy to deploy, test, and extend. All examples run on the high performance NVIDIA CUDA-X software stack and NVIDIA GPUs. These examples showcase the capabilities of NVIDIA's Generative AI platform, which includes tools, frameworks, and models for building and deploying generative AI applications.

RLAIF-V is a novel framework that aligns MLLMs in a fully open-source paradigm for super GPT-4V trustworthiness. It maximally exploits open-source feedback from high-quality feedback data and online feedback learning algorithm. Notable features include achieving super GPT-4V trustworthiness in both generative and discriminative tasks, using high-quality generalizable feedback data to reduce hallucination of different MLLMs, and exhibiting better learning efficiency and higher performance through iterative alignment.

MicroLens is a content-driven micro-video recommendation dataset at scale. It provides a large dataset with multimodal data, including raw text, images, audio, video, and video comments, for tasks such as multi-modal recommendation, foundation model building, and fairness recommendation. The dataset is available in two versions: MicroLens-50K and MicroLens-100K, with extracted features for multimodal recommendation tasks. Researchers can access the dataset through provided links and reach out to the corresponding author for the complete dataset. The repository also includes codes for various algorithms like VideoRec, IDRec, and VIDRec, each implementing different video models and baselines.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

Supervisely is a computer vision platform that provides a range of tools and services for developing and deploying computer vision solutions. It includes a data labeling platform, a model training platform, and a marketplace for computer vision apps. Supervisely is used by a variety of organizations, including Fortune 500 companies, research institutions, and government agencies.

DataFrame is a C++ analytical library designed for data analysis similar to libraries in Python and R. It allows you to slice, join, merge, group-by, and perform various statistical, summarization, financial, and ML algorithms on your data. DataFrame also includes a large collection of analytical algorithms in form of visitors, ranging from basic stats to more involved analysis. You can easily add your own algorithms as well. DataFrame employs extensive multithreading in almost all its APIs, making it suitable for analyzing large datasets. Key principles followed in the library include supporting any type without needing new code, avoiding pointer chasing, having all column data in contiguous memory space, minimizing space usage, avoiding data copying, using multi-threading judiciously, and not protecting the user against garbage in, garbage out.

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.

Apollo is a multilingual medical LLM that covers English, Chinese, French, Hindi, Spanish, Hindi, and Arabic. It is designed to democratize medical AI to 6B people. Apollo has achieved state-of-the-art results on a variety of medical NLP tasks, including question answering, medical dialogue generation, and medical text classification. Apollo is easy to use and can be integrated into a variety of applications, making it a valuable tool for healthcare professionals and researchers.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

RAFT (Reusable Accelerated Functions and Tools) is a C++ header-only template library with an optional shared library that contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

Python code annotator and test generator

For "Generative AI Test". Examiner in Generative AI, posing questions and providing feedback.

Generates items for psychometric instruments to measure psychological constructs.

Versatile Python programming assistant, adept in TDD and pytest across various projects.

API Finder: Analyze, Clarify, Suggest, build code, Iterate, test ... International version

私はExcelのショートカットキーのクイズを出題するボットです。私の出した問題に正しく回答してください。採点します。

Let's flip a coin

Crafting full, accurate Apex test classes, with 100% user service.

Makes every Sofware Tester an Expert Prompt Engineer

Expert in advanced data analysis and interpretation

Calculate the results of your A/B test and check whether the result is statistically significant or due to chance.

Provides Raven's Progressive Matrices test with explanations and calculates your IQ score.

Formal and structured interactive IQ test platform.

IQ Test is designed to simulate an IQ testing environment. It provides a formal and objective experience, delivering questions and processing answers in a straightforward manner.

I conduct a Turing test and try to decide if you are an AI

Test ideas for cognitive biases or challenge your own views. Member of the Hipster Energy Team. https://hipster.energy/team

Specializes in creating, refining, and testing data analysis prompts based on user queries.

児童、生徒、学生のテストの自己採点物を分析し、文化や私生活を考慮した学習のアドバイスを行います。(This program analyzes the self-graded test items of children, students, and students, and advises them on their studies, taking into account their cultural and personal lives.)

Sequentially administers Big Five Test with 1-5 scale.

The main objective of a personalized ChatGPT for reading laboratory tests is to evaluate laboratory test results and create a spreadsheet with the evaluation results and possible solutions.