Best AI tools for< fill test coverage gaps >

Roost.ai is an AI-driven testing copilot that offers automated test case generation using Large Language Models (LLMs). It helps in building reliable software by providing 100% test coverage every single time. Roost.ai leverages generative AI to free up developer time, elevate test accuracy and coverage, and detect static vulnerabilities in source code and logs. The platform is trusted by global financial institutions and industry leaders for its ability to fill gaps in test coverage and automate complex parts of testing and deploying changes.

Quizbot.ai is an advanced AI question generator designed to revolutionize the process of question and exam development. It offers a cutting-edge artificial intelligence system that can create various types of questions from different sources like PDFs, Word documents, videos, images, web links, and audio files. Quizbot.ai is a versatile tool that supports multiple languages and question types, making it suitable for educational institutions, corporate training programs, and personal enrichment purposes. The platform provides personalized quizzes, detailed analytics, and insights to enhance the learning experience and improve knowledge retention. Quizbot.ai prioritizes user data security and offers flexible pricing plans to cater to different user needs.

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.

Yippity is an AI-powered question generator that helps educators and trainers create engaging and interactive assessments. With Yippity, you can easily create multiple choice, true/false, fill-in-the-blank, and short answer questions. You can also add images, videos, and audio to your questions to make them more engaging. Yippity is a great tool for creating formative assessments, quizzes, and tests. It can also be used to create practice questions for students who are preparing for standardized tests.

CreateMyTest is an online tool that uses artificial intelligence to automatically convert documents and YouTube videos into tests. It offers various question types, including multiple choice, true/false, matching, and fill in the blank. The platform aims to enhance studying by helping users retain knowledge through practice testing and reduce test anxiety.

Bytebot is a web automation tool that uses AI to make it easy to create and manage web tasks. With Bytebot, you can create browser automations as intuitively as writing a simple prompt. Bytebot will take care of the code for you, so you can focus on the task at hand. Bytebot is perfect for a variety of tasks, including data extraction, form filling, and website monitoring.

Goless is a browser automation tool that allows users to automate tasks on websites without the need for coding. It offers a range of features such as data scraping, form filling, CAPTCHA solving, and workflow automation. The tool is designed to be easy to use, with a drag-and-drop interface and a marketplace of ready-made workflows. Goless can be used to automate a variety of tasks, including data collection, data entry, website testing, and social media automation.

Fill A Form AI is an innovative tool designed to streamline the form-filling process by leveraging artificial intelligence technology. It offers a one-click solution for filling out forms quickly and efficiently, eliminating the need for tedious data entry tasks. The tool learns from past filled forms, efficiently finds answers from data, and provides powerful features tailored to users' needs. With features like auto-detect form fields, auto-fill from history, and smart collaboration, Fill A Form AI aims to ease users' form-filling experience and save time and effort.

AI Form Fill is an AI-powered tool that revolutionizes form filling by using advanced AI models to understand context and accurately fill forms across various websites and form types. Users can save time and boost productivity by customizing the AI's behavior, choosing from multiple AI models, and enjoying a flexible pricing system. The tool offers features like AI-powered filling, one-click magic fill, customizable context, and a referral program. With applications in job applications, survey responses, content creation, and product listings, AI Form Fill streamlines various tasks and enhances user efficiency and consistency.

FillDream.net is an AI tool that allows users to fill images with desired content using AI technology. Users can input prompts such as 'Cabin', 'Lake', 'Rocket', or 'Tree' to generate images filled with the specified content. The website provides a simple and intuitive platform for users to bring their creative ideas to life through AI-generated images.

TalkForm AI is an AI-powered platform that revolutionizes the way forms are created and filled. It offers a seamless chat-based interface for users to effortlessly generate and complete forms without the need for manual configuration. The AI technology behind TalkForm automatically infers field types, validates, cleans, structures, and fills form responses, ensuring data integrity and ease of analysis. With TalkForm AI, users can enjoy faster, easier, and more powerful form creation and filling experiences.

Stylar is a powerful AI-powered image generation and design tool that provides users with unparalleled control over image composition and style. With its user-friendly interface and advanced features, Stylar makes it easy for users of all skill levels to create stunning and professional-looking images. Key features of Stylar include predefined styles for effortless design customization, layering, positioning, and sketching tools for intuitive design, and user-friendly interface for all skill levels.

Autofillr is an AI-powered Chrome extension that automates form filling, making it accurate, secure, and effortless. It utilizes advanced AI technology to understand and learn the structure of web forms, enabling it to detect and fill out a wide variety of forms with precision. Autofillr goes beyond basic fields like names and addresses, aiming to make any form a one-click experience. It continuously enhances its technology to provide a streamlined and efficient online experience for users.

PYQ is an AI-powered platform that helps businesses automate document-related tasks, such as data extraction, form filling, and system integration. It uses natural language processing (NLP) and machine learning (ML) to understand the content of documents and perform tasks accordingly. PYQ's platform is designed to be easy to use, with pre-built automations for common use cases. It also offers custom automation development services for more complex needs.

Huntr is a job search tool that helps users create tailored resumes and cover letters, fill out application forms, and organize their job search. It uses AI to generate resume suggestions, extract keywords from job descriptions, and calculate job match scores. Huntr also has a Chrome extension that allows users to save jobs and autofill applications.

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Mockitt is an all-in-one online design, prototyping, and collaboration platform that empowers UI/UX designers to create interactive and animated prototypes, flowcharts, and mind maps. With its AI-powered features, such as AI Prototype Generator, AI Component Generator, and Magic Fill, Mockitt helps designers significantly elevate their efficiency and unlock new possibilities. Mockitt also offers a wide range of built-in templates, components, and resources, making it easy for anyone to bring their ideas to life. Additionally, Mockitt's real-time collaboration features enable designers to share, edit, and comment on projects simultaneously, ensuring everyone is on the same page.

Designstripe is a web-based platform that uses artificial intelligence to help businesses create social media content. It analyzes a business's website and social media channels to get a thorough understanding of its brand, products, and audience. This information is then used to generate personalized marketing designs that are on-brand and on-demand. Designstripe also offers a variety of tools to help businesses create custom illustrations, mockups, and animations.

Heidi is an AI-powered medical scribe that helps clinicians save time and improve patient care. It uses natural language processing to capture every detail of a patient visit, and then automatically generates a note that is tailored to the clinician's preferences. Heidi can also be used to create letters, add billing codes, and generate patient summaries. It is trusted by clinicians and healthcare staff in over 35 countries.

AI Image Magic Cleanup is an online tool that uses advanced AI technology to remove unwanted objects from images and automatically fill in the background. It is designed to make image editing easier and more efficient, especially for tasks such as removing logos, watermarks, and other distracting elements from photos.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

FeedGen is an open-source tool that uses Google Cloud's state-of-the-art Large Language Models (LLMs) to improve product titles, generate more comprehensive descriptions, and fill missing attributes in product feeds. It helps merchants and advertisers surface and fix quality issues in their feeds using Generative AI in a simple and configurable way. The tool relies on GCP's Vertex AI API to provide both zero-shot and few-shot inference capabilities on GCP's foundational LLMs. With few-shot prompting, users can customize the model's responses towards their own data, achieving higher quality and more consistent output. FeedGen is an Apps Script based application that runs as an HTML sidebar in Google Sheets, allowing users to optimize their feeds with ease.

This repository provides a ready-to-run basic Slack AI solution that allows users to summarize threads and channels using OpenAI. Users can generate thread summaries, channel overviews, channel summaries since a specific time, and full channel summaries. The tool is powered by GPT-3.5-Turbo and an ensemble of NLP models. It requires Python 3.8 or higher, an OpenAI API key, Slack App with associated API tokens, Poetry package manager, and ngrok for local development. Users can customize channel and thread summaries, run tests with coverage using pytest, and contribute to the project for future enhancements.

Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

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)

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

The Universal Numbers Library is a header-only C++ template library designed for universal number arithmetic, offering alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. It tailors arithmetic types to the application's precision and dynamic range, enabling improved application performance and energy efficiency. The library provides fast implementations of special IEEE-754 formats like quarter precision, half-precision, and quad precision, as well as vendor-specific extensions. It supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval, and adaptive-precision integers, rationals, and floats. The library is suitable for AI, DSP, HPC, and HFT algorithms.

LightEval is a lightweight LLM evaluation suite that Hugging Face has been using internally with the recently released LLM data processing library datatrove and LLM training library nanotron. We're releasing it with the community in the spirit of building in the open. Note that it is still very much early so don't expect 100% stability ^^' In case of problems or question, feel free to open an issue!

Parea AI provides a SDK to evaluate & monitor AI applications. It allows users to test, evaluate, and monitor their AI models by defining and running experiments. The SDK also enables logging and observability for AI applications, as well as deploying prompts to facilitate collaboration between engineers and subject-matter experts. Users can automatically log calls to OpenAI and Anthropic, create hierarchical traces of their applications, and deploy prompts for integration into their applications.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features such as a Virtual API System with caching and API simulators, a new set of solvable queries determined by LLMs, and a Stable Evaluation System using GPT-4. The Virtual API Server can be set up either by building from source or using a prebuilt Docker image. Users can test the server using provided scripts and evaluate models with Solvable Pass Rate and Solvable Win Rate metrics. The tool also includes model experiments results comparing different models' performance.

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.

LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.

Twinny is a free and private AI extension for Visual Studio Code that offers AI-based code completion and code discussion features. It provides real-time code suggestions, function explanations, test generation, refactoring requests, and more. Twinny operates both online and offline, supports customizable API endpoints, conforms to OpenAI API standards, and offers various customization options for prompt templates, API providers, model names, and more. It is compatible with multiple APIs and allows users to accept code solutions directly in the editor, create new documents from code blocks, and copy generated code solution blocks. Twinny is open-source under the MIT license and welcomes contributions from the community.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

AgentBench is a benchmark designed to evaluate Large Language Models (LLMs) as autonomous agents in various environments. It includes 8 distinct environments such as Operating System, Database, Knowledge Graph, Digital Card Game, and Lateral Thinking Puzzles. The tool provides a comprehensive evaluation of LLMs' ability to operate as agents by offering Dev and Test sets for each environment. Users can quickly start using the tool by following the provided steps, configuring the agent, starting task servers, and assigning tasks. AgentBench aims to bridge the gap between LLMs' proficiency as agents and their practical usability.

RayLLM (formerly known as Aviary) is an LLM serving solution that makes it easy to deploy and manage a variety of open source LLMs, built on Ray Serve. It provides an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. RayLLM supports Transformer models hosted on Hugging Face Hub or present on local disk. It simplifies the deployment of multiple LLMs, the addition of new LLMs, and offers unique autoscaling support, including scale-to-zero. RayLLM fully supports multi-GPU & multi-node model deployments and offers high performance features like continuous batching, quantization and streaming. It provides a REST API that is similar to OpenAI's to make it easy to migrate and cross test them. RayLLM supports multiple LLM backends out of the box, including vLLM and TensorRT-LLM.

org-ai is a minor mode for Emacs org-mode that provides access to generative AI models, including OpenAI API (ChatGPT, DALL-E, other text models) and Stable Diffusion. Users can use ChatGPT to generate text, have speech input and output interactions with AI, generate images and image variations using Stable Diffusion or DALL-E, and use various commands outside org-mode for prompting using selected text or multiple files. The tool supports syntax highlighting in AI blocks, auto-fill paragraphs on insertion, and offers block options for ChatGPT, DALL-E, and other text models. Users can also generate image variations, use global commands, and benefit from Noweb support for named source blocks.

Mistral Inference repository contains minimal code to run 7B, 8x7B, and 8x22B models. It provides model download links, installation instructions, and usage guidelines for running models via CLI or Python. The repository also includes information on guardrailing, model platforms, deployment, and references. Users can interact with models through commands like mistral-demo, mistral-chat, and mistral-common. Mistral AI models support function calling and chat interactions for tasks like testing models, chatting with models, and using Codestral as a coding assistant. The repository offers detailed documentation and links to blogs for further information.

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