Best AI tools for< Reduce Test Anxiety >

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.

Testim is an AI-powered UI and functional testing platform that helps accelerate test authoring, reduce test maintenance, and release higher-quality apps faster. It offers a range of features such as fast authoring speed, test stability, root cause analysis, and TestOps, making it an efficient and effective solution for product development teams.

hirex.ai is an AI tool designed to make job interviews open, fair, and accessible for all. The platform offers the GenAI assistant to help users get interviewed instantly and jump the line to secure their dream job. With no credit card required, users can register for free early access and benefit from faster screening processes by interviewing candidates using the GenAI assistant. The website aims to transform HR and talent acquisition by providing innovative solutions for job seekers and employers.

Checkmyidea-IA is an AI-powered tool that helps entrepreneurs and businesses evaluate their business ideas before launching them. It uses a variety of factors, such as customer interest, uniqueness, initial product development, and launch strategy, to provide users with a comprehensive review of their idea's potential for success. Checkmyidea-IA can help users save time, increase their chances of success, reduce risk, and improve their decision-making.

Parasoft is an intelligent automated testing and quality platform that offers a range of tools covering every stage of the software development lifecycle. It provides solutions for compliance standards, automated software testing, and various industries' needs. Parasoft helps users accelerate software delivery, ensure quality, and comply with safety and security standards.

Diffblue Cover is an autonomous AI-powered unit test writing tool for Java development teams. It uses next-generation autonomous AI to automate unit testing, freeing up developers to focus on more creative work. Diffblue Cover can write a complete and correct Java unit test every 2 seconds, and it is directly integrated into CI pipelines, unlike AI-powered code suggestions that require developers to check the code for bugs. Diffblue Cover is trusted by the world's leading organizations, including Goldman Sachs, and has been proven to improve quality, lower developer effort, help with code understanding, reduce risk, and increase deployment frequency.

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.

SmartExam is an AI-powered platform designed to assist students in exam preparation by generating test exams based on uploaded lectures. The tool aims to help students succeed in their exams by providing tailored interactive exams and study materials. SmartExam is trusted by top students worldwide and offers a user-friendly experience. Users can upload lecture materials in PDF format, generate test exams in seconds, and download them for further training. The platform reduces exam preparation time by 50% and has received positive feedback for its efficiency and effectiveness.

testRigor is an AI-based test automation tool that allows users to create and execute test cases using plain English instructions. It leverages generative AI in software testing to automate test creation and maintenance, offering features such as no code/codeless testing, web, mobile, and desktop testing, Salesforce automation, and accessibility testing. With testRigor, users can achieve test coverage faster and with minimal maintenance, enabling organizations to reallocate QA engineers to build API tests and increase test coverage significantly. The tool is designed to simplify test automation, reduce QA headaches, and improve productivity by streamlining the testing process.

The website offers an AI testing system that allows users to generate test questions instantly. It features a smart question bank, rapid question generation, and immediate test creation. Users can try out various test questions, such as generating knowledge test questions for car sales, company compliance standards, and real estate tax rate knowledge. The system ensures each test paper has similar content and difficulty levels. It also provides random question selection to reduce cheating possibilities. Employees can access the test link directly, view test scores immediately after submission, and check incorrect answers with explanations. The system supports single sign-on via WeChat for employee verification and record-keeping of employee rankings and test attempts. The platform prioritizes enterprise data security with a three-level network security rating, ISO/IEC 27001 information security management system, and ISO/IEC 27701 privacy information management system.

GRAIL is a healthcare company innovating to solve medicine’s most important challenges. Our team of leading scientists, engineers and clinicians are on an urgent mission to detect cancer early, when it is more treatable and potentially curable. GRAIL's Galleri® test is a first-of-its-kind multi-cancer early detection (MCED) test that can detect a signal shared by more than 50 cancer types and predict the tissue type or organ associated with the signal to help healthcare providers determine next steps.

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%.

Sympher AI offers a suite of easy-to-use AI apps for everyday tasks. These apps are designed to help users save time, improve productivity, and make better decisions. Some of the most popular Sympher AI apps include: * **MeMyselfAI:** This app helps users create personalized AI assistants that can automate tasks, answer questions, and provide support. * **Screenshot to UI Components:** This app helps users convert screenshots of UI designs into code. * **User Story Generator:** This app helps project managers quickly and easily generate user stories for their projects. * **EcoQuery:** This app helps businesses assess their carbon footprint and develop strategies to reduce their emissions. * **SensAI:** This app provides user feedback on uploaded images. * **Excel Sheets Function AI:** This app helps users create functions and formulas for Google Sheets or Microsoft Excel. * **ScriptSensei:** This app helps users create tailored setup scripts to streamline the start of their projects. * **Flutterflow Friend:** This app helps users answer their Flutterflow problems or issues. * **TestScenarioInsight:** This app generates test scenarios for apps before deploying. * **CaptionGen:** This app automatically turns images into captions.

Sider is an AI tool that combines ChatGPT Sidebar with GPT-4o, Claude 3, and Gemini 1.5 to provide an all-in-one AI assistant for reading, writing, and chatting on any webpage. It offers features such as chat support with links, images, PDFs, and various GPT models, free usage, and integration with Chrome. Users can benefit from increased productivity, reduced time spent on tasks, and enhanced creativity and knowledge expansion.

Tricentis is an AI-powered testing tool that offers a comprehensive set of test automation capabilities to address various testing challenges. It provides end-to-end test automation solutions for a wide range of applications, including Salesforce, mobile testing, performance testing, and data integrity testing. Tricentis leverages advanced ML technologies to enable faster and smarter testing, ensuring quality at speed with reduced risk, time, and costs. The platform also offers continuous performance testing, change and data intelligence, and model-based, codeless test automation for mobile applications.

Horizon3.ai Solutions offers the NodeZero™ Platform, an AI-powered autonomous penetration testing tool designed to enhance cybersecurity measures. The platform combines expert human analysis by Offensive Security Certified Professionals with automated testing capabilities to streamline compliance processes and proactively identify vulnerabilities. NodeZero empowers organizations to continuously assess their security posture, prioritize fixes, and verify the effectiveness of remediation efforts. With features like internal and external pentesting, rapid response capabilities, AD password audits, phishing impact testing, and attack research, NodeZero is a comprehensive solution for large organizations, ITOps, SecOps, security teams, pentesters, and MSSPs. The platform provides real-time reporting, integrates with existing security tools, reduces operational costs, and helps organizations make data-driven security decisions.

Pongo is an AI-powered tool that helps reduce hallucinations in Large Language Models (LLMs) by up to 80%. It utilizes multiple state-of-the-art semantic similarity models and a proprietary ranking algorithm to ensure accurate and relevant search results. Pongo integrates seamlessly with existing pipelines, whether using a vector database or Elasticsearch, and processes top search results to deliver refined and reliable information. Its distributed architecture ensures consistent latency, handling a wide range of requests without compromising speed. Pongo prioritizes data security, operating at runtime with zero data retention and no data leaving its secure AWS VPC.

DailyBot is an AI-powered toolkit for teams that want automation, better reporting, and customization. It offers a range of features to enhance team visibility, reduce meetings, and improve collaboration. With DailyBot, teams can run asynchronous standups, retros, and other meetings, send kudos and recognition, create surveys and collect data, and access a variety of add-ons like watercoolers and random coffees. DailyBot also integrates with popular tools like Zapier, Jira, and Trello, making it easy to connect with the tools teams already use. Trusted by leading companies and backed by Y Combinator, DailyBot is a valuable tool for teams looking to improve their collaboration and productivity.

Nametag is an identity verification solution designed specifically for IT helpdesks. It helps businesses prevent social engineering attacks, account takeovers, and data breaches by verifying the identity of users at critical moments, such as password resets, MFA resets, and high-risk transactions. Nametag's unique approach to identity verification combines mobile cryptography, device telemetry, and proprietary AI models to provide unmatched security and better user experiences.

SentinelOne is an advanced enterprise cybersecurity AI platform that offers a comprehensive suite of AI-powered security solutions for endpoint, cloud, and identity protection. The platform leverages AI technology to anticipate threats, manage vulnerabilities, and protect resources across the enterprise ecosystem. SentinelOne provides real-time threat hunting, managed services, and actionable insights through its unified data lake, empowering security teams to respond effectively to cyber threats. With a focus on automation, efficiency, and value maximization, SentinelOne is a trusted cybersecurity solution for leading enterprises worldwide.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

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.

This repository contains an implementation of Ring Attention, a technique for processing large sequences in transformers. Ring Attention splits the data across the sequence dimension and applies ring reduce to the processing of the tiles of the attention matrix, similar to flash attention. It also includes support for Striped Attention, a follow-up paper that permutes the sequence for better workload balancing for autoregressive transformers, and grouped query attention, which saves on communication costs during the ring reduce. The repository includes a CUDA version of the flash attention kernel, which is used for the forward and backward passes of the ring attention. It also includes logic for splitting the sequence evenly among ranks, either within the attention function or in the external ring transformer wrapper, and basic test cases with two processes to check for equivalent output and gradients.

ReproModel is an open-source toolbox designed to boost AI research efficiency by enabling researchers to reproduce, compare, train, and test AI models faster. It provides standardized models, dataloaders, and processing procedures, allowing researchers to focus on new datasets and model development. With a no-code solution, users can access benchmark and SOTA models and datasets, utilize training visualizations, extract code for publication, and leverage an LLM-powered automated methodology description writer. The toolbox helps researchers modularize development, compare pipeline performance reproducibly, and reduce time for model development, computation, and writing. Future versions aim to facilitate building upon state-of-the-art research by loading previously published study IDs with verified code, experiments, and results stored in the system.

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.

Lobe Icons is a collection of popular AI / LLM Model Brand SVG logos and icons. It features lightweight and scalable icons designed with highly optimized scalable vector graphics (SVG) for optimal performance. The collection is tree-shakable, allowing users to import only the icons they need to reduce the overall bundle size of their projects. Lobe Icons has an active community of designers and developers who can contribute and seek support on platforms like GitHub and Discord. The repository supports a wide range of brands across different models, providers, and applications, with more brands continuously being added through contributions. Users can easily install Lobe UI with the provided commands and integrate it with NextJS for server-side rendering. Local development can be done using Github Codespaces or by cloning the repository. Contributions are welcome, and users can contribute code by checking out the GitHub Issues. The project is MIT licensed and maintained by LobeHub.

The bilingual_book_maker is an AI translation tool that uses ChatGPT to assist users in creating multi-language versions of epub/txt/srt files and books. It supports various models like gpt-4, gpt-3.5-turbo, claude-2, palm, llama-2, azure-openai, command-nightly, and gemini. Users need ChatGPT or OpenAI token, epub/txt books, internet access, and Python 3.8+. The tool provides options to specify OpenAI API key, model selection, target language, proxy server, context addition, translation style, and more. It generates bilingual books in epub format after translation. Users can test translations, set batch size, tweak prompts, and use different models like DeepL, Google Gemini, Tencent TranSmart, and more. The tool also supports retranslation, translating specific tags, and e-reader type specification. Docker usage is available for easy setup.

Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.

Voicechat2 is a fast, fully local AI voice chat tool that uses WebSockets for communication. It includes a WebSocket server for remote access, default web UI with VAD and Opus support, and modular/swappable SRT, LLM, TTS servers. Users can customize components like SRT, LLM, and TTS servers, and run different models for voice-to-voice communication. The tool aims to reduce latency in voice communication and provides flexibility in server configurations.

AutoGPT is a revolutionary tool that empowers everyone to harness the power of AI. With AutoGPT, you can effortlessly build, test, and delegate tasks to AI agents, unlocking a world of possibilities. Our mission is to provide the tools you need to focus on what truly matters: innovation and creativity.

Consistency Large Language Models (CLLMs) is a family of efficient parallel decoders that reduce inference latency by efficiently decoding multiple tokens in parallel. The models are trained to perform efficient Jacobi decoding, mapping any randomly initialized token sequence to the same result as auto-regressive decoding in as few steps as possible. CLLMs have shown significant improvements in generation speed on various tasks, achieving up to 3.4 times faster generation. The tool provides a seamless integration with other techniques for efficient Large Language Model (LLM) inference, without the need for draft models or architectural modifications.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project caches pre-generated model results to reduce response time for similar requests and enhance user experience. It integrates various embedding frameworks and local storage options, offering functionalities like cache-writing, cache-querying, and cache-clearing through RESTful API. The tool supports multi-tenancy, system commands, and multi-turn dialogue, with features for data isolation, database management, and model loading schemes. Future developments include data isolation based on hyperparameters, enhanced system prompt partitioning storage, and more versatile embedding models and similarity evaluation algorithms.

Open-Lyrics is a Python library that transcribes voice files using faster-whisper and translates/polishes the resulting text into `.lrc` files in the desired language using LLM, e.g. OpenAI-GPT, Anthropic-Claude. It offers well preprocessed audio to reduce hallucination and context-aware translation to improve translation quality. Users can install the library from PyPI or GitHub and follow the installation steps to set up the environment. The tool supports GUI usage and provides Python code examples for transcription and translation tasks. It also includes features like utilizing context and glossary for translation enhancement, pricing information for different models, and a list of todo tasks for future improvements.

llmc is an off-the-shell tool designed for compressing LLM, leveraging state-of-the-art compression algorithms to enhance efficiency and reduce model size without compromising performance. It provides users with the ability to quantize LLMs, choose from various compression algorithms, export transformed models for further optimization, and directly infer compressed models with a shallow memory footprint. The tool supports a range of model types and quantization algorithms, with ongoing development to include pruning techniques. Users can design their configurations for quantization and evaluation, with documentation and examples planned for future updates. llmc is a valuable resource for researchers working on post-training quantization of large language models.

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.

RTL-Coder is a tool designed to outperform GPT-3.5 in RTL code generation by providing a fully open-source dataset and a lightweight solution. It targets Verilog code generation and offers an automated flow to generate a large labeled dataset with over 27,000 diverse Verilog design problems and answers. The tool addresses the data availability challenge in IC design-related tasks and can be used for various applications beyond LLMs. The tool includes four RTL code generation models available on the HuggingFace platform, each with specific features and performance characteristics. Additionally, RTL-Coder introduces a new LLM training scheme based on code quality feedback to further enhance model performance and reduce GPU memory consumption.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project facilitates sharing and exchanging technologies related to large model semantic cache through open-source collaboration.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome). It is designed to provide high performance and scalability for large language models, enabling efficient inference on cloud-based TPUs. JetStream leverages XLA to optimize the execution of LLM models, resulting in faster and more efficient inference. Additionally, JetStream supports quantization techniques to further enhance performance and reduce memory consumption. By utilizing JetStream, developers can deploy and run LLM models on TPUs with ease, achieving optimal performance and cost-effectiveness.

This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for **fast prototyping** and **prompting** , and turning unstructured responses into **robust outputs** for various NLP tasks, **no training data** required. It supports open-source LLMs hosted on Hugging Face 🤗: Falcon, Dolly, Llama 2, OpenLLaMA, StableLM, Mistral. Integration with LangChain 🦜️🔗 - all `langchain` models and features can be used in `spacy-llm`. Tasks available out of the box: Named Entity Recognition, Text classification, Lemmatization, Relationship extraction, Sentiment analysis, Span categorization, Summarization, Entity linking, Translation, Raw prompt execution for maximum flexibility. Soon: Semantic role labeling. Easy implementation of **your own functions** via spaCy's registry for custom prompting, parsing and model integrations. For an example, see here. Map-reduce approach for splitting prompts too long for LLM's context window and fusing the results back together

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