Best AI tools for< Deploy Tests >

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

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

Vapi is a Voice AI tool designed specifically for developers. It enables developers to interact with their code using voice commands, making the coding process more efficient and hands-free. With Vapi, developers can perform various tasks such as writing code, debugging, and running tests simply by speaking. The tool is equipped with advanced natural language processing capabilities to accurately interpret and execute voice commands. Vapi aims to revolutionize the way developers work by providing a seamless and intuitive coding experience.

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.

Pythagora AI is an AI-powered tool designed to help users build internal tools with artificial intelligence. It enables users to develop web apps, integrate with Cursor, and deploy full-stack web applications seamlessly. Pythagora offers features such as one-click deployment, automatic breakpoints, code reviews, pair programming, and automated tests generation. Built for developers, by developers, Pythagora aims to simplify the app development process by providing utility functions, advanced features, and self-healing code capabilities. The tool supports building frontend in React and backend in Node.js, with Python support coming soon. Users retain full ownership of the projects and code created using Pythagora, with pricing plans ranging from Starter to Enterprise for different team sizes and project needs.

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Cirrascale Cloud Services is an AI tool that offers cloud solutions for Artificial Intelligence applications. The platform provides a range of cloud services and products tailored for AI innovation, including NVIDIA GPU Cloud, AMD Instinct Series Cloud, Qualcomm Cloud, Graphcore, Cerebras, and SambaNova. Cirrascale's AI Innovation Cloud enables users to test and deploy on leading AI accelerators in one cloud, democratizing AI by delivering high-performance AI compute and scalable deep learning solutions. The platform also offers professional and managed services, tailored multi-GPU server options, and high-throughput storage and networking solutions to accelerate development, training, and inference workloads.

Contentable.ai is a platform for comparing multiple AI models, rapidly moving from prototyping to production, and management of your custom AI solutions across multiple vendors. It allows users to test multiple AI models in seconds, compare models side-by-side across top AI providers, collaborate on AI models with their team seamlessly, design complex AI workflows without coding, and pay as they go.

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.

Filuta AI is an advanced AI application that redefines game testing with planning agents. It utilizes Composite AI with planning techniques to provide a 24/7 testing environment for smooth, bug-free releases. The application brings deep space technology to game testing, enabling intelligent agents to analyze game states, adapt in real time, and execute action sequences to achieve test goals. Filuta AI offers goal-driven testing, adaptive exploration, detailed insights, and shorter development cycles, making it a valuable tool for game developers, QA leads, game designers, automation engineers, and producers.

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.

Hanabi.rest is an AI-based API building platform that allows users to create REST APIs from natural language and screenshots using AI technology. Users can deploy the APIs on Cloudflare Workers and roll them out globally. The platform offers a live editor for testing database access and API endpoints, generates code compatible with various runtimes, and provides features like sharing APIs via URL, npm package integration, and CLI dump functionality. Hanabi.rest simplifies API design and deployment by leveraging natural language processing, image recognition, and v0.dev components.

Leapwork is an AI-powered test automation platform that enables users to build, manage, maintain, and analyze complex data-driven testing across various applications, including AI apps. It offers a democratized testing approach with an intuitive visual interface, composable architecture, and generative AI capabilities. Leapwork supports testing of diverse application types, web, mobile, desktop applications, and APIs. It allows for scalable testing with reusable test flows that adapt to changes in the application under test. Leapwork can be deployed on the cloud or on-premises, providing full control to the users.

MagikKraft is an AI-powered platform that simplifies complex controls by allowing users to create personalized sequences and actions for programmable devices like drones, automated appliances, and self-driving vehicles. Users can craft customized recipes, test them in a virtual environment, and deploy them seamlessly into the real world. MagikKraft prioritizes privacy, user control, and creative freedom, aiming to enhance technology's potential without causing harm or unforeseen consequences.

OpenPlayground is a cloud-based platform that provides access to a variety of AI tools and resources. It allows users to train and deploy machine learning models, access pre-trained models, and collaborate on AI projects. OpenPlayground is designed to make AI more accessible and easier to use for everyone, from beginners to experienced data scientists.

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.

GptSdk is an AI tool that simplifies incorporating AI capabilities into PHP projects. It offers dynamic prompt management, model management, bulk testing, collaboration chaining integration, and more. The tool allows developers to develop professional AI applications 10x faster, integrates with Laravel and Symfony, and supports both local and API prompts. GptSdk is open-source under the MIT License and offers a flexible pricing model with a generous free tier.

BotStacks is a conversational AI solution that offers premium AI sidekicks to automate, engage, and succeed. It provides a platform for designing, building, and deploying AI chatbots with advanced technology accessible to everyone. With features like canvas designer, knowledge base, and chat SDKs, BotStacks empowers users to create personalized and scalable AI assistants. The application focuses on easy design flow, seamless integration, customization, scalability, and accessibility for non-technical users, making it a gateway to the future of conversational AI.

LuckyRobots is an AI tool designed to make robotics accessible to software engineers by providing a simulation platform for deploying end-to-end AI models. The platform allows users to interact with robots using natural language commands, explore virtual environments, test robot models in realistic scenarios, and receive camera feeds for monitoring. LuckyRobots aims to train AI models on real-world simulations and respond to natural language inputs, offering a user-friendly and innovative approach to robotics development.

Cerebium is a serverless AI infrastructure platform that allows teams to build, test, and deploy AI applications quickly and efficiently. With a focus on speed, performance, and cost optimization, Cerebium offers a range of features and tools to simplify the development and deployment of AI projects. The platform ensures high reliability, security, and compliance while providing real-time logging, cost tracking, and observability tools. Cerebium also offers GPU variety and effortless autoscaling to meet the diverse needs of developers and businesses.

The 'ai-dev-2024-ml-workshop' repository contains materials for the Deploy and Monitor ML Pipelines workshop at the AI_dev 2024 conference in Paris, focusing on deployment designs of machine learning pipelines using open-source applications and free-tier tools. It demonstrates automating data refresh and forecasting using GitHub Actions and Docker, monitoring with MLflow and YData Profiling, and setting up a monitoring dashboard with Quarto doc on GitHub Pages.

Seer is a service that provides AI capabilities to Sentry by running inference on Sentry issues and providing user insights. It is currently in early development and not yet compatible with self-hosted Sentry instances. The tool requires access to internal Sentry resources and is intended for internal Sentry employees. Users can set up the environment, download model artifacts, integrate with local Sentry, run evaluations for Autofix AI agent, and deploy to a sandbox staging environment. Development commands include applying database migrations, creating new migrations, running tests, and more. The tool also supports VCRs for recording and replaying HTTP requests.

Mastra is an opinionated Typescript framework designed to help users quickly build AI applications and features. It provides primitives such as workflows, agents, RAG, integrations, syncs, and evals. Users can run Mastra locally or deploy it to a serverless cloud. The framework supports various LLM providers, offers tools for building language models, workflows, and accessing knowledge bases. It includes features like durable graph-based state machines, retrieval-augmented generation, integrations, syncs, and automated tests for evaluating LLM outputs.

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.

Tau is a framework for building low maintenance & highly scalable cloud computing platforms that software developers will love. It aims to solve the high cost and time required to build, deploy, and scale software by providing a developer-friendly platform that offers autonomy and flexibility. Tau simplifies the process of building and maintaining a cloud computing platform, enabling developers to achieve 'Local Coding Equals Global Production' effortlessly. With features like auto-discovery, content-addressing, and support for WebAssembly, Tau empowers users to create serverless computing environments, host frontends, manage databases, and more. The platform also supports E2E testing and can be extended using a plugin system called orbit.

Beta9 is an open-source platform for running scalable serverless GPU workloads across cloud providers. It allows users to scale out workloads to thousands of GPU or CPU containers, achieve ultrafast cold-start for custom ML models, automatically scale to zero to pay for only what is used, utilize flexible distributed storage, distribute workloads across multiple cloud providers, and easily deploy task queues and functions using simple Python abstractions. The platform is designed for launching remote serverless containers quickly, featuring a custom, lazy loading image format backed by S3/FUSE, a fast redis-based container scheduling engine, content-addressed storage for caching images and files, and a custom runc container runtime.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

AirSwap Protocols is a repository containing smart contracts for developers and traders on the AirSwap peer-to-peer trading network. It includes various packages for functionalities like server registry, atomic token swap, staking, rewards pool, batch token and order calls, libraries, and utils. The repository follows a branching and release process for contracts and tools, with steps for regular development process and individual package features or patches. Users can deploy and verify contracts using specific commands with network flags.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

The GPT Server project leverages the basic capabilities of FastChat to provide the capabilities of an openai server. It perfectly adapts more models, optimizes models with poor compatibility in FastChat, and supports loading vllm, LMDeploy, and hf in various ways. It also supports all sentence_transformers compatible semantic vector models, including Chat templates with function roles, Function Calling (Tools) capability, and multi-modal large models. The project aims to reduce the difficulty of model adaptation and project usage, making it easier to deploy the latest models with minimal code changes.

Omnia is a deployment tool designed to turn servers with RPM-based Linux images into functioning Slurm/Kubernetes clusters. It provides an Ansible playbook-based deployment for Slurm and Kubernetes on servers running an RPM-based Linux OS. The tool simplifies the process of setting up and managing clusters, making it easier for users to deploy and maintain their infrastructure.

This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

Cortex is a C++ AI engine with a Docker-like command-line interface and client libraries. It supports running AI models using ONNX, TensorRT-LLM, and llama.cpp engines. Cortex can function as a standalone server or be integrated as a library. The tool provides support for various engines and models, allowing users to easily deploy and interact with AI models. It offers a range of CLI commands for managing models, embeddings, and engines, as well as a REST API for interacting with models. Cortex is designed to simplify the deployment and usage of AI models in C++ applications.

CB-Tumblebug (CB-TB) is a system for managing multi-cloud infrastructure consisting of resources from multiple cloud service providers. It provides an overview, features, and architecture. The tool supports various cloud providers and resource types, with ongoing development and localization efforts. Users can deploy a multi-cloud infra with GPUs, enjoy multiple LLMs in parallel, and utilize LLM-related scripts. The tool requires Linux, Docker, Docker Compose, and Golang for building the source. Users can run CB-TB with Docker Compose or from the Makefile, set up prerequisites, contribute to the project, and view a list of contributors. The tool is licensed under an open-source license.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

Eidolon is an open-source agent services framework that helps developers design and deploy agent-based services. It simplifies agent deployment, facilitates agent-to-agent communication, and enables painless component customization and upgrades. Eidolon's modular architecture allows developers to easily swap out components, such as language models, reinforcement learning implementations, tools, and more. This flexibility minimizes vendor lock-in and reduces the effort required to upgrade agent components. As the AI landscape rapidly evolves, Eidolon empowers developers to adapt their agents to meet changing requirements.

Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. With Flyte, user teams can construct pipelines using the Python SDK, and seamlessly deploy them on both cloud and on-premises environments, enabling distributed processing and efficient resource utilization.

This project is a c++ version of the AI reasoning library that supports the reasoning of tensorrt models. It provides accelerated deployment cases of deep learning CV popular models and supports dynamic-batch image processing, inference, decode, and NMS. The project has been updated with various models and provides tutorials for model exports. It also includes a producer-consumer inference model for specific tasks. The project directory includes implementations for model inference applications, backend reasoning classes, post-processing, pre-processing, and target detection and tracking. Speed tests have been conducted on various models, and onnx downloads are available for different models.

Cog is an open-source tool that lets you package machine learning models in a standard, production-ready container. You can deploy your packaged model to your own infrastructure, or to Replicate.

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