Best AI tools for< Test Flow >

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Keploy is an AI tool designed for developers to generate API tests efficiently. It is an open-source platform that converts API calls to test cases with data mocks. Keploy simplifies testing by capturing network interactions and generating automated tests, helping teams accelerate development with streamlined testing processes. The tool allows users to record and replay complex API flows, find duplicate tests, and seamlessly integrate with popular testing libraries like JUnit, PyTest, Jest, and Go-Test in CI/CD pipelines.

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

PaceAI is an AI assistant designed for IT professionals to generate, analyze, and simplify software documentation on IT projects. It uses advanced generative AI models to understand the user's vision, analyze requirements, and automatically generate clear, concise software documentation tailored to the project's needs. With 35+ powerful AI tools, PaceAI assists in every phase of the project, from planning to deployment.

LivePlan is a business plan software that offers performance tracking and financial forecasting tools to help small businesses plan, launch, and grow successfully. It provides a user-friendly interface with AI-powered features, such as the LivePlan Assistant, to guide users through creating comprehensive business plans and financial reports. LivePlan also offers interactive demos, integrations with accounting software like QuickBooks and Xero, and a range of solutions tailored for different business stages and needs. With over 1 million users, LivePlan has helped entrepreneurs and business owners achieve their goals by providing tools and resources to streamline the planning process and improve decision-making.

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.

AI Generated Test Cases is an innovative tool that leverages artificial intelligence to automatically generate test cases for software applications. By utilizing advanced algorithms and machine learning techniques, this tool can efficiently create a comprehensive set of test scenarios to ensure the quality and reliability of software products. With AI Generated Test Cases, software development teams can save time and effort in the testing phase, leading to faster release cycles and improved overall productivity.

AI Test Kitchen is a website that provides a variety of AI-powered tools for creative professionals. These tools can be used to generate images, music, and text, as well as to explore different creative concepts. The website is designed to be a place where users can experiment with AI and learn how to use it to enhance their creative process.

Face Symmetry Test is an AI-powered tool that analyzes the symmetry of facial features by detecting key landmarks such as eyes, nose, mouth, and chin. Users can upload a photo to receive a personalized symmetry score, providing insights into the balance and proportion of their facial features. The tool uses advanced AI algorithms to ensure accurate results and offers guidelines for improving the accuracy of the analysis. Face Symmetry Test is free to use and prioritizes user privacy and security by securely processing uploaded photos without storing or sharing data with third parties.

The AI-powered Cambridge English Test platform offers exercises for English levels B1, B2, C1, and C2. Users can select exercise types such as Reading and Use of English, including activities like Open Cloze, Multiple Choice, Word Formation, and more. The AI, developed by Shining Apps in partnership with Use of English PRO, provides a unique learning experience by generating exercises from a database of over 5000 official exams. It uses advanced Natural Language Processing (NLP) to understand context, tweak exercises, and offer detailed feedback for effective learning.

FaceSymAI is an online tool that utilizes advanced AI algorithms to analyze and determine the symmetry of your face. By uploading a photo, the AI examines your facial features, including the eyes, nose, mouth, and overall structure, to provide an accurate assessment of your facial symmetry. The analysis is based on mathematical and statistical methods, ensuring reliable and precise results. FaceSymAI is designed to be user-friendly and accessible, offering a free service to everyone. The uploaded photos are treated with utmost confidentiality and are not stored or used for any other purpose, ensuring your privacy is respected.

Thumblytics is a tool that helps YouTubers test their YouTube thumbnails and titles before they publish them. It uses a combination of machine learning and human feedback to help users choose the best thumbnail and title combination for their videos. Thumblytics is designed to be easy to use, even for beginners. Users simply upload their thumbnail and title variants to Thumblytics, and the tool will preview them in a YouTube template and show them to hundreds of real people to collect click data. Thumblytics then crunches the data to help users pick the highest click-through rate (CTR) thumbnail and title.

ILoveMyQA is an AI-powered QA testing service that provides comprehensive, well-documented bug reports. The service is affordable, easy to get started with, and requires no time-zapping chats. ILoveMyQA's team of Rockstar QAs is dedicated to helping businesses find and fix bugs before their customers do, so they can enjoy the results and benefits of having a QA team without the cost, management, and headaches.

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.

The website is a platform where users can submit fake hacker news for testing purposes. Users can log in to submit their titles and test their submissions. The platform allows users to see how readers may respond to their posts. The website was built by Justin and Michael.

bottest.ai is an AI-powered chatbot testing tool that focuses on ensuring quality, reliability, and safety in AI-based chatbots. The tool offers automated testing capabilities without the need for coding, making it easy for users to test their chatbots efficiently. With features like regression testing, performance testing, multi-language testing, and AI-powered coverage, bottest.ai provides a comprehensive solution for testing chatbots. Users can record tests, evaluate responses, and improve their chatbots based on analytics provided by the tool. The tool also supports enterprise readiness by allowing scalability, permissions management, and integration with existing workflows.

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 generate various types of questions from different sources like PDFs, Word documents, videos, images, and more. Quizbot.ai is a versatile tool that caters to multiple languages and question types, providing a personalized and engaging learning experience for users across various industries. The platform ensures scalability, flexibility, and personalized assessments, along with detailed analytics and insights to track learner performance. Quizbot.ai is secure, user-friendly, and offers a range of subscription plans to suit different needs.

ACCELQ is a powerful AI-driven test automation platform that offers codeless automation for web, desktop, mobile, and API testing. It provides a unified platform for continuous delivery, full-stack automation, and manual testing integration. ACCELQ is known for its industry-first no-code, no-setup mobile automation platform and comprehensive API automation capabilities. The platform is designed to handle real-world complexities with zero coding required, making it intuitive and scalable for businesses of all sizes.

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

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.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

LLMOps with Prompt flow is a template and guidance for building LLM-infused apps using Prompt flow. It provides centralized code hosting, lifecycle management, variant and hyperparameter experimentation, A/B deployment, many-to-many dataset/flow relationships, multiple deployment targets, comprehensive reporting, BYOF capabilities, configuration-based development, local prompt experimentation and evaluation, endpoint testing, and optional Human-in-loop validation. The tool is customizable to suit various application needs.

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

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

ChainForge is a visual programming environment for battle-testing prompts to LLMs. It is geared towards early-stage, quick-and-dirty exploration of prompts, chat responses, and response quality that goes beyond ad-hoc chatting with individual LLMs. With ChainForge, you can: * Query multiple LLMs at once to test prompt ideas and variations quickly and effectively. * Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case. * Setup evaluation metrics (scoring function) and immediately visualize results across prompts, prompt parameters, models, and model settings. * Hold multiple conversations at once across template parameters and chat models. Template not just prompts, but follow-up chat messages, and inspect and evaluate outputs at each turn of a chat conversation. ChainForge comes with a number of example evaluation flows to give you a sense of what's possible, including 188 example flows generated from benchmarks in OpenAI evals. This is an open beta of Chainforge. We support model providers OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and Dalai-hosted models Alpaca and Llama. You can change the exact model and individual model settings. Visualization nodes support numeric and boolean evaluation metrics. ChainForge is built on ReactFlow and Flask.

Flow Prompt is a dynamic library for managing and optimizing prompts for large language models. It facilitates budget-aware operations, dynamic data integration, and efficient load distribution. Features include CI/CD testing, dynamic prompt development, multi-model support, real-time insights, and prompt testing and evolution.

Rill Flow is a high-performance, scalable distributed workflow orchestration service that supports the execution of tens of millions of tasks per day with task execution latency less than 100ms. It is distributed and supports the orchestration and scheduling of heterogeneous distributed systems. Rill Flow is easy to use, supporting visual process orchestration and plug-in access. It is cloud native, allowing for cloud native container deployment and cloud native function orchestration. Additionally, Rill Flow supports rapid integration of LLM model services.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

ARTKIT is a Python framework developed by BCG X for automating prompt-based testing and evaluation of Gen AI applications. It allows users to develop automated end-to-end testing and evaluation pipelines for Gen AI systems, supporting multi-turn conversations and various testing scenarios like Q&A accuracy, brand values, equitability, safety, and security. The framework provides a simple API, asynchronous processing, caching, model agnostic support, end-to-end pipelines, multi-turn conversations, robust data flows, and visualizations. ARTKIT is designed for customization by data scientists and engineers to enhance human-in-the-loop testing and evaluation, emphasizing the importance of tailored testing for each Gen AI use case.

OpenKF (Open Knowledge Flow) is an online intelligent customer service system. It is an open-source customer service system based on OpenIM, supporting LLM (Local Knowledgebase) customer service and multi-channel customer service. It is easy to integrate with third-party systems, deploy, and perform secondary development. The system provides features like login page, config page, dashboard page, platform page, and session page. Users can quickly get started with OpenKF by following the installation and run instructions. The architecture follows MVC design with a standardized directory structure. The community encourages involvement through community meetings, contributions, and development. OpenKF is licensed under the Apache 2.0 license.

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

SQL Explorer is a Django-based application that simplifies the flow of data between users by providing a user-friendly SQL editor to write and share queries. It supports multiple database connections, AI-powered SQL assistant, schema information access, query snapshots, in-browser statistics, parameterized queries, ad-hoc query running, email query results, and more. Users can upload and query JSON or CSV files, and the tool can connect to various SQL databases supported by Django. It aims for simplicity, stability, and ease of use, offering features like autocomplete, pivot tables, and query history logs.

Langflow is an open-source Python-powered visual framework designed for building multi-agent and RAG applications. It is fully customizable, language model agnostic, and vector store agnostic. Users can easily create flows by dragging components onto the canvas, connect them, and export the flow as a JSON file. Langflow also provides a command-line interface (CLI) for easy management and configuration, allowing users to customize the behavior of Langflow for development or specialized deployment scenarios. The tool can be deployed on various platforms such as Google Cloud Platform, Railway, and Render. Contributors are welcome to enhance the project on GitHub by following the contributing guidelines.

The dbgpts repository contains data apps, AWEL operators, AWEL workflow templates, and agents that are built upon DB-GPT. Users can install and manage these components within their DB-GPT environment. The repository offers functionalities such as listing available flows, installing dbgpts from the official repository, viewing installed dbgpts, running flows, and managing repositories. Users can create new workflow templates and operators using the provided commands. The repository aims to enhance the capabilities of DB-GPT by providing a collection of useful tools and resources for data processing and workflow management.

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.

AgentGenesis is an open-source web app that provides customizable Gen AI code snippets for building custom RAG flows and AI agents. Users can easily copy and paste components into their applications, modify the code as needed, and build on top of it. The tool aims to simplify the development process by offering pre-built code snippets that can be integrated seamlessly into projects without the need for npm installation. AgentGenesis encourages contributions, positive feedback, and support from the community to enhance and grow the project.

YAO is an open-source application engine written in Golang, suitable for developing business systems, website/APP API, admin panel, and self-built low-code platforms. It adopts a flow-based programming model to implement functions by writing YAO DSL or using JavaScript. Yao allows developers to create web services by processes, creating a database model, writing API services, and describing dashboard interfaces just by JSON for web & hardware, and 10x productivity. It is based on the flow-based programming idea, developed in Go language, and supports multiple ways to expand the data stream processor. Yao has a built-in data management system, making it suitable for quickly making various management backgrounds, CRM, ERP, and other internal enterprise systems. It is highly versatile, efficient, and performs better than PHP, JAVA, and other languages.

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.

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