Best AI tools for< Test Endpoints >

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.

jsonAI is an AI tool that allows users to easily transform data into structured JSON format. Users can define their schema, add custom prompts, and receive AI-structured JSON responses. The tool enables users to create complex schemas with nested objects, control the response JSON on the fly, and test their JSON data in real-time. jsonAI offers a free trial plan, seamless integration with existing apps, and ensures data security by not storing user data on their servers.

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.

PrepGenius.ai is an AI-driven test preparation platform designed to revolutionize the way students prepare for AP courses, college admission tests, and more. The platform offers personalized study plans, real-time feedback, interactive learning tools, and comprehensive resources to help students understand their strengths and weaknesses. With PrepGenius.ai, students can study smarter, receive tailored feedback, and track their progress to improve their test scores effectively.

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.

Virtuoso is an AI-powered, end-to-end functional testing tool for web applications. It uses Natural Language Programming, Machine Learning, and Robotic Process Automation to automate the testing process, making it faster and more efficient. Virtuoso can be used by QA managers, practitioners, and senior executives to improve the quality of their software applications.

Ottic is an AI tool designed to empower both technical and non-technical teams to test Language Model (LLM) applications efficiently and accelerate the development cycle. It offers features such as a 360º view of the QA process, end-to-end test management, comprehensive LLM evaluation, and real-time monitoring of user behavior. Ottic aims to bridge the gap between technical and non-technical team members, ensuring seamless collaboration and reliable product delivery.

ClearML Serving is a command line utility for model deployment and orchestration, enabling model deployment including serving and preprocessing code to a Kubernetes cluster or custom container based solution. It supports machine learning models like Scikit Learn, XGBoost, LightGBM, and deep learning models like TensorFlow, PyTorch, ONNX. It provides a customizable RestAPI for serving, online model deployment, scalable solutions, multi-model per container, automatic deployment, canary A/B deployment, model monitoring, usage metric reporting, metric dashboard, and model performance metrics. ClearML Serving is modular, scalable, flexible, customizable, and open source.

llm-swarm is a tool designed to manage scalable open LLM inference endpoints in Slurm clusters. It allows users to generate synthetic datasets for pretraining or fine-tuning using local LLMs or Inference Endpoints on the Hugging Face Hub. The tool integrates with huggingface/text-generation-inference and vLLM to generate text at scale. It manages inference endpoint lifetime by automatically spinning up instances via `sbatch`, checking if they are created or connected, performing the generation job, and auto-terminating the inference endpoints to prevent idling. Additionally, it provides load balancing between multiple endpoints using a simple nginx docker for scalability. Users can create slurm files based on default configurations and inspect logs for further analysis. For users without a Slurm cluster, hosted inference endpoints are available for testing with usage limits based on registration status.

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.

A Rust based tool to evaluate LLM models, prompts and model params. It automates the process of selecting the best model parameters, given an LLM model and a prompt, iterating over the possible combinations and letting the user visually inspect the results. The tool assumes the user has Ollama installed and serving endpoints, either in `localhost` or in a remote server. Key features include: * Automatically fetches models from local or remote Ollama servers * Iterates over different models and params to generate inferences * A/B test prompts on different models simultaneously * Allows multiple iterations for each combination of parameters * Makes synchronous inference calls to avoid spamming servers * Optionally outputs inference parameters and response metadata (inference time, tokens and tokens/s) * Refetching of individual inference calls * Model selection can be filtered by name * List experiments which can be downloaded in JSON format * Configurable inference timeout * Custom default parameters and system prompts can be defined in settings

EasyAIVtuber is a tool designed to animate 2D waifus by providing features like automatic idle actions, speaking animations, head nodding, singing animations, and sleeping mode. It also offers API endpoints and a web UI for interaction. The tool requires dependencies like torch and pre-trained models for optimal performance. Users can easily test the tool using OBS and UnityCapture, with options to customize character input, output size, simplification level, webcam output, model selection, port configuration, sleep interval, and movement extension. The tool also provides an API using Flask for actions like speaking based on audio, rhythmic movements, singing based on music and voice, stopping current actions, and changing images.

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.

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.

The Apache Airflow Python Client provides a range of REST API endpoints for managing Airflow metadata objects. It supports CRUD operations for resources, with endpoints accepting and returning JSON. Users can create, read, update, and delete resources. The API design follows conventions with consistent naming and field formats. Update mask is available for patch endpoints to specify fields for update. API versioning is not synchronized with Airflow releases, and changes go through a deprecation phase. The tool supports various authentication methods and error responses follow RFC 7807 format.

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.

Momentum is an open-source behavioral auditor for backend code that helps developers generate powerful insights into their codebase. It analyzes code behavior, tests it at every git push, and ensures readiness for production. Momentum understands backend code, visualizes dependencies, identifies behaviors, generates test code, runs code in the local environment, and provides debugging solutions. It aims to improve code quality, streamline testing processes, and enhance developer productivity.

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.

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

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.

Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.

UnrealOpenAIPlugin is a comprehensive Unreal Engine wrapper for the OpenAI API, supporting various endpoints such as Models, Completions, Chat, Images, Vision, Embeddings, Speech, Audio, Files, Moderations, Fine-tuning, and Functions. It provides support for both C++ and Blueprints, allowing users to interact with OpenAI services seamlessly within Unreal Engine projects. The plugin also includes tutorials, updates, installation instructions, authentication steps, examples of usage, blueprint nodes overview, C++ examples, plugin structure details, documentation references, tests, packaging guidelines, and limitations. Users can leverage this plugin to integrate powerful AI capabilities into their Unreal Engine projects effortlessly.

WilmerAI is a middleware system designed to process prompts before sending them to Large Language Models (LLMs). It categorizes prompts, routes them to appropriate workflows, and generates manageable prompts for local models. It acts as an intermediary between the user interface and LLM APIs, supporting multiple backend LLMs simultaneously. WilmerAI provides API endpoints compatible with OpenAI API, supports prompt templates, and offers flexible connections to various LLM APIs. The project is under heavy development and may contain bugs or incomplete code.

BentoVLLM is an example project demonstrating how to serve and deploy open-source Large Language Models using vLLM, a high-throughput and memory-efficient inference engine. It provides a basis for advanced code customization, such as custom models, inference logic, or vLLM options. The project allows for simple LLM hosting with OpenAI compatible endpoints without the need to write any code. Users can interact with the server using Swagger UI or other methods, and the service can be deployed to BentoCloud for better management and scalability. Additionally, the repository includes integration examples for different LLM models and tools.

LiteLLM is a tool that allows you to call all LLM APIs using the OpenAI format. This includes Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, and more. LiteLLM manages translating inputs to provider's `completion`, `embedding`, and `image_generation` endpoints, providing consistent output, and retry/fallback logic across multiple deployments. It also supports setting budgets and rate limits per project, api key, and model.

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output (objects). It provides a simple yet robust interface and supports llama-cpp-python and OpenAI endpoints with GBNF grammar support (like the llama-cpp-python server) and the llama.cpp backend server. It works by generating a formal GGML-BNF grammar of the user defined structures and functions, which is then used by llama.cpp to generate text valid to that grammar. In contrast to most GBNF grammar generators it also supports nested objects, dictionaries, enums and lists of them.

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.

I generate API requests from JSON descriptions.

Test Shaman: Guiding software testing with Grug wisdom and humor, balancing fun with practical advice.

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

I craft tests first, then code, validating new features.

An AI conducting 30-question IQ tests, assessing and providing detailed feedback.

I will provide guidance on testing, verification, and validation for QA roles.

Formal and structured interactive IQ test platform.

Assists teachers in marking tests and generating score reports.

How smart are you? Solve it with your friends, find out who is smarter!

Software code tester and debugger

Formal, concise Angular 2 test guide.

Personality test by birthday.

Helps user learn essential vocabulary for GRE test with multiple choice questions

I'm your lab test consultant for blood tests and microbial cultures. How can I help you today?

Creates Application Security Test cases in YAML

Helping you study for cybersecurity certifications and get the job you want!

Expert in advanced data analysis and interpretation

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

Train to pass the Reverse Turing Test!

Your go-to MBTI assessment tool, providing personalized insights.