Best AI tools for< Test Agents >

Prompt Hippo is an AI tool designed as a side-by-side LLM prompt testing suite to ensure the robustness, reliability, and safety of prompts. It saves time by streamlining the process of testing LLM prompts and allows users to test custom agents and optimize them for production. With a focus on science and efficiency, Prompt Hippo helps users identify the best prompts for their needs.

Hamming is an AI tool designed to help automate voice agent testing and optimization. It offers features such as prompt optimization, automated voice testing, monitoring, and more. The platform allows users to test AI voice agents against simulated users, create optimized prompts, actively monitor AI app usage, and simulate customer calls to identify system gaps. Hamming is trusted by AI-forward enterprises and is built for inbound and outbound agents, including AI appointment scheduling, AI drive-through, AI customer support, AI phone follow-ups, AI personal assistant, and AI coaching and tutoring.

TestArmy is an AI-driven software testing platform that offers an army of testing agents to help users achieve software quality by balancing cost, speed, and quality. The platform leverages AI agents to generate Gherkin tests based on user specifications, automate test execution, and provide detailed logs and suggestions for test maintenance. TestArmy is designed for rapid scaling and adaptability to changes in the codebase, making it a valuable tool for both technical and non-technical users.

MAIHEM is an AI-powered quality assurance platform that helps businesses test and improve the performance and safety of their AI applications. It automates the testing process, generates realistic test cases, and provides comprehensive analytics to help businesses identify and fix potential issues. MAIHEM is used by a variety of businesses, including those in the customer support, healthcare, education, and sales industries.

Elixir is an AI tool designed for observability and testing of AI voice agents. It offers features such as automated testing, call review, monitoring, analytics, tracing, scoring, and reviewing. Elixir helps in simulating realistic test calls, analyzing conversations, identifying mistakes, and debugging issues with audio snippets and call transcripts. It provides detailed traces for complex abstractions, streamlines manual review processes, and allows for simulating thousands of calls for full test coverage. The tool is suitable for monitoring agent performance, detecting anomalies in real-time, and improving conversational systems through human-in-the-loop feedback.

Voiceflow is a powerful, flexible, and collaborative platform for building AI automation. It allows teams of any size to build agents of any scale and complexity, easily. Voiceflow's visual workflow builder is used by developers and designers to collaboratively create, iterate, and ship complex agents. Voiceflow also offers a central CMS for managing all of your agent content, including variables, intents, entities, and knowledge base sources. With Voiceflow, you can integrate with any API or service, share and test prototypes, and launch agents to any interface.

Nunu.ai is an AI application focused on advancing Artificial General Intelligence (AGI) for games. The platform is dedicated to building multimodal gameplay agents that can test and play any game. These agents are vision-based, mimicking human-like interaction with games. Nunu.ai introduces breakthrough capabilities such as interactivity, reporting, and interpretability, revolutionizing Quality Assurance (QA) processes in gaming and beyond.

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.

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.

Langflow is a low-code app builder for RAG and multi-agent AI applications. It is Python-based and agnostic to any model, API, or database. Langflow offers a visual IDE for building and testing workflows, multi-agent orchestration, free cloud service, observability features, and ecosystem integrations. Users can customize workflows using Python and publish them as APIs or export as Python applications.

GitStart is an AI-powered platform that offers Elastic Engineering Capacity by assigning tickets and delivering high-quality production code. It leverages AI agents and a global developer community to increase engineering capacity without hiring more staff. GitStart is supported by top tech leaders and provides solutions for bugs, tech debt, frontend and backend development. The platform aims to empower developers, create economic opportunities, and grow the world's future software talent.

Kusho is an AI-powered tool designed to help software developers build bug-free software efficiently. It offers the capability to transform API specs into exhaustive test suites that seamlessly integrate into the CI/CD pipeline. With KushoAI, developers can generate robust AI-generated test suites, receive AI-analyzed test results, and modify code instantly based on real-time reports. The tool is customizable to meet company's context and understands natural language prompts to produce test case code instantly. KushoAI ensures maximum test coverage in minutes, saves hours of manual effort, and adapts to the codebase to prevent missing any test cases.

TestDriver is an AI-powered testing tool that helps developers automate their testing process. It can be integrated with GitHub and can test anything, right in the GitHub environment. TestDriver is easy to set up and use, and it can help developers save time and effort by offloading testing to AI. It uses Dashcam.io technology to provide end-to-end exploratory testing, allowing developers to see the screen, logs, and thought process as the AI completes its test.

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.

Enhans AI Model Generator is an advanced AI tool designed to help users generate AI models efficiently. It utilizes cutting-edge algorithms and machine learning techniques to streamline the model creation process. With Enhans AI Model Generator, users can easily input their data, select the desired parameters, and obtain a customized AI model tailored to their specific needs. The tool is user-friendly and does not require extensive programming knowledge, making it accessible to a wide range of users, from beginners to experts in the field of AI.

Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.

Celp is a contextually aware AI-driven unit test generation tool designed for Typescript Node.js projects. It intelligently parses and deeply understands your code, saving you time and ensuring code stability. It uses an agentic design pattern to build context through parsing with Abstract Syntax Trees and intermediary AI prompting. Celp focuses on essential context, formulates detailed plans, and automatically runs and resolves tests. It generates unit tests from selection, reuses existing code, and learns as you use it.

Synthetic Users is an AI-powered platform that revolutionizes user research by providing human-like AI participants for user and market research. It leverages advanced AI architecture to create accurate synthetic interviews and surveys, enabling users to run quantitative research at scale in minutes. The platform offers a multi-agent framework for dynamic interactions, continuous learning, and adaptation to mimic real human behaviors, providing valuable insights for various applications.

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.

PromptPanda is an AI Prompt Management System designed to streamline workflow by securely managing prompts. It centralizes company prompts, allowing for efficient retrieval and comparison of new prompts. Users can explore and optimize market-tested prompts, ensuring consistent high-quality outcomes. The tool offers a central prompt repository for easy organization and clarity in AI usage.

Astra.ai is a multimodal agent powered by TEN, showcasing its capabilities in speech, vision, and reasoning through RAG from local documentation. It provides a platform for developing AI agents with features like RTC transportation, extension store, workflow builder, and local deployment. Users can build and test agents locally using Docker and Node.js, with prerequisites including Agora App ID, Azure's speech-to-text and text-to-speech API keys, and OpenAI API key. The platform offers advanced customization options through config files and API keys setup, enabling users to create and deploy their AI agents for various tasks.

Agent Evaluation is a generative AI-powered framework for testing virtual agents. It implements an LLM agent (evaluator) to orchestrate conversations with your own agent (target) and evaluate responses. It supports popular AWS services, allows concurrent multi-turn conversations, defines hooks for additional tasks, and can be used in CI/CD pipelines for faster delivery and stable production environments.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

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.

AgentOps is a toolkit for evaluating and developing robust and reliable AI agents. It provides benchmarks, observability, and replay analytics to help developers build better agents. AgentOps is open beta and can be signed up for here. Key features of AgentOps include: - Session replays in 3 lines of code: Initialize the AgentOps client and automatically get analytics on every LLM call. - Time travel debugging: (coming soon!) - Agent Arena: (coming soon!) - Callback handlers: AgentOps works seamlessly with applications built using Langchain and LlamaIndex.

The Arcade Learning Environment (ALE) is a simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. It is built on top of the Atari 2600 emulator Stella and separates the details of emulation from agent design. The ALE currently supports three different interfaces: C++, Python, and OpenAI Gym.

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

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications. Ollama is designed to be easy to use and accessible to developers of all levels. It is open source and available for free on GitHub.

NotHotDog is an open-source testing framework for evaluating and validating voice and text-based AI agents. It offers a user-friendly interface for creating, managing, and executing tests against AI models. The framework supports WebSocket and REST API, test case management, automated evaluation of responses, and provides a seamless experience for test creation and execution.

Vivaria is a web application tool designed for running evaluations and conducting agent elicitation research. Users can interact with Vivaria using a web UI and a command-line interface. It allows users to start task environments based on METR Task Standard definitions, run AI agents, perform agent elicitation research, view API requests and responses, add tags and comments to runs, store results in a PostgreSQL database, sync data to Airtable, test prompts against LLMs, and authenticate using Auth0.

Agents-Flex is a LLM Application Framework like LangChain base on Java. It provides a set of tools and components for building LLM applications, including LLM Visit, Prompt and Prompt Template Loader, Function Calling Definer, Invoker and Running, Memory, Embedding, Vector Storage, Resource Loaders, Document, Splitter, Loader, Parser, LLMs Chain, and Agents Chain.

This repository contains code for building cooperative embodied agents modularly with large language models. The agents are trained to perform tasks in two different environments: ThreeDWorld Multi-Agent Transport (TDW-MAT) and Communicative Watch-And-Help (C-WAH). TDW-MAT is a multi-agent environment where agents must transport objects to a goal position using containers. C-WAH is an extension of the Watch-And-Help challenge, which enables agents to send messages to each other. The code in this repository can be used to train agents to perform tasks in both of these environments.

Godot RL Agents is an open-source package that facilitates the integration of Machine Learning algorithms with games created in the Godot Engine. It provides interfaces for popular RL frameworks, support for memory-based agents, 2D and 3D games, AI sensors, and is licensed under MIT. Users can train agents in the Godot editor, create custom environments, export trained agents in ONNX format, and utilize advanced features like different RL training frameworks.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

SWE-agent is a tool that turns language models (e.g. GPT-4) into software engineering agents capable of fixing bugs and issues in real GitHub repositories. It achieves state-of-the-art performance on the full test set by resolving 12.29% of issues. The tool is built and maintained by researchers from Princeton University. SWE-agent provides a command line tool and a graphical web interface for developers to interact with. It introduces an Agent-Computer Interface (ACI) to facilitate browsing, viewing, editing, and executing code files within repositories. The tool includes features such as a linter for syntax checking, a specialized file viewer, and a full-directory string searching command to enhance the agent's capabilities. SWE-agent aims to improve prompt engineering and ACI design to enhance the performance of language models in software engineering tasks.

The future of business education: Generate and test ideas in a complex global market simulation, populated by autonomous agents. Powered by the MANNS engine for unparalleled entity autonomy and simulated market forces

I simulate tough Customer Support scenarios for Agent Training.

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