Best AI tools for< Debug Ai Agent >

RagaAI Catalyst is a sophisticated AI observability, monitoring, and evaluation platform designed to help users observe, evaluate, and debug AI agents at all stages of Agentic AI workflows. It offers features like visualizing trace data, instrumenting and monitoring tools and agents, enhancing AI performance, agentic testing, comprehensive trace logging, evaluation for each step of the agent, enterprise-grade experiment management, secure and reliable LLM outputs, finetuning with human feedback integration, defining custom evaluation logic, generating synthetic data, and optimizing LLM testing with speed and precision. The platform is trusted by AI leaders globally and provides a comprehensive suite of tools for AI developers and enterprises.

Portkey is a control panel for production AI applications that offers an AI Gateway, Prompts, Guardrails, and Observability Suite. It enables teams to ship reliable, cost-efficient, and fast apps by providing tools for prompt engineering, enforcing reliable LLM behavior, integrating with major agent frameworks, and building AI agents with access to real-world tools. Portkey also offers seamless AI integrations for smarter decisions, with features like managed hosting, smart caching, and edge compute layers to optimize app performance.

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.

Machinet is an AI Agent designed for full-stack software developers. It serves as an AI-based IDE that assists developers in various tasks, such as code generation, terminal access, front-end debugging, architecture suggestions, refactoring, and mentoring. The tool aims to enhance productivity and streamline the development workflow by providing intelligent assistance and support throughout the coding process. Machinet prioritizes security and privacy, ensuring that user data is encrypted, secure, and never stored for training purposes.

Wordware is an AI toolkit that empowers cross-functional teams to build reliable high-quality agents through rapid iteration. It combines the best aspects of software with the power of natural language, freeing users from traditional no-code tool constraints. With advanced technical capabilities, multiple LLM providers, one-click API deployment, and multimodal support, Wordware offers a seamless experience for AI app development and deployment.

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.

LogRocket is a session replay, product analytics, and issue detection platform that helps software teams deliver the best web and mobile experiences. With LogRocket, you can see exactly what users experienced on your app, as well as DOM playback, console and network logs, errors, and performance data. You can also surface the most impactful user issues with JavaScript errors, network errors, stack traces, automatic triaging, and alerting. LogRocket also provides product analytics to help you understand how users are interacting with your app, and UX analytics to help you visualize how users experience your app at both the individual and aggregate level.

ChatGPT 4 Online is an artificial intelligence-based chatbot powered by generative pre-trained transformer (GPT) technology. It responds with human-like natural conversation when you put text prompts or input in it. ChatGPT online version is a state-of-the-art AI language model that lets you enhance your productivity without spending a single penny. It is owned and developed by OpenAI, the artificial intelligence research laboratory, with the mission of advancing digital intelligence to benefit humanity.

SWE Kit is an open-source headless IDE designed for building custom coding agents with state-of-the-art performance. It offers AI-native tools to streamline the coding review process, enhance code quality, and optimize development efficiency. The application supports various agentic frameworks and LLM inference providers, providing a flexible runtime environment for seamless codebase interaction. With features like code analysis, code indexing, and third-party service integrations, SWE Kit empowers developers to create and run coding agents effortlessly.

LangChain is a framework for developing applications powered by large language models (LLMs). It simplifies every stage of the LLM application lifecycle, including development, productionization, and deployment. LangChain consists of open-source libraries such as langchain-core, langchain-community, and partner packages. It also includes LangGraph for building stateful agents and LangSmith for debugging and monitoring LLM applications.

Microsoft Responsible AI Toolbox is a suite of tools designed to assess, develop, and deploy AI systems in a safe, trustworthy, and ethical manner. It offers integrated tools and functionalities to help operationalize Responsible AI in practice, enabling users to make user-facing decisions faster and easier. The Responsible AI Dashboard provides a customizable experience for model debugging, decision-making, and business actions. With a focus on responsible assessment, the toolbox aims to promote ethical AI practices and transparency in AI development.

Whybug is an AI tool designed to help developers debug their code by providing explanations for errors. By utilizing a large language model trained on data from StackExchange and other sources, Whybug can predict the causes of errors and suggest fixes. Users can simply paste an error message and receive detailed explanations on how to resolve the issue. The tool aims to streamline the debugging process and improve code quality.

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

New Relic is an AI monitoring platform that offers an all-in-one observability solution for monitoring, debugging, and improving the entire technology stack. With over 30 capabilities and 750+ integrations, New Relic provides the power of AI to help users gain insights and optimize performance across various aspects of their infrastructure, applications, and digital experiences.

Zazzani AI Buddy is an AI-powered platform that empowers users to create, debug code, write articles, and communicate with AI in multiple languages. It enhances productivity by generating ideas, providing context-specific answers, and eliminating monotony through automated tasks. Users can sign up to receive updates and contribute to the platform's growth. Zazzani AI Buddy aims to streamline workflows and inspire creativity through its innovative AI capabilities.

Code Companion AI is a desktop application powered by OpenAI's ChatGPT, designed to aid by performing a myriad of coding tasks. This application streamlines project management with its chatbot interface that can execute shell commands, generate code, handle database queries and review your existing code. Tasks are as simple as sending a message - you could request creation of a .gitignore file, or deploy an app on AWS, and CodeCompanion.AI does it for you. Simply download CodeCompanion.AI from the website to enjoy all features across various programming languages and platforms.

CodeCompanion.AI is an AI-powered coding companion that helps developers write better code. It provides real-time feedback, suggestions, and documentation, and can even generate code for you. CodeCompanion.AI is designed to make coding faster, easier, and more efficient.

Zazzani AI is a comprehensive AI-powered platform that empowers users to enhance their workflow and unleash their creativity. With a suite of cutting-edge tools, Zazzani AI streamlines tasks, generates high-quality content, and provides real-time assistance. From debugging code to writing articles, generating ideas, and answering questions, Zazzani AI serves as an invaluable companion for professionals, students, and anyone seeking to optimize their productivity.

Athina AI is a comprehensive platform designed to monitor, debug, analyze, and improve the performance of Large Language Models (LLMs) in production environments. It provides a suite of tools and features that enable users to detect and fix hallucinations, evaluate output quality, analyze usage patterns, and optimize prompt management. Athina AI supports integration with various LLMs and offers a range of evaluation metrics, including context relevancy, harmfulness, summarization accuracy, and custom evaluations. It also provides a self-hosted solution for complete privacy and control, a GraphQL API for programmatic access to logs and evaluations, and support for multiple users and teams. Athina AI's mission is to empower organizations to harness the full potential of LLMs by ensuring their reliability, accuracy, and alignment with business objectives.

TimeComplexity.ai is an AI tool that allows users to analyze the runtime complexity of their code. It works seamlessly across different programming languages without the need for headers, imports, or a main statement. Users can input their code and get insights into its performance. However, it is important to note that the results may not always be accurate, so caution is advised when using the tool.

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

Arcadia is an all-in-one enterprise-grade LLMOps platform that provides a unified interface for developers and operators to build, debug, deploy, and manage AI agents. It supports various LLMs, embedding models, reranking models, and more. Built on langchaingo (golang) for better performance and maintainability. The platform follows the operator pattern that extends Kubernetes APIs, ensuring secure and efficient operations.

Agently is a development framework that helps developers build AI agent native application really fast. You can use and build AI agent in your code in an extremely simple way. You can create an AI agent instance then interact with it like calling a function in very few codes like this below. Click the run button below and witness the magic. It's just that simple: python # Import and Init Settings import Agently agent = Agently.create_agent() agent\ .set_settings("current_model", "OpenAI")\ .set_settings("model.OpenAI.auth", {"api_key": ""}) # Interact with the agent instance like calling a function result = agent\ .input("Give me 3 words")\ .output([("String", "one word")])\ .start() print(result) ['apple', 'banana', 'carrot'] And you may notice that when we print the value of `result`, the value is a `list` just like the format of parameter we put into the `.output()`. In Agently framework we've done a lot of work like this to make it easier for application developers to integrate Agent instances into their business code. This will allow application developers to focus on how to build their business logic instead of figure out how to cater to language models or how to keep models satisfied.

AI2Apps is a visual IDE for building LLM-based AI agent applications, enabling developers to efficiently create AI agents through drag-and-drop, with features like design-to-development for rapid prototyping, direct packaging of agents into apps, powerful debugging capabilities, enhanced user interaction, efficient team collaboration, flexible deployment, multilingual support, simplified product maintenance, and extensibility through plugins.

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.

Reasonable Planning AI is a robust design and data-driven AI solution for game developers. It provides an AI Editor that allows creating AI without Blueprints or C++. The AI can think for itself, plan actions, adapt to the game environment, and act dynamically. It consists of Core components like RpaiGoalBase, RpaiActionBase, RpaiPlannerBase, RpaiReasonerBase, and RpaiBrainComponent, as well as Composer components for easier integration by Game Designers. The tool is extensible, cross-compatible with Behavior Trees, and offers debugging features like visual logging and heuristics testing. It follows a simple path of execution and supports versioning for stability and compatibility with Unreal Engine versions.

Langfuse is a powerful tool that helps you develop, monitor, and test your LLM applications. With Langfuse, you can: * **Develop:** Instrument your app and start ingesting traces to Langfuse, inspect and debug complex logs, and manage, version, and deploy prompts from within Langfuse. * **Monitor:** Track metrics (cost, latency, quality) and gain insights from dashboards & data exports, collect and calculate scores for your LLM completions, run model-based evaluations, collect user feedback, and manually score observations in Langfuse. * **Test:** Track and test app behaviour before deploying a new version, test expected in and output pairs and benchmark performance before deploying, and track versions and releases in your application. Langfuse is easy to get started with and offers a generous free tier. You can sign up for Langfuse Cloud or deploy Langfuse locally or on your own infrastructure. Langfuse also offers a variety of integrations to make it easy to connect to your LLM applications.

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.

ControlFlow is a Python framework designed for building agentic AI workflows. It provides a structured approach for defining tasks, assigning specialized AI agents, and orchestrating complex behaviors. By balancing AI autonomy with precise oversight, users can create sophisticated AI-powered applications with confidence. ControlFlow offers a task-centric architecture, structured results with type-safe outputs, specialized agents for efficient problem-solving, ecosystem integration with LangChain models, flexible control over workflows, multi-agent orchestration, and native observability and debugging capabilities.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

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.

Flo AI is a Python framework that enables users to build production-ready AI agents and teams with minimal code. It allows users to compose complex AI architectures using pre-built components while maintaining the flexibility to create custom components. The framework supports composable, production-ready, YAML-first, and flexible AI systems. Users can easily create AI agents and teams, manage teams of AI agents working together, and utilize built-in support for Retrieval-Augmented Generation (RAG) and compatibility with Langchain tools. Flo AI also provides tools for output parsing and formatting, tool logging, data collection, and JSON output collection. It is MIT Licensed and offers detailed documentation, tutorials, and examples for AI engineers and teams to accelerate development, maintainability, scalability, and testability of AI systems.

The Multi-Agent -Custom Automation Engine Solution Accelerator is an AI-driven orchestration system that manages a group of AI agents to accomplish tasks based on user input. It uses a FastAPI backend to handle HTTP requests, processes them through various specialized agents, and stores stateful information using Azure Cosmos DB. The system allows users to focus on what matters by coordinating activities across an organization, enabling GenAI to scale, and is applicable to most industries. It is intended for developing and deploying custom AI solutions for specific customers, providing a foundation to accelerate building out multi-agent systems.

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

Awesome AI-Powered Developer Tools is a curated list of AI-powered developer tools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and more. The repository includes a wide range of tools, from IDEs and Git clients to assistants, agents, app generators, UI generators, snippet generators, documentation tools, code generation tools, agent platforms, OpenAI plugins, search tools, and testing tools. These tools are designed to enhance developer productivity and streamline various development tasks by integrating AI capabilities.

The 'ai-app' repository is a comprehensive collection of tools and resources related to artificial intelligence, focusing on topics such as server environment setup, PyCharm and Anaconda installation, large model deployment and training, Transformer principles, RAG technology, vector databases, AI image, voice, and music generation, and AI Agent frameworks. It also includes practical guides and tutorials on implementing various AI applications. The repository serves as a valuable resource for individuals interested in exploring different aspects of AI technology.

Clean Coder is an AI tool that serves as a 2-in-1 Scrum Master and Developer. It helps users delegate planning, managing, and coding tasks to AI agents. These agents create tasks within Todoist, write code, and test it, enabling users to work on projects with minimal effort and stress. The tool offers features like project supervision, task execution by programming agents, frontend feedback, automatic file linting, file researcher agent, and sensitive files protection. Users can interact with Clean Coder through speech and benefit from advanced techniques for intelligent task execution.

AI Agent Starter Kit is a modern full-stack AI-enabled template using Next.js for frontend and Express.js for backend, with Telegram and OpenAI integrations. It offers AI-assisted development, smart environment variable setup assistance, intelligent error resolution, context-aware code completion, and built-in debugging helpers. The kit provides a structured environment for developers to interact with AI tools seamlessly, enhancing the development process and productivity.

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