Best AI tools for< Debug Algorithms >

PseudoEditor is an online pseudocode editor that offers a free, fast, and dynamic platform for writing and testing pseudocode. It includes features like syntax highlighting, code saving, and error highlighting to enhance the coding experience. With the ability to save code and resume work from any device, PseudoEditor aims to streamline the process of writing pseudocode and creating algorithms. The platform is supported by ads, ensuring that users can access the editor for free.

AtozAi is an AI application designed to empower developers by providing AI-powered tools that enhance coding efficiency and productivity. The platform offers features such as AI-driven code debugging, efficient code conversion, smart regex generation, comprehensive code explanations, and instant text explanations. AtozAi aims to cover a wide range of coding tasks with specialized AI algorithms, continually expanding its toolkit to make tasks easier, more efficient, and creative for developers.

CodeMate is an AI pair programmer tool designed to help developers write error-free code faster and more efficiently. It offers features such as code analysis, debugging assistance, code refactoring, and code review using advanced AI algorithms and machine learning techniques. CodeMate supports various programming languages and provides a secure environment for developers to work on their projects. With a user-friendly interface and collaborative features, CodeMate aims to streamline the coding process and enhance productivity for individual developers, teams, and enterprises.

AskCodi is an AI coding assistant that helps developers write code more efficiently. It provides real-time suggestions, code completion, and error detection to streamline the coding process. With its advanced algorithms, AskCodi can understand the context of the code and offer relevant recommendations. By leveraging machine learning techniques, AskCodi continuously learns and improves its suggestions to better assist developers in their coding tasks.

Copilot is an AI-powered code completion tool developed by OpenAI. It assists developers in writing code by providing suggestions and completing code snippets based on the context. Copilot uses machine learning algorithms to analyze code patterns and predict the next lines of code, making coding faster and more efficient. With its intuitive interface, Copilot aims to streamline the coding process and enhance developer productivity.

Chat Blackbox is an AI tool that specializes in AI code generation, code chat, and code search. It provides a platform where users can interact with AI to generate code, discuss code-related topics, and search for specific code snippets. The tool leverages artificial intelligence algorithms to enhance the coding experience and streamline the development process. With Chat Blackbox, users can access a wide range of features to improve their coding skills and efficiency.

Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks, algorithms provided by Amazon, or your own algorithms built into SageMaker-compatible Docker images.

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

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.

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.

Rerun is an SDK, time-series database, and visualizer for temporal and multimodal data. It is used in fields like robotics, spatial computing, 2D/3D simulation, and finance to verify, debug, and explain data. Rerun allows users to log data like tensors, point clouds, and text to create streams, visualize and interact with live and recorded streams, build layouts, customize visualizations, and extend data and UI functionalities. The application provides a composable data model, dynamic schemas, and custom views for enhanced data visualization and analysis.

Snaplet is a data management tool for developers that provides AI-generated dummy data for local development, end-to-end testing, and debugging. It uses a real programming language (TypeScript) to define and edit data, ensuring type safety and auto-completion. Snaplet understands database structures and relationships, automatically transforming personally identifiable information and seeding data accordingly. It integrates seamlessly into development workflows, providing data where it's needed most: on local machines, for CI/CD testing, and preview environments.

SourceAI is an AI-powered code generator that allows users to generate code in any programming language. It is easy to use, even for non-developers, and has a clear and intuitive interface. SourceAI is powered by GPT-3 and Codex, the most advanced AI technology available. It can be used to generate code for a variety of tasks, including calculating the factorial of a number, finding the roots of a polynomial, and translating text from one language to another.

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.

Langtail is a platform that helps developers build, test, and deploy AI-powered applications. It provides a suite of tools to help developers debug prompts, run tests, and monitor the performance of their AI models. Langtail also offers a community forum where developers can share tips and tricks, and get help from other users.

CodeMate is an AI pair programmer tool designed to help developers write error-free code faster. It offers features like code navigation, understanding complex codebases, intuitive interface for smarter coding, instant debugging, code refactoring, and AI-powered code reviews. CodeMate supports all programming languages and provides suggestions for code optimizations. The tool ensures the security and privacy of user code and offers different pricing plans for individual developers, teams, and enterprises. Users can interact with their codebase, documentation, and Git repositories using CodeMate Chat. The tool aims to improve code quality and productivity by acting as a co-developer while programming.

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.

Kropply is an AI-powered debugging tool that helps developers fix logic, package, and unit-level bugs in their codebase once they run the code. It integrates with VSCode to provide real-time insights and error correction, streamlining the debugging process and making coding more efficient.

Microsoft Copilot is an AI-powered coding assistant that helps developers write better code, faster. It provides real-time suggestions and code completions, and can even generate entire functions and classes. Copilot is available as a Visual Studio Code extension and as a standalone application.

Cognition is an applied AI lab focused on reasoning. Their first product, Devin, is the first AI software engineer. Cognition is a small team based in New York and the San Francisco Bay Area.

This repository provides a collection of interview questions and answers for algorithm engineers. The questions are organized by topic, and each question includes a detailed explanation of the answer. This repository is a valuable resource for anyone preparing for an algorithm engineering interview.

The vscode-pddl extension provides comprehensive support for Planning Domain Description Language (PDDL) in Visual Studio Code. It enables users to model planning domains, validate them, industrialize planning solutions, and run planners. The extension offers features like syntax highlighting, auto-completion, plan visualization, plan validation, plan happenings evaluation, search debugging, and integration with Planning.Domains. Users can create PDDL files, run planners, visualize plans, and debug search algorithms efficiently within VS Code.

LAMBDA is a code-free multi-agent data analysis system that utilizes large models to address data analysis challenges in complex data-driven applications. It allows users to perform complex data analysis tasks through human language instruction, seamlessly generate and debug code using two key agent roles, integrate external models and algorithms, and automatically generate reports. The system has demonstrated strong performance on various machine learning datasets, enhancing data science practice by integrating human and artificial intelligence.

The Universal Numbers Library is a header-only C++ template library designed for universal number arithmetic, offering alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. It tailors arithmetic types to the application's precision and dynamic range, enabling improved application performance and energy efficiency. The library provides fast implementations of special IEEE-754 formats like quarter precision, half-precision, and quad precision, as well as vendor-specific extensions. It supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval, and adaptive-precision integers, rationals, and floats. The library is suitable for AI, DSP, HPC, and HFT algorithms.

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

TaskWeaver is a code-first agent framework designed for planning and executing data analytics tasks. It interprets user requests through code snippets, coordinates various plugins to execute tasks in a stateful manner, and preserves both chat history and code execution history. It supports rich data structures, customized algorithms, domain-specific knowledge incorporation, stateful execution, code verification, easy debugging, security considerations, and easy extension. TaskWeaver is easy to use with CLI and WebUI support, and it can be integrated as a library. It offers detailed documentation, demo examples, and citation guidelines.

LLM Reasoners is a library that enables LLMs to conduct complex reasoning, with advanced reasoning algorithms. It approaches multi-step reasoning as planning and searches for the optimal reasoning chain, which achieves the best balance of exploration vs exploitation with the idea of "World Model" and "Reward". Given any reasoning problem, simply define the reward function and an optional world model (explained below), and let LLM reasoners take care of the rest, including Reasoning Algorithms, Visualization, LLM calling, and more!

Caissa is a strong, UCI command-line chess engine optimized for regular chess, FRC, and DFRC. It features its own neural network trained with self-play games, supports various UCI options, and provides different EXE versions for different CPU architectures. The engine uses advanced search algorithms, neural network evaluation, and endgame tablebases. It offers outstanding performance in ultra-short games and is written in C++ with modules for backend, frontend, and utilities like neural network trainer and self-play data generator.

AI Gallery is a showcase site built using React and Nextjs for static site generation, featuring interactive visualizations of classic algorithms, classic games implementation, and various interesting widgets. The project utilizes AI assistance from Claude 3.5 and GPT-4 to create components and enhance the development process. It aims to continually add more components with AI assistance, providing a platform for contributors to leverage AI in frontend development.

ddddocr is a Rust version of a simple OCR API server that provides easy deployment for captcha recognition without relying on the OpenCV library. It offers a user-friendly general-purpose captcha recognition Rust library. The tool supports recognizing various types of captchas, including single-line text, transparent black PNG images, target detection, and slider matching algorithms. Users can also import custom OCR training models and utilize the OCR API server for flexible OCR result control and range limitation. The tool is cross-platform and can be easily deployed.

Paperless-AI is an automated document analyzer tool designed for Paperless-ngx users. It utilizes the OpenAI API and Ollama (Mistral, llama, phi 3, gemma 2) to automatically scan, analyze, and tag documents. The tool offers features such as automatic document scanning, AI-powered document analysis, automatic title and tag assignment, manual mode for analyzing documents, easy setup through a web interface, document processing dashboard, error handling, and Docker support. Users can configure the tool through a web interface and access a debug interface for monitoring and troubleshooting. Paperless-AI aims to streamline document organization and analysis processes for users with access to Paperless-ngx and AI capabilities.

The Neutone SDK is a tool designed for researchers to wrap their own audio models and run them in a DAW using the Neutone Plugin. It simplifies the process by allowing models to be built using PyTorch and minimal Python code, eliminating the need for extensive C++ knowledge. The SDK provides support for buffering inputs and outputs, sample rate conversion, and profiling tools for model performance testing. It also offers examples, notebooks, and a submission process for sharing models with the community.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

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 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

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.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

The RAG ChatBot project combines Lama.cpp, Chroma, and Streamlit to build a Conversation-aware Chatbot and a Retrieval-augmented generation (RAG) ChatBot. The RAG Chatbot works by taking a collection of Markdown files as input and provides answers based on the context provided by those files. It utilizes a Memory Builder component to load Markdown pages, divide them into sections, calculate embeddings, and save them in an embedding database. The chatbot retrieves relevant sections from the database, rewrites questions for optimal retrieval, and generates answers using a local language model. It also remembers previous interactions for more accurate responses. Various strategies are implemented to deal with context overflows, including creating and refining context, hierarchical summarization, and async hierarchical summarization.

Translate texts in manga/images. Some manga/images will never be translated, therefore this project is born. * Image/Manga Translator * Samples * Online Demo * Disclaimer * Installation * Pip/venv * Poetry * Additional instructions for **Windows** * Docker * Hosting the web server * Using as CLI * Setting Translation Secrets * Using with Nvidia GPU * Building locally * Usage * Batch mode (default) * Demo mode * Web Mode * Api Mode * Related Projects * Docs * Recommended Modules * Tips to improve translation quality * Options * Language Code Reference * Translators Reference * GPT Config Reference * Using Gimp for rendering * Api Documentation * Synchronous mode * Asynchronous mode * Manual translation * Next steps * Support Us * Thanks To All Our Contributors :

Golang, algorithms, data structures & HTMX expert

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Expert in generating and debugging Neo4j code, with explanations on graph database principles.