Best AI tools for< Understand Code Efficiency >

Respell is an advanced Agentic AI Workflow platform that offers automation for powerful workflows by leveraging cutting-edge AI models from various providers. It provides custom-built agents for research, phone calls, integrations, and more. Users can connect Respell with popular platforms like Gmail, Notion, Slack, Airtable, Salesforce, and more to analyze, understand, and act on data for smarter decision-making. The platform ensures enterprise security with SOC II compliance and offers a human-in-the-loop feature for running Spells, embedding them into dashboards, scheduling runs, or calling them via API. Respell is designed to help teams move faster, make fewer mistakes, and optimize operational workflows for enhanced efficiency.

AI Code Translator is an online tool that allows users to translate code or natural language into multiple programming languages. It is powered by artificial intelligence (AI) and provides intelligent and efficient code translation. With AI Code Translator, developers can save time and effort by quickly converting code between different languages, optimizing their development process.

Figstack is an intelligent coding companion powered by AI, designed to help developers document and understand code more efficiently. It offers a suite of solutions that include features like explaining code in natural language, translating programming languages, automating documentation, and analyzing the time complexity of programs. Figstack aims to simplify the coding process by providing tools that enhance productivity and code readability.

AlphaCode is an AI-powered programming assistant that can help you write code faster and more efficiently. It uses advanced machine learning techniques to understand your code and generate suggestions that can help you improve your code quality and performance.

**bloop** is an AI-powered legacy code modernization tool that helps teams modernize, write, and understand their legacy code. With bloop, you can automatically convert COBOL and Java programs to readable Java code that can be immediately modified and maintained. bloop also provides an AI pair programmer that can help you write COBOL code faster and more efficiently. Additionally, bloop offers a variety of other features to help you understand your codebase, including natural language code navigation, multi-repo search, and regex matching.

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.

Qwen is an AI tool that focuses on developing and releasing various language models, including dense models, coding models, mathematical models, and vision language models. The Qwen family offers open-source models with different parameter ranges to cater to various user needs, such as production use, mobile applications, coding assistance, mathematical problem-solving, and visual understanding of images and videos. Qwen aims to enhance intelligence and provide smarter and more knowledgeable models for developers and users.

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.

Wasps is an AI code review tool that integrates seamlessly into VSCode, providing developers with a fast and efficient way to understand their codebase, detect and fix code issues using AI and Gitsecure. With Wasps, developers can identify and fix buggy & vulnerable code in minutes, receive clear and actionable feedback driven by deep analysis, and get recommendations for potential issues and improvements within their codebase. The tool allows developers to keep coding as usual while Wasps analyzes their code for them, making it easier to maintain code quality and keep bugs out of their code.

Simplescraper is a web scraping tool that allows users to extract data from any website in seconds. It offers the ability to download data instantly, scrape at scale in the cloud, or create APIs without the need for coding. The tool is designed for developers and no-coders, making web scraping simple and efficient. Simplescraper AI Enhance provides a new way to pull insights from web data, allowing users to summarize, analyze, format, and understand extracted data using AI technology.

vizGPT is an AI-powered data visualization tool that simplifies the process of turning complex data into clear insights. The software offers contextual understanding, intelligent conversation, and natural language processing capabilities to help users quickly generate and understand complex visualizations. With real-time responses and contextual memory features, vizGPT provides a seamless data storytelling experience. Users can create visualizations using a no-code GUI with drag-and-drop functionality and leverage powerful data transformation and profiling tools. vizGPT aims to revolutionize data visualization by offering an intuitive and efficient solution for data analysis.

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.

Sourcegraph is a code intelligence platform that helps developers write, fix, and maintain code faster. It uses artificial intelligence to understand the code graph and provide insights that help developers focus on writing and shipping code. Sourcegraph is used by over 2.5 million engineers at companies like Google, Amazon, and Microsoft.

This tool uses AI to explain any piece of code you don't understand. Simply paste the code in the code editor and press "Explain Code" and AI will output a paragraph explaining what the code is doing.

TLDR is an AI-powered IDE plugin that explains code in plain English. It helps developers understand code by providing quick summaries of what a piece of code is doing. The tool supports almost all programming languages and offers a free version for users to try before purchasing. TLDR aims to simplify the understanding of complex code structures and save developers time in comprehending codebases.

Storia AI is an AI tool designed to assist software engineering teams in understanding and generating code. It provides a Perplexity-like chat experience where users can interact with an AI expert that has access to the latest versions of open-source software. The tool aims to improve code understanding and generation by providing responses backed with links to implementations, API references, GitHub issues, and more. Storia AI is developed by a team of natural language processing researchers from Google and Amazon Alexa, with a mission to build the most reliable AI pair programmer for engineering teams.

NoAGI is an AI tool that helps you write better code. It uses natural language processing to understand your code and suggest improvements. NoAGI can help you with a variety of coding tasks, including code generation, code completion, and code refactoring.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code and an ID for reference, along with a suggestion to check the documentation for more information and troubleshooting.

The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::z2jxr-1736614143090-03728368920f'. Users are directed to refer to the documentation for further information and troubleshooting.

AutoKT is an AI-powered application designed for Automatic Knowledge Transfer. It helps in effortless documentation by automatically writing and updating documentation, allowing users to focus on building innovative projects. The tool addresses the challenge of time and bandwidth spent on writing and maintaining documentation in agile workplaces. AutoKT ensures asynchronous knowledge transfer by keeping documentation in sync with code changes and providing a query feature for easy access to information. It is a valuable tool for developers, enabling them to understand legacy code, streamline documentation writing, and facilitate faster onboarding of new team members.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

FastWiki is an enterprise-level artificial intelligence customer service management system. It is a high-performance knowledge base system designed for large-scale information retrieval and intelligent search. Leveraging Microsoft's Semantic Kernel for deep learning and natural language processing, combined with .NET 8 and React framework, it provides an efficient, user-friendly, and scalable intelligent vector search platform. The system aims to offer an intelligent search solution that can understand and process complex queries, assisting users in quickly and accurately obtaining the needed information.

Mo AI Studio is an enterprise-level AI agent running platform that enables the operation of customized intelligent AI agents with system-level capabilities. It supports various IDEs and programming languages, allows modification of multiple files with reasoning, cross-project context modifications, customizable agents, system-level file operations, document writing, question answering, knowledge sharing, and flexible output processors. The platform also offers various setters and a custom component publishing feature. Mo AI Studio is a fusion of artificial intelligence and human creativity, designed to bring unprecedented efficiency and innovation to enterprises.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

Enhance coding efficiency with expert-led GitHub Copilot course for C#/.NET developers. Learn to integrate AI-powered coding assistance, automate testing, and boost collaboration using Visual Studio Code and Copilot Chat. From autocompletion to unit testing, cover essential techniques for cleaner, faster, smarter code.

This repository is part of the Certified Agentic & Robotic AI Engineer program, covering the first quarter of the course work. It focuses on Modern AI Python Programming, emphasizing static typing for robust and scalable AI development. The course includes modules on Python fundamentals, object-oriented programming, advanced Python concepts, AI-assisted Python programming, web application basics with Python, and the future of Python in AI. Upon completion, students will be able to write proficient Modern Python code, apply OOP principles, implement asynchronous programming, utilize AI-powered tools, develop basic web applications, and understand the future directions of Python in AI.

RepoAgent is an LLM-powered framework designed for repository-level code documentation generation. It automates the process of detecting changes in Git repositories, analyzing code structure through AST, identifying inter-object relationships, replacing Markdown content, and executing multi-threaded operations. The tool aims to assist developers in understanding and maintaining codebases by providing comprehensive documentation, ultimately improving efficiency and saving time.

LLM Agentic Tool Mesh is a platform by HPE Athonet that democratizes Generative Artificial Intelligence (Gen AI) by enabling users to create tools and web applications using Gen AI with Low or No Coding. The platform simplifies the integration process, focuses on key user needs, and abstracts complex libraries into easy-to-understand services. It empowers both technical and non-technical teams to develop tools related to their expertise and provides orchestration capabilities through an agentic Reasoning Engine based on Large Language Models (LLMs) to ensure seamless tool integration and enhance organizational functionality and efficiency.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.

DevDocs is a platform designed to simplify the process of digesting technical documentation for software engineers and developers. It automates the extraction and conversion of web content into markdown format, making it easier for users to access and understand the information. By crawling through child pages of a given URL, DevDocs provides a streamlined approach to gathering relevant data and integrating it into various tools for software development. The tool aims to save time and effort by eliminating the need for manual research and content extraction, ultimately enhancing productivity and efficiency in the development process.

autoMate is an AI-powered local automation tool designed to help users automate repetitive tasks and reclaim their time. It leverages AI and RPA technology to operate computer interfaces, understand screen content, make autonomous decisions, and support local deployment for data security. With natural language task descriptions, users can easily automate complex workflows without the need for programming knowledge. The tool aims to transform work by freeing users from mundane activities and allowing them to focus on tasks that truly create value, enhancing efficiency and liberating creativity.

DriveLM is a multimodal AI model that enables autonomous driving by combining computer vision and natural language processing. It is designed to understand and respond to complex driving scenarios using visual and textual information. DriveLM can perform various tasks related to driving, such as object detection, lane keeping, and decision-making. It is trained on a massive dataset of images and text, which allows it to learn the relationships between visual cues and driving actions. DriveLM is a powerful tool that can help to improve the safety and efficiency of autonomous vehicles.

Llama-github is a powerful tool that helps retrieve relevant code snippets, issues, and repository information from GitHub based on queries. It empowers AI agents and developers to solve coding tasks efficiently. With features like intelligent GitHub retrieval, repository pool caching, LLM-powered question analysis, and comprehensive context generation, llama-github excels at providing valuable knowledge context for development needs. It supports asynchronous processing, flexible LLM integration, robust authentication options, and logging/error handling for smooth operations and troubleshooting. The vision is to seamlessly integrate with GitHub for AI-driven development solutions, while the roadmap focuses on empowering LLMs to automatically resolve complex coding tasks.

code2prompt is a command-line tool that converts your codebase into a single LLM prompt with a source tree, prompt templating, and token counting. It automates generating LLM prompts from codebases of any size, customizing prompt generation with Handlebars templates, respecting .gitignore, filtering and excluding files using glob patterns, displaying token count, including Git diff output, copying prompt to clipboard, saving prompt to an output file, excluding files and folders, adding line numbers to source code blocks, and more. It helps streamline the process of creating LLM prompts for code analysis, generation, and other tasks.

Analyzes code for time and memory complexity

To get started, please type "menu" and select an option from the menu by typing the corresponding keyword or number. If at any time you need assistance or wish to ask a question, just type "help" for more options.

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