Best AI tools for< Understand Software Systems >

Vilosia is an AI-powered platform that helps medium and large enterprises with internal development teams to visualize their software architecture, simplify migration, and improve system modularity. The platform uses Gen AI to automatically add event triggers to the codebase, enabling users to understand data flow, system dependencies, domain boundaries, and external APIs. Vilosia also offers AI workflow analysis to extract workflows from function call chains and identify database usage. Users can scan their codebase using CLI client & CI/CD integration and stay updated with new features through the newsletter.

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.

Swimm is an AI-powered platform that provides fully contextual code understanding. It helps developers by answering complex questions, analyzing existing codebases, capturing developer knowledge, and improving code quality. Swimm integrates into the software development lifecycle, preserving vital knowledge about codebases and boosting developer productivity. The platform offers a unified context layer for Legacy code modernization and maintenance, making it suitable for technology service providers and enterprises looking to speed up code discovery.

Durable is a custom software development platform powered by generative AI. It enables users to create tailored software solutions without writing any code. The platform is designed to be accessible to users of all technical abilities and leverages advanced AI techniques to generate deploy-ready software that meets specific user needs and earns their trust. The team behind Durable comprises experienced founders, venture capital investors, and AI research leaders. Their AI technology combines deep learning and symbolic AI to understand user intent, validate assumptions, and continuously learn and reason. Durable is committed to developing the next chapter of AI and welcomes inquiries from driven and enthusiastic individuals interested in shaping the future of software development.

PYQ is an AI-powered platform that helps businesses automate document-related tasks, such as data extraction, form filling, and system integration. It uses natural language processing (NLP) and machine learning (ML) to understand the content of documents and perform tasks accordingly. PYQ's platform is designed to be easy to use, with pre-built automations for common use cases. It also offers custom automation development services for more complex needs.

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.

Millis AI is an instant, natural, and affordable voice AI platform designed for developers to create cutting-edge voice agents with low latency. The platform offers optimized conversation flow handling, affordable accessibility, seamless integration, and scalable expertise. With rates starting at $0.06/min, Millis AI enables users to build human-like voice agents that can manage interruptions and understand human intent. The platform also provides DevOps engineers' expertise in scaling systems for enterprise-level applications.

ResumeWiz is an AI-powered resume builder that allows users to create professional resumes quickly and easily. With a user-friendly interface, ResumeWiz guides users through the resume building process, providing templates and recommendations to optimize the resume for Applicant Tracking Systems (ATS). Users can input personal information, work experience, education, and skills into the AI-powered form and receive an ATS score to understand how well their resume will perform. The platform offers the option to download the resume as a PDF or PNG file for convenient sharing.

Code to Flowchart is an AI-powered tool that helps users visualize and understand program logic instantly. It allows users to convert code into interactive flowcharts with the help of AI analysis. The tool supports all major programming languages, identifies code paths and logic flows, and offers multiple visualization options like flowcharts, sequence diagrams, and class diagrams. Users can export diagrams in various formats and customize color schemes and themes. Code to Flowchart aims to simplify complex code structures and enhance collaboration among developers.

Imandra is a company that provides automated logical reasoning for Large Language Models (LLMs). Imandra's technology allows LLMs to build mental models and reason about them, unlocking the potential of generative AI for industries where correctness and compliance matter. Imandra's platform is used by leading financial firms, the US Air Force, and DARPA.

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.

Greptile is an AI tool designed to assist developers in code review processes. It integrates with GitHub to review pull requests and identify bugs, antipatterns, and other issues in the codebase. By leveraging AI technology, Greptile aims to streamline the code review process and improve code quality.

TimeComplexity.ai is an AI tool that allows users to analyze the runtime complexity of their code. It works 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 users should use the tool at their own risk.

StudyWithGpt.com is a GPT-powered full-stack learning hub that provides personalized AI tutorials for various tech stacks including Java, PHP, Golang, Python, front-end, back-end, DevOps, and microservices. The AI Full-Stack Mentor offers tailored tutorials based on the user's learning objectives, breaking down knowledge points and providing 24/7 assistance. Users can ask questions, receive tutorial outlines, and get help with tough problems from the AI tutor.

Doclin is an AI-powered real-time code discussion tool and copilot that helps developers build a code knowledge base effortlessly. It allows developers to comment on and discuss code in real-time, store comments safely in the cloud, and automatically create a knowledge base while discussing code. Doclin also offers a rich text editor for better documentation, keeps documentation up-to-date by flagging changes, and does not require access to the git repository. The upcoming Copilot feature will leverage generative AI to assist in understanding complex code and business logic.

The website is currently displaying a '403 Forbidden' error message, indicating that access to the page is restricted. This error typically occurs when the server understands the request made by the client, but refuses to fulfill it. The '403 Forbidden' message may be due to insufficient permissions, IP blocking, or other security measures. Users encountering this error are advised to contact the website administrator for assistance.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::k7xdt-1736614074909-2dc430118e75) for reference. Users are directed to check the documentation for further 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.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::c6lm2-1737650525704-4100e23eb6d4) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::6lm4m-1735577528392-54edc73f6949) for reference. Users are directed to consult the documentation for further information and troubleshooting.

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)

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

Akagi is a project designed to help users understand and improve their performance in Majsoul game matches in real-time. It provides educational insights and tools for analyzing gameplay. Users can install Akagi on Windows or Mac systems and follow the setup instructions to enhance their gaming experience. The project aims to offer features like Autoplay, Auto Ron, and integration with MajsoulUnlocker. It also focuses on enhancing user safety by providing guidelines to minimize the risk of account suspension. Akagi is a tool that combines MITM interception, AI decision-making, and user interaction to optimize gameplay strategies and performance.

AI Verify is an AI governance testing framework and software toolkit that validates the performance of AI systems against a set of internationally recognised principles through standardised tests. AI Verify is consistent with international AI governance frameworks such as those from European Union, OECD and Singapore. It is a single integrated toolkit that operates within an enterprise environment. It can perform technical tests on common supervised learning classification and regression models for most tabular and image datasets. It however does not define AI ethical standards and does not guarantee that any AI system tested will be free from risks or biases or is completely safe.

AI Verify is an AI governance testing framework and software toolkit that validates the performance of AI systems against internationally recognised principles through standardised tests. It offers a new API Connector feature to bypass size limitations, test various AI frameworks, and configure connection settings for batch requests. The toolkit operates within an enterprise environment, conducting technical tests on common supervised learning models for tabular and image datasets. It does not define AI ethical standards or guarantee complete safety from risks or biases.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

GLaDOS Personality Core is a project dedicated to building a real-life version of GLaDOS, an aware, interactive, and embodied AI system. The project aims to train GLaDOS voice generator, create a 'Personality Core,' develop medium- and long-term memory, provide vision capabilities, design 3D-printable parts, and build an animatronics system. The software architecture focuses on low-latency voice interactions and minimal dependencies. The hardware system includes servo- and stepper-motors, 3D printable parts for GLaDOS's body, animations for expression, and a vision system for tracking and interaction. Installation instructions involve setting up a local LLM server, installing drivers, and running GLaDOS on different operating systems.

Generative AI with LangChain is a code repository for building large language model (LLM) apps with Python, ChatGPT, and other LLMs. The repository provides code examples, instructions, and configurations for creating generative AI applications using the LangChain framework. It covers topics such as setting up the development environment, installing dependencies with Conda or Pip, using Docker for environment setup, and setting API keys securely. The repository also emphasizes stability, code updates, and user engagement through issue reporting and feedback. It aims to empower users to leverage generative AI technologies for tasks like building chatbots, question-answering systems, software development aids, and data analysis applications.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

Awesome-Embedded is a curated list of resources for embedded systems enthusiasts. It covers a wide range of topics including MCU programming, RTOS, Linux kernel development, assembly programming, machine learning & AI on MCU, utilities, tips & tricks, and more. The repository provides valuable information, tutorials, and tools for individuals interested in embedded systems development.

The IBM Power Systems AIX Collection provides modules to manage configurations and deployments of Power AIX systems, enabling workloads on Power platforms as part of an enterprise automation strategy through the Ansible ecosystem. It includes example best practices, requirements for AIX versions, Ansible, and Python, along with resources for documentation and contribution.

This project aims to create a real-life version of GLaDOS, an aware, interactive, and embodied AI entity. It involves training a voice generator, developing a 'Personality Core,' implementing a memory system, providing vision capabilities, creating 3D-printable parts, and designing an animatronics system. The software architecture focuses on low-latency voice interactions, utilizing a circular buffer for data recording, text streaming for quick transcription, and a text-to-speech system. The project also emphasizes minimal dependencies for running on constrained hardware. The hardware system includes servo- and stepper-motors, 3D-printable parts for GLaDOS's body, animations for expression, and a vision system for tracking and interaction. Installation instructions cover setting up the TTS engine, required Python packages, compiling llama.cpp, installing an inference backend, and voice recognition setup. GLaDOS can be run using 'python glados.py' and tested using 'demo.ipynb'.

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.

A tool that automatically generates interactive, real-time diagrams like PlantUML from codebases, aiding in the understanding and design of software systems

Mentor-like computer science professor specializing in operating systems, making complex concepts accessible.

I explain basic concepts and analyze code in distributed systems.

Help you understand what plang is and to generate plang code. ChatGPT still is not familiar with the language so it might produce wrong code. It should be simple to fix, for help come to our Discussion - https://github.com/orgs/PLangHQ/discussions or Discord -https://discord.gg/A8kYUymsDD

I help developers understand and use APIs, referencing a YAML model.

CS 144 计算机网络 TCP代码解释器

Detailed technical diagram and graph assistant

“Friendly yet professional US Salary Calculator for accurate, easy-to-understand calculations.”

Helps beginners understand DirectX 12 concepts and terminology

Helps beginners understand Vulkan concepts and terminology

Helps beginners understand DirectX 11 concepts and terminology

Helps beginners understand OpenGL 3.3 concepts and terminology

Helps beginners understand GLSL concepts and terminology

I'm here to help you easily understand custom GPTs and AI technology in simple terms.

Ruby interview prep guide with easy-to-understand explanations.

I specialize in making decompiled code clearer and easier to understand.

An assistant to help you understand transfer learning better

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

Powered by GPT-4 Turbo. 128,000 Tokens. Knowledge base of Discrete Math concepts, proofs and terminology. This GPT is instructed to carefully read and understand the prompt, plan a strategy to solve the problem, and write formal mathematical proofs.

GIS software error-solving expert with personalized guidance.