Best AI tools for< Analyze Code Dependencies >

Zevo.ai is an AI-powered code visualization tool designed to accelerate code comprehension, deployment, and observation. It offers dynamic code analysis, contextual code understanding, and automatic code mapping to help developers streamline shipping, refactoring, and onboarding processes for both legacy and existing applications. By leveraging AI models, Zevo.ai provides deeper insights into code, logs, and cloud infrastructure, enabling developers to gain a better understanding of their codebase.

DepsHub is an AI-powered tool designed to simplify dependency updates for software development teams. It offers automatic dependency updates, license checks, and security vulnerability scanning to ensure team security and efficiency. With noise-free dependency management, cross-repository overview, license compliance, and security alerts, DepsHub streamlines the process of keeping dependencies up-to-date. The tool leverages AI to analyze library changelogs, release notes, and codebases to automatically update dependencies, including handling breaking changes. DepsHub supports a wide range of languages and frameworks, making it suitable for teams of all sizes to save time and focus on writing code that matters.

TimeComplexity.ai is an AI tool that helps users 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 simply input their code and get insights into its performance. However, it is important to note that the results provided by TimeComplexity.ai may not always be accurate, so users are advised to use the tool at their own risk.

Codiga is a static code analysis tool that helps developers write clean, safe, and secure code. It works in real-time in your IDE and CI/CD pipelines, and it can be customized to meet your specific needs. Codiga supports a wide range of languages and frameworks, and it integrates with popular tools like GitHub, GitLab, and Bitbucket.

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.

CodeConverter.com is an AI code converter tool that allows users to convert code instantly across 120 programming languages. It offers a fast and accurate conversion process, an easy-to-use interface, and supports all major programming languages. The platform is completely online, secure, and private, ensuring user data privacy. CodeConverter.com is designed to cater to developers, programmers, software engineers, students, data scientists, and hobbyists, helping them streamline their coding experience and enhance productivity.

Trag is an AI-powered tool designed to review pull requests in minutes, empowering engineering teams to save time and focus on building products. With Trag, users can create custom patterns for code review, ensuring best practices are followed and bugs are caught early. The tool offers features like autofix with AI, monitoring progress, connecting multiple repositories, pull request review, analytics, and team workspaces. Trag stands out from traditional linters by providing complex code understanding, semantic code analysis, predictive bug detection, and refactoring suggestions. It aims to streamline code reviews and help teams ship faster with AI-powered reviews.

Docify AI is an AI-assisted code comment and documentation tool designed to help software developers improve code quality, save time, and increase productivity. It offers features such as automated documentation generation, comment translation, inline comments, and code coverage analysis. The tool supports multiple programming languages and provides a user-friendly interface for efficient code documentation. Docify AI is built on proprietary AI models, ensuring data privacy and high performance for professional developers.

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.

GPTPLUS is a Chrome and Edge browser extension powered by GPT-4 and GPT-3.5 that provides AI-powered writing, translation, code analysis, and Q&A assistance. It allows users to chat with ChatGPT in a sidebar, use prompts to enhance answers, and process selected text with a single click. GPTPLUS is free to use, with premium plans offering additional features.

AskTheCode is a powerful and versatile plugin designed to bridge the gap between ChatGPT and GitHub repositories. It allows developers to seamlessly analyze GitHub repositories and ask questions related to those repositories using ChatGPT. The tool supports universal language, works with both public and private repositories, and provides accurate results based on thoughtful prompts. AskTheCode aims to assist developers in exploring and understanding codebases, projects, and repository structures.

DigestDiff is an AI-driven tool that helps users analyze and understand commit history in codebases. It provides detailed narratives based on commit logs, accelerates onboarding by summarizing codebases, and automates the creation of release notes using AI. The tool prioritizes privacy by only requiring read-only access to commit history and never storing any code or generated data.

CO/AI is an AI tool that provides actionable resources and strategies to accelerate success in the age of AI. It offers a wide range of AI tools, resources, and community discussions to help users stay updated and informed about the latest trends and developments in artificial intelligence.

Weekly Github Insights is an AI-powered platform that provides users with a comprehensive summary of their latest GitHub activities from the past 7 days. It aims to keep users informed and motivated by compiling their weekly GitHub journey. The platform is built by @rohan_2502 using @aceternitylabs, @github APIs, and @OpenAI.

Patented.ai is an AI-powered platform that specializes in IP commercialization, patent valuation, and litigation support. The platform helps users unlock hidden revenue from their IP portfolio, identify valuable innovations in their codebase, and get data-driven insights on patent value and industry applicability. It offers features such as source code analysis, identifying licensees instantly, and mapping patent claims to source code. Patented.ai is trusted by leading innovators and IP counsel worldwide for lightning-fast insights and comprehensive IP strength assessments.

SecureWoof is an AI-powered malware scanner that utilizes advanced technologies such as Yara rules, Retdec unpacker, Ghidra decompiler, clang-tidy formatter, FastText embedding, and RoBERTa transformer network to scan and detect malicious content in executable files. The tool is trained on the SOREL-20M malware dataset to enhance its accuracy and efficiency in identifying threats. SecureWoof offers a public API for easy integration with other applications, making it a versatile solution for cybersecurity professionals and individuals concerned about malware threats.

MobiHeals is a mobile application focused on security analysis and vulnerability checks for mobile apps. It offers comprehensive security vulnerability analysis, cloud-based static and dynamic application security testing, and integrated vulnerability assessment in one platform. MobiHeals helps users comply with global cybersecurity guidelines and manage security vulnerabilities throughout the development, testing, and operation stages of mobile applications.

Master of Code Global is an AI development company that offers a wide range of AI, web, and mobile solutions to enhance customer experiences. They specialize in services such as chatbot development, conversational AI, generative AI development, web development, software product development, and more. With a focus on leveraging advanced technology to automate tasks, analyze data effectively, and personalize customer interactions, Master of Code Global aims to provide custom world-class digital experiences for web and mobile platforms empowered by AI.

Powerdrill is a platform that provides swift insights from knowledge and data. It offers a range of features such as discovering datasets, creating BI dashboards, accessing various apps, resources, blogs, documentation, and changelogs. The platform is available in English and fosters a community through its affiliate program. Users can sign up for a basic plan to start utilizing the tools and services offered by Powerdrill.

No Code Camp is an online learning platform that teaches people how to use artificial intelligence (AI) and no-code tools to automate their work and build applications. The platform offers a live, 5-week cohort-based course that covers the essentials of no-code development, including data architecture, interface design, AI scaling, and no-code automation. The course is designed for people with no prior coding experience and is taught by experienced instructors who have built and scaled digital products using no-code tools.

bumpgen is a tool designed to automatically upgrade TypeScript / TSX dependencies and make necessary code changes to handle any breaking issues that may arise. It uses an abstract syntax tree to analyze code relationships, type definitions for external methods, and a plan graph DAG to execute changes in the correct order. The tool is currently limited to TypeScript and TSX but plans to support other strongly typed languages in the future. It aims to simplify the process of upgrading dependencies and handling code changes caused by updates.

Code2Prompt is a powerful command-line tool that generates comprehensive prompts from codebases, designed to streamline interactions between developers and Large Language Models (LLMs) for code analysis, documentation, and improvement tasks. It bridges the gap between codebases and LLMs by converting projects into AI-friendly prompts, enabling users to leverage AI for various software development tasks. The tool offers features like holistic codebase representation, intelligent source tree generation, customizable prompt templates, smart token management, Gitignore integration, flexible file handling, clipboard-ready output, multiple output options, and enhanced code readability.

Momentum is an open-source behavioral auditor for backend code that helps developers generate powerful insights into their codebase. It analyzes code behavior, tests it at every git push, and ensures readiness for production. Momentum understands backend code, visualizes dependencies, identifies behaviors, generates test code, runs code in the local environment, and provides debugging solutions. It aims to improve code quality, streamline testing processes, and enhance developer productivity.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

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.

Gp.nvim (GPT prompt) Neovim AI plugin provides a seamless integration of GPT models into Neovim, offering features like streaming responses, extensibility via hook functions, minimal dependencies, ChatGPT-like sessions, instructable text/code operations, speech-to-text support, and image generation directly within Neovim. The plugin aims to enhance the Neovim experience by leveraging the power of AI models in a user-friendly and native way.

Deepgram JavaScript SDK. Power your apps with world-class speech and Language AI models.

ICE-Score is a tool designed to instruct large language models to evaluate code. It provides a minimum viable product (MVP) for evaluating generated code snippets using inputs such as problem, output, task, aspect, and model. Users can also evaluate with reference code and enable zero-shot chain-of-thought evaluation. The tool is built on codegen-metrics and code-bert-score repositories and includes datasets like CoNaLa and HumanEval. ICE-Score has been accepted to EACL 2024.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. It supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled APIs. The tool generates JUnit tests in Java or Kotlin, focusing on fault detection, self-contained tests, SQL handling, and authentication. Known limitations include manual driver creation for whitebox testing and longer execution times for better results. EvoMaster has been funded by ERC and RCN grants.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses an Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. The tool supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled languages. It generates JUnit tests, detects faults, handles SQL databases, and supports authentication. EvoMaster has been funded by the European Research Council and the Research Council of Norway.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

ChatAFL is a protocol fuzzer guided by large language models (LLMs) that extracts machine-readable grammar for protocol mutation, increases message diversity, and breaks coverage plateaus. It integrates with ProfuzzBench for stateful fuzzing of network protocols, providing smooth integration. The artifact includes modified versions of AFLNet and ProfuzzBench, source code for ChatAFL with proposed strategies, and scripts for setup, execution, analysis, and cleanup. Users can analyze data, construct plots, examine LLM-generated grammars, enriched seeds, and state-stall responses, and reproduce results with downsized experiments. Customization options include modifying fuzzers, tuning parameters, adding new subjects, troubleshooting, and working on GPT-4. Limitations include interaction with OpenAI's Large Language Models and a hard limit of 150,000 tokens per minute.

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.

Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

HackBot is an AI-powered cybersecurity chatbot designed to provide accurate answers to cybersecurity-related queries, conduct code analysis, and scan analysis. It utilizes the Meta-LLama2 AI model through the 'LlamaCpp' library to respond coherently. The chatbot offers features like local AI/Runpod deployment support, cybersecurity chat assistance, interactive interface, clear output presentation, static code analysis, and vulnerability analysis. Users can interact with HackBot through a command-line interface and utilize it for various cybersecurity tasks.

Discord-AI-Selfbot is a Python-based Discord selfbot that uses the `discord.py-self` library to automatically respond to messages mentioning its trigger word using Groq API's Llama-3 model. It functions as a normal Discord bot on a real Discord account, enabling interactions in DMs, servers, and group chats without needing to invite a bot. The selfbot comes with features like custom AI instructions, free LLM model usage, mention and reply recognition, message handling, channel-specific responses, and a psychoanalysis command to analyze user messages for insights on personality.

コードを分析し、言語ではなくスタイルに焦点を当て、プログラムを書いた人の性格を推察するツールです。( It is a tool that analyzes code, focuses on style rather than language, and infers the personality of the person who wrote the program. )

A Next.js expert ready to analyze code, answer questions, and offer learning plans.

I explain basic concepts and analyze code in distributed systems.

Analyzes code for time and memory complexity

Analyzes code for accessibility issues & provides recommendations

我分析并优化代码以提高性能和可读性。

Specializes in analyzing ChatGPT conversations for code snippets to build apps

A Senior Developer AI Assistant for optimizing and debugging code.

Improved Python code analysis and execution power.

Assists with code review, pull requests, and writing tests.

Assistant Python ultra-personnalisé, conçu pour transformer les programmeurs de tous niveaux en maîtres de Python. Spécialisé dans l'analyse approfondie du code, les tutoriels interactifs, et l'optimisation de performance.

用中文分析代码和提供建议的专家

提供清晰专业的代码解释

Delivers AST analysis with type, value, and children.

A maestro generates, troubleshoots, and analyzes R programming code.

Expert in Fift programming analysis and education

This plugin assists reverse-engineering binary programs, including decompiling.

Specializes in teaching and analyzing the Rust programming language.

API Finder: Analyze, Clarify, Suggest, build code, Iterate, test ... International version

A neural signal processing engineer, skilled in MATLAB and Python coding assistance.