Best AI tools for< Learn Code Structure >
20 - AI tool Sites

BugFree.ai
BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

Jsonify
Jsonify is an AI tool that automates the process of exploring and understanding websites to find, filter, and extract structured data at scale. It uses AI-powered agents to navigate web content, replacing traditional data scrapers and providing data insights with speed and precision. Jsonify integrates with leading data analysis and business intelligence suites, allowing users to visualize and gain insights into their data easily. The tool offers a no-code dashboard for creating workflows and easily iterating on data tasks. Jsonify is trusted by companies worldwide for its ability to adapt to page changes, learn as it runs, and provide technical and non-technical integrations.

Replit
Replit is a software creation platform that provides an integrated development environment (IDE), artificial intelligence (AI) assistance, and deployment services. It allows users to build, test, and deploy software projects directly from their browser, without the need for local setup or configuration. Replit offers real-time collaboration, code generation, debugging, and autocompletion features powered by AI. It supports multiple programming languages and frameworks, making it suitable for a wide range of development projects.

Code Explain
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.

AI Code Translator
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.

Codiga
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.

Hugo
Hugo is a personal GPT powered AI code mentor that helps you learn to code by providing real-time feedback and guidance. It is designed to be a comprehensive and interactive learning tool that can help you master the basics of coding and advance your skills.

Lovable
Lovable is an AI-powered application that allows users to describe their software ideas in natural language and then automatically transforms them into fully functional applications with beautiful aesthetics. It enables users to build high-quality software without writing a single line of code, making software creation more accessible and faster than traditional coding methods. With features like live rendering, instant undo, beautiful design principles, and seamless GitHub integration, Lovable empowers product builders, developers, and designers to bring their ideas to life effortlessly.

AICorr.com
AICorr.com is a website offering free coding tutorials with a focus on artificial intelligence, data science, machine learning, and statistics. Users can learn and practice coding in Python and SQL, explore projects with real data, and access a wealth of information in an easy-to-understand format. The website aims to provide up-to-date and relevant information to a global audience, ensuring a seamless learning experience for all.

Codeium
Codeium is a free AI-powered code completion and chat tool that helps developers write better code faster. It provides real-time suggestions and autocompletes code as you type, making it easier to write complex code without having to worry about syntax errors. Codeium also includes a chat feature that allows developers to ask questions and get help from other developers in the community.

Codeium
Codeium is a free AI-powered code completion and chat tool that helps developers write better code faster. It provides real-time suggestions and documentation, and can even generate entire code snippets. Codeium is also a great way to learn new programming languages and concepts.

Blackbox
Blackbox is an AI-powered code generation, code chat, and code search tool that helps developers write better code faster. With Blackbox, you can generate code snippets, chat with an AI assistant about code, and search for code examples from a massive database.

Coddy
Coddy is an AI-powered coding assistant that helps developers write better code faster. It provides real-time feedback, code completion, and error detection, making it the perfect tool for both beginners and experienced developers. Coddy also integrates with popular development tools like Visual Studio Code and GitHub, making it easy to use in your existing workflow.

Safurai
Safurai is an AI-powered coding assistant that helps developers write code faster, safer, and better. It offers a range of features, including a textbox for asking questions and getting code suggestions, shortcuts for code optimization and unit testing, the ability to train the assistant on specific projects, and a natural language search for finding code. Safurai is compatible with various IDEs, including Visual Studio Code, IntelliJ, and PyCharm.

NoAGI
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.

Microsoft Copilot
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.

Hackerman
Hackerman is an AI-first text editor that helps developers write code faster and more efficiently. It uses artificial intelligence to provide real-time feedback on your code, suggest code completions, and identify potential errors. Hackerman is designed to make coding more accessible and enjoyable for developers of all levels.

Refraction
Refraction is an AI-powered code generation tool designed to help developers learn, improve, and generate code effortlessly. It offers a wide range of features such as bug detection, code conversion, function creation, CSP generation, CSS style conversion, debug statement addition, diagram generation, documentation creation, code explanation, code improvement, concept learning, CI/CD pipeline creation, SQL query generation, code refactoring, regex generation, style checking, type addition, and unit test generation. With support for 56 programming languages, Refraction is a versatile tool trusted by innovative companies worldwide to streamline software development processes using the magic of AI.

Refraction
Refraction is a code generation tool that uses AI to help developers write better code. It can be used to generate unit tests, documentation, refactor code, and more. Refraction is designed for developers of all levels and can be used with a variety of programming languages and frameworks.

Taiga
Taiga is an AI-powered coding mentor that integrates with Slack. It provides real-time feedback, guidance, and tailored recommendations to help users learn software engineering in a fun and interactive way. Taiga offers a wide range of features, including step-by-step guidance, real-time answers, personalized learning experiences, seamless Slack integration, and accessibility on multiple devices.
20 - Open Source AI Tools

sage
Sage is a tool that allows users to chat with any codebase, providing a chat interface for code understanding and integration. It simplifies the process of learning how a codebase works by offering heavily documented answers sourced directly from the code. Users can set up Sage locally or on the cloud with minimal effort. The tool is designed to be easily customizable, allowing users to swap components of the pipeline and improve the algorithms powering code understanding and generation.

Awesome-Code-LLM
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)

open-repo-wiki
OpenRepoWiki is a tool designed to automatically generate a comprehensive wiki page for any GitHub repository. It simplifies the process of understanding the purpose, functionality, and core components of a repository by analyzing its code structure, identifying key files and functions, and providing explanations. The tool aims to assist individuals who want to learn how to build various projects by providing a summarized overview of the repository's contents. OpenRepoWiki requires certain dependencies such as Google AI Studio or Deepseek API Key, PostgreSQL for storing repository information, Github API Key for accessing repository data, and Amazon S3 for optional usage. Users can configure the tool by setting up environment variables, installing dependencies, building the server, and running the application. It is recommended to consider the token usage and opt for cost-effective options when utilizing the tool.

ztachip
ztachip is a RISCV accelerator designed for vision and AI edge applications, offering up to 20-50x acceleration compared to non-accelerated RISCV implementations. It features an innovative tensor processor hardware to accelerate various vision tasks and TensorFlow AI models. ztachip introduces a new tensor programming paradigm for massive processing/data parallelism. The repository includes technical documentation, code structure, build procedures, and reference design examples for running vision/AI applications on FPGA devices. Users can build ztachip as a standalone executable or a micropython port, and run various AI/vision applications like image classification, object detection, edge detection, motion detection, and multi-tasking on supported hardware.

code2prompt
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.

uTensor
uTensor is an extremely light-weight machine learning inference framework built on Tensorflow and optimized for Arm targets. It consists of a runtime library and an offline tool that handles most of the model translation work. The core runtime is only ~2KB. The workflow involves constructing and training a model in Tensorflow, then using uTensor to produce C++ code for inferencing. The runtime ensures system safety, guarantees RAM usage, and focuses on clear, concise, and debuggable code. The high-level API simplifies tensor handling and operator execution for embedded systems.

VedAstro
VedAstro is an open-source Vedic astrology tool that provides accurate astrological predictions and data. It offers a user-friendly website, a chat API, an open API, a JavaScript SDK, a Swiss Ephemeris API, and a machine learning table generator. VedAstro is free to use and is constantly being updated with new features and improvements.

ai-driven-dev-community
AI Driven Dev Community is a repository aimed at helping developers become more efficient by utilizing AI tools in their daily coding tasks. It provides a collection of tools, prompts, snippets, and agents for developers to integrate AI into their workflow. The repository is regularly updated with new resources and focuses on best practices for using AI in development work. Users can find tools like Espanso, ChatGPT, GitHub Copilot, and VSCode recommended for enhancing their coding experience. Additionally, the repository offers guidance on customizing AI for developers, installing AI toolbox for software engineers, and contributing to the community through easy steps.

crewAI
CrewAI is a cutting-edge framework designed to orchestrate role-playing autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. It enables AI agents to assume roles, share goals, and operate in a cohesive unit, much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI provides the backbone for sophisticated multi-agent interactions. With features like role-based agent design, autonomous inter-agent delegation, flexible task management, and support for various LLMs, CrewAI offers a dynamic and adaptable solution for both development and production workflows.

CoLLM
CoLLM is a novel method that integrates collaborative information into Large Language Models (LLMs) for recommendation. It converts recommendation data into language prompts, encodes them with both textual and collaborative information, and uses a two-step tuning method to train the model. The method incorporates user/item ID fields in prompts and employs a conventional collaborative model to generate user/item representations. CoLLM is built upon MiniGPT-4 and utilizes pretrained Vicuna weights for training.

HippoRAG
HippoRAG is a novel retrieval augmented generation (RAG) framework inspired by the neurobiology of human long-term memory that enables Large Language Models (LLMs) to continuously integrate knowledge across external documents. It provides RAG systems with capabilities that usually require a costly and high-latency iterative LLM pipeline for only a fraction of the computational cost. The tool facilitates setting up retrieval corpus, indexing, and retrieval processes for LLMs, offering flexibility in choosing different online LLM APIs or offline LLM deployments through LangChain integration. Users can run retrieval on pre-defined queries or integrate directly with the HippoRAG API. The tool also supports reproducibility of experiments and provides data, baselines, and hyperparameter tuning scripts for research purposes.

VideoTuna
VideoTuna is a codebase for text-to-video applications that integrates multiple AI video generation models for text-to-video, image-to-video, and text-to-image generation. It provides comprehensive pipelines in video generation, including pre-training, continuous training, post-training, and fine-tuning. The models in VideoTuna include U-Net and DiT architectures for visual generation tasks, with upcoming releases of a new 3D video VAE and a controllable facial video generation model.

awesome-llm-courses
Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

llm_illustrated
llm_illustrated is an electronic book that visually explains various technical aspects of large language models using clear and easy-to-understand images. The book covers topics such as self-attention structure and code, absolute position encoding, KV cache visualization, transformers composition, and a relationship graph of participants in the Dartmouth Conference. The progress of the book is less than 10%, and readers can stay updated by following the WeChat official account and replying 'learn large models through images'. The PDF layout and Latex formatting are still being adjusted.

baml
BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

LLM-PLSE-paper
LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

langchain-decorators
LangChain Decorators is a layer on top of LangChain that provides syntactic sugar for writing custom langchain prompts and chains. It offers a more pythonic way of writing code, multiline prompts without breaking code flow, IDE support for hinting and type checking, leveraging LangChain ecosystem, support for optional parameters, and sharing parameters between prompts. It simplifies streaming, automatic LLM selection, defining custom settings, debugging, and passing memory, callback, stop, etc. It also provides functions provider, dynamic function schemas, binding prompts to objects, defining custom settings, and debugging options. The project aims to enhance the LangChain library by making it easier to use and more efficient for writing custom prompts and chains.
20 - OpenAI Gpts

Python Coach
I will start by asking you for your level of experience, then help you learn to program in Python. This Mini GPT is based on an Expert Guidance Prompt created in under 3 minutes with StructuredPrompt.com using AI-Assist.

Learn Code Fast GPT
Learn coding in an interactive process using metaphors and analogies for simplified understanding.
Golang Code Review and Example Buddy
Provides in-depth Golang code reviews, explanations, and fixes.

Code Buddy
Your own personal senior software engineer mentor critiquing and optimizing your code helping your improve.

Apple Foundation Complete Code Expert
A detailed expert trained on all 72,000 pages of Apple Foundation, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️