Best AI tools for< Get Coding Examples >

Bash Senpai is a terminal assistant powered by ChatGPT that transforms instructions into ready-to-use commands. It provides convenience by allowing users to get answers without leaving the terminal and offers better answers by providing context with questions. The tool also incorporates self-reflection to improve the quality of its responses.

ExplainDev is a platform that allows users to ask and answer technical coding questions. It uses computer vision to retrieve technical context from images or videos. The platform is designed to help developers get the best answers to their technical questions and guide others to theirs.

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.

Ordinary Prompts is a tool that helps users create better prompts for ChatGPT and other AI language models. It provides a library of pre-written prompts that can be used for a variety of tasks, such as generating creative content, getting help with coding, and writing emails. Ordinary Prompts also includes a number of features that make it easy to customize prompts and track your progress.

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.

Zeus Notebook is an AI code assistant designed by Ying Hang Seah. It allows users to run a Python notebook entirely on their browser. Users can enter their OpenAI API key to enable chat functionality. The application is a helpful tool for developers and programmers to get assistance with coding tasks and projects.

Owlbot is an AI-powered chatbot that integrates and interprets data from various sources. It simplifies data analysis and presents insights in a user-friendly format, allowing you to make informed decisions. Owlbot can handle large volumes of data and supports 95 languages. It can be embedded on your website or used via API. Owlbot is designed to be user-friendly and intuitive, making complex data analysis accessible to everyone, regardless of their data expertise.

Pgrammer is an AI-powered platform designed to help users practice coding interview questions with hints and personalized learning experiences. Unlike traditional methods like LeetCode, Pgrammer offers a diverse set of questions for over 20 programming languages, real-time hints, and solution analysis to improve coding skills and knowledge. The platform provides feedback on submitted solutions, helping users ace coding interviews with confidence.

Octoparse is an AI web scraping tool that offers a no-coding solution for turning web pages into structured data with just a few clicks. It provides users with the ability to build reliable web scrapers without any coding knowledge, thanks to its intuitive workflow designer. With features like AI assistance, automation, and template libraries, Octoparse is a powerful tool for data extraction and analysis across various industries.

AllChat is an intelligent conversational AI assistant designed to enhance user interactions and streamline communication processes. It leverages advanced AI algorithms to provide personalized assistance and support in various tasks. With its intuitive interface, AllChat aims to revolutionize the way users engage with technology, offering a seamless and efficient experience. Whether it's answering queries, scheduling appointments, or managing tasks, AllChat is your go-to virtual assistant for all your needs.

Lindy.ai is a platform that allows users to create custom AI assistants to automate tasks. The platform is designed to be easy to use, with no coding required. Lindy.ai offers a variety of pre-built AI assistants for common tasks, such as customer support, sales, and recruiting. Users can also create their own AI assistants from scratch. Lindy.ai integrates with a variety of third-party applications, including CRM systems, email clients, and document management systems.

Replit GPT Assistant is a tool that acts as a Replit-informed assistant, helping developers address their issues. It provides solutions to common problems faced by developers when using Replit, such as lower Node version errors and issues with updating environment variables.

AI Code Reviewer is a tool that uses artificial intelligence to review code. It can help you find bugs, improve code quality, and enforce coding standards.

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.

GlobalSeo is an AI-powered website translation tool that enables users to easily translate their websites into 93 languages, reach a global audience, and improve SEO rankings. The tool offers automatic translation, website localization, and integration with popular search engines. Users can sign up for free, get a demo, and start translating their websites in under 5 minutes. GlobalSeo simplifies the translation process, saves time, and helps businesses expand their online presence globally.

InsightBase is a powerful AI-powered analytics platform that makes it easy for everyone to get insights from their data. With InsightBase, you can ask questions in plain English and get answers in seconds, build powerful dashboards and reports in minutes, and get the most out of your data with the least amount of time, money, and resources.

The website displays a '404 - Page not found' error message, indicating that the requested page does not exist or has been moved. It seems to be a generic error page that users encounter when trying to access a non-existent or relocated webpage.

hirex.ai is an AI tool designed to make job interviews open, fair, and accessible for all. The platform offers the GenAI assistant to help users get interviewed instantly and jump the line to secure their dream job. With no credit card required, users can register for free early access and benefit from faster screening processes by interviewing candidates using the GenAI assistant. The website aims to transform HR and talent acquisition by providing innovative solutions for job seekers and employers.

Magnet is an AI coding assistant that helps product teams fix issues, share AI threads, and organize projects. It integrates with Linear, GitHub, and Notion, and provides auto-suggested files and code files for personalized and accurate AI recommendations. Magnet also offers prompt templates to help users get started and suggests quick fixes for bugs or enhancements.

Interview.study is an AI-powered interview preparation platform that helps candidates practice real interview questions asked by top companies. The platform provides users with instant feedback on their responses, helping them identify areas for improvement and develop stronger answers. Interview.study also offers a variety of features to help candidates prepare for their interviews, including a database of interview questions, a mock interview tool, and a resume builder.

DuckDuckGPT brings the magic of ChatGPT to DDG (powered by GPT-4!). DuckDuckGPT is a browser extension that allows you to use ChatGPT within DuckDuckGo. This means you can ask ChatGPT questions, get help with tasks, and generate creative content, all without leaving DuckDuckGo. DuckDuckGPT is easy to use. Once you have installed the extension, simply type your question into the DuckDuckGo search bar and hit enter. ChatGPT will then generate a response that will appear below the search results. DuckDuckGPT is a powerful tool that can help you with a wide variety of tasks. Here are just a few examples of what you can use it for: * Get help with research * Write essays and other creative content * Translate languages * Get coding help * Answer trivia questions * And much more! DuckDuckGPT is still in development, but it is already a very powerful tool. As GPT-4 continues to improve, DuckDuckGPT will only get better. So if you are looking for a way to make your DuckDuckGo searches more productive, be sure to give DuckDuckGPT a try.

Julep is an advanced platform for creating stateful and functional AI apps powered by large language models. It offers features like statefulness by design, automatic function calling, production-ready deployment, cron-like asynchronous functions, 90+ built-in tools, and the ability to switch between different LLMs easily. Users can build AI applications without the need to write code for embedding, saving, and retrieving conversation history, and can connect to third-party applications using Composio. Julep simplifies the process of getting started with AI apps, whether they are conversational, functional, or agentic.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

CoML (formerly MLCopilot) is an interactive coding assistant for data scientists and machine learning developers, empowered on large language models. It offers an out-of-the-box interactive natural language programming interface for data mining and machine learning tasks, integration with Jupyter lab and Jupyter notebook, and a built-in large knowledge base of machine learning to enhance the ability to solve complex tasks. The tool is designed to assist users in coding tasks related to data analysis and machine learning using natural language commands within Jupyter environments.

Curated Transformers is a transformer library for PyTorch that provides state-of-the-art models composed of reusable components. It supports various transformer architectures, including encoders like ALBERT, BERT, and RoBERTa, and decoders like Falcon, Llama, and MPT. The library emphasizes consistent type annotations, minimal dependencies, and ease of use for education and research. It has been production-tested by Explosion and will be the default transformer implementation in spaCy 3.7.

Burr is a Python library and UI that makes it easy to develop applications that make decisions based on state (chatbots, agents, simulations, etc...). Burr includes a UI that can track/monitor those decisions in real time.

WilmerAI is a middleware system designed to process prompts before sending them to Large Language Models (LLMs). It categorizes prompts, routes them to appropriate workflows, and generates manageable prompts for local models. It acts as an intermediary between the user interface and LLM APIs, supporting multiple backend LLMs simultaneously. WilmerAI provides API endpoints compatible with OpenAI API, supports prompt templates, and offers flexible connections to various LLM APIs. The project is under heavy development and may contain bugs or incomplete code.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

The ChatGPT R package provides a set of features to assist in R coding. It includes addins like Ask ChatGPT, Comment selected code, Complete selected code, Create unit tests, Create variable name, Document code, Explain selected code, Find issues in the selected code, Optimize selected code, and Refactor selected code. Users can interact with ChatGPT to get code suggestions, explanations, and optimizations. The package helps in improving coding efficiency and quality by providing AI-powered assistance within the RStudio environment.

StarCoder2-Instruct is an open-source pipeline that introduces StarCoder2-15B-Instruct-v0.1, a self-aligned code Large Language Model (LLM) trained with a fully permissive and transparent pipeline. It generates instruction-response pairs to fine-tune StarCoder-15B without human annotations or data from proprietary LLMs. The tool is primarily finetuned for Python code generation tasks that can be verified through execution, with potential biases and limitations. Users can provide response prefixes or one-shot examples to guide the model's output. The model may have limitations with other programming languages and out-of-domain coding tasks.

Plandex is an open source, terminal-based AI coding engine designed for complex tasks. It uses long-running agents to break up large tasks into smaller subtasks, helping users work through backlogs, navigate unfamiliar technologies, and save time on repetitive tasks. Plandex supports various AI models, including OpenAI, Anthropic Claude, Google Gemini, and more. It allows users to manage context efficiently in the terminal, experiment with different approaches using branches, and review changes before applying them. The tool is platform-independent and runs from a single binary with no dependencies.

Dravid (DRD) is an advanced, AI-powered CLI coding framework designed to follow user instructions until the job is completed, including fixing errors. It can generate code, fix errors, handle image queries, manage file operations, integrate with external APIs, and provide a development server with error handling. Dravid is extensible and requires Python 3.7+ and CLAUDE_API_KEY. Users can interact with Dravid through CLI commands for various tasks like creating projects, asking questions, generating content, handling metadata, and file-specific queries. It supports use cases like Next.js project development, working with existing projects, exploring new languages, Ruby on Rails project development, and Python project development. Dravid's project structure includes directories for source code, CLI modules, API interaction, utility functions, AI prompt templates, metadata management, and tests. Contributions are welcome, and development setup involves cloning the repository, installing dependencies with Poetry, setting up environment variables, and using Dravid for project enhancements.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

The Agent OS is an experimental framework and runtime to build sophisticated, long running, and self-coding AI agents. We believe that the most important super-power of AI agents is to write and execute their own code to interact with the world. But for that to work, they need to run in a suitable environment—a place designed to be inhabited by agents. The Agent OS is designed from the ground up to function as a long-term computing substrate for these kinds of self-evolving agents.

CodeSpin.AI is a set of open-source code generation tools that leverage large language models (LLMs) to automate coding tasks. With CodeSpin, you can generate code in various programming languages, including Python, JavaScript, Java, and C++, by providing natural language prompts. CodeSpin offers a range of features to enhance code generation, such as custom templates, inline prompting, and the ability to use ChatGPT as an alternative to API keys. Additionally, CodeSpin provides options for regenerating code, executing code in prompt files, and piping data into the LLM for processing. By utilizing CodeSpin, developers can save time and effort in coding tasks, improve code quality, and explore new possibilities in code generation.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

SambaNova AI Starter Kits is a collection of open-source examples and guides designed to facilitate the deployment of AI-driven use cases for developers and enterprises. The kits cover various categories such as Data Ingestion & Preparation, Model Development & Optimization, Intelligent Information Retrieval, and Advanced AI Capabilities. Users can obtain a free API key using SambaNova Cloud or deploy models using SambaStudio. Most examples are written in Python but can be applied to any programming language. The kits provide resources for tasks like text extraction, fine-tuning embeddings, prompt engineering, question-answering, image search, post-call analysis, and more.

AI Agents Framework is a .NET framework built on Semantic Kernel and Orleans for creating and hosting event-driven AI Agents. It is currently in an experimental phase and not recommended for production use. The framework aims to automate requirements engineering, planning, and coding processes using event-driven agents.

CompressAI-Vision is a tool that helps you develop, test, and evaluate compression models with standardized tests in the context of compression methods optimized for machine tasks algorithms such as Neural-Network (NN)-based detectors. It currently focuses on two types of pipeline: Video compression for remote inference (`compressai-remote-inference`), which corresponds to the MPEG "Video Coding for Machines" (VCM) activity. Split inference (`compressai-split-inference`), which includes an evaluation framework for compressing intermediate features produced in the context of split models. The software supports all the pipelines considered in the related MPEG activity: "Feature Compression for Machines" (FCM).

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