Best AI tools for< Find Error >

Wand is an AI-powered tool that helps you find and fix errors in your code. It uses machine learning to identify potential problems and provides suggestions for how to resolve them. Wand can be used with a variety of programming languages, including Python, Java, JavaScript, and C++.

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::l44g5-1727283130745-f99c9f7f28f4) 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::qhrjt-1726765433586-bc18f7adaa0c) 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::lpcgw-1726939089118-f134fdcd683c) for reference. Users are directed to consult 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::k52hk-1728147113444-17b9d56f17fd) 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. Users encountering this error are advised to refer to the documentation for more 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::7crbp-1720289011850-d12041b250e9) for reference. Users are directed to check the documentation for further information and troubleshooting.

SourceAI is an AI-powered code generator that allows users to generate code in any programming language. It is easy to use, even for non-developers, and has a clear and intuitive interface. SourceAI is powered by GPT-3 and Codex, the most advanced AI technology available. It can be used to generate code for a variety of tasks, including calculating the factorial of a number, finding the roots of a polynomial, and translating text from one language to another.

Code Snippets AI is an AI-powered code snippets library for teams. It helps developers master their codebase with contextually-rich AI chats, integrated with a secure code snippets library. Developers can build new features, fix bugs, add comments, and understand their codebase with the help of Code Snippets AI. The tool is trusted by the best development teams and helps developers code smarter than ever. With Code Snippets AI, developers can leverage the power of a codebase aware assistant, helping them write clean, performance optimized code. They can also create documentation, refactor, debug and generate code with full codebase context. This helps developers spend more time creating code and less time debugging errors.

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::22md2-1720772812453-4893618e160a) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the requested deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::ltfvp-1727369324219-e2d8330c3f8d) 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. Users encountering this error are directed to refer to 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::bfgnm-1727111577504-fc9106f5c26a'. Users are directed to refer to the documentation for further information and troubleshooting.

The website page 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::fd55k-1727629228031-7a0d0ffffbbb'. Users are directed to refer to the documentation for further information and troubleshooting.

The website is a simple error page indicating that the requested page is not found. It is a standard HTTP response code that informs users that the server could not find the requested page. The message '404 - Page not found' is displayed to inform users that the page they are trying to access does not exist or has been moved.

Rush Analytics is an all-in-one SEO platform offering a suite of powerful tools for search engine optimization and pay-per-click automation. It provides features such as rank tracking, keyword research, site audit, PBN tools, and more, all aimed at helping users improve their website's visibility and performance. With a focus on automation and analytics, Rush Analytics streamlines SEO tasks and offers valuable insights to enhance online presence and competitiveness. Trusted by top digital brands, Rush Analytics is a comprehensive solution for SEO professionals and marketers seeking efficient and effective tools for their projects.

Essay Grader AI is an AI-powered platform designed to help teachers grade essays efficiently and effectively. It offers features such as creating and managing classes, applying custom rubrics, bulk uploading essays, providing detailed feedback reports, and integrating with Google Classroom. The tool uses AI content detection and summarization to streamline the grading process, saving teachers time and providing actionable insights for student improvement. Essay Grader AI is trusted by over 1,000 schools and aims to simplify grading while maintaining consistency and fairness.

ChatOrDie.ai is an AI-powered platform that allows users to chat with various AI models such as ChatGPT-4, Claude 3, Gemini 1.5, and more. It emphasizes privacy by ensuring that user conversations are anonymous, not tracked, and not used for training AI models. Users can compare different AI models side by side, spot biases, hallucinations, and errors, and access new trending AI models. The platform is designed to leverage the power of AI without compromising user privacy.

WebLead AI is an automated lead generator tool designed to revolutionize how businesses discover and engage potential customers. By leveraging advanced AI technology, WebLead AI streamlines the lead generation process, helping marketers save time, reduce manual errors, and focus on high-value tasks. The tool offers various subscription plans tailored to different business needs, providing features like multiple domain emails, global coverage, industry-specific leads, and verified emails. With a user-friendly interface and 24/7 support, WebLead AI is a must-have for businesses looking to enhance their marketing efforts and drive growth.

The website imgProof is an AI tool that offers an Automated Image Proofreader service. Users can upload images containing text, and the tool will attempt to find and correct spelling and grammatical errors in the text within the image. It provides a convenient solution for individuals or businesses looking to ensure the accuracy of text within images without manual proofreading.

ShellGPT is a command-line productivity tool powered by AI large language models (LLMs). This command-line tool offers streamlined generation of shell commands, code snippets, documentation, eliminating the need for external resources (like Google search). Supports Linux, macOS, Windows and compatible with all major Shells like PowerShell, CMD, Bash, Zsh, etc.

Züs is a high-performance cloud on a fast blockchain offering privacy and configurable uptime. It uses erasure code to distribute data between data and parity servers, allowing flexibility for IT managers to design for security and uptime. Users can easily share encrypted data with business partners through a proxy key sharing protocol. The ecosystem includes apps like Blimp for cloud migration, Vult for personal cloud storage, and Chalk for NFT artists. Other apps include Bolt for secure wallet and staking, Atlus for blockchain explorer, and Chimney for network participation. The QoS protocol challenges providers based on response time, while the privacy protocol enables secure data sharing. Züs supports hybrid and multi-cloud architectures, allowing users to improve regulatory compliance and security requirements.

Airbroke is an open-source error catcher tool designed for modern web applications. It provides a PostgreSQL-based backend with an Airbrake-compatible HTTP collector endpoint and a React-based frontend for error management. The tool focuses on simplicity, maintaining a small database footprint even under heavy data ingestion. Users can ask AI about issues, replay HTTP exceptions, and save/manage bookmarks for important occurrences. Airbroke supports multiple OAuth providers for secure user authentication and offers occurrence charts for better insights into error occurrences. The tool can be deployed in various ways, including building from source, using Docker images, deploying on Vercel, Render.com, Kubernetes with Helm, or Docker Compose. It requires Node.js, PostgreSQL, and specific system resources for deployment.

PromptAgent is a repository for a novel automatic prompt optimization method that crafts expert-level prompts using language models. It provides a principled framework for prompt optimization by unifying prompt sampling and rewarding using MCTS algorithm. The tool supports different models like openai, palm, and huggingface models. Users can run PromptAgent to optimize prompts for specific tasks by strategically sampling model errors, generating error feedbacks, simulating future rewards, and searching for high-reward paths leading to expert prompts.

The Self-Iterative Agent System for Complex Problem Solving is a solution developed for the Alibaba Mathematical Competition (AI Challenge). It involves multiple LLMs engaging in multi-round 'self-questioning' to iteratively refine the problem-solving process and select optimal solutions. The system consists of main and evaluation models, with a process that includes detailed problem-solving steps, feedback loops, and iterative improvements. The approach emphasizes communication and reasoning between sub-agents, knowledge extraction, and the importance of Agent-like architectures in complex tasks. While effective, there is room for improvement in model capabilities and error prevention mechanisms.

BIG-Bench Mistake is a dataset of chain-of-thought (CoT) outputs annotated with the location of the first logical mistake. It was released as part of a research paper focusing on benchmarking LLMs in terms of their mistake-finding ability. The dataset includes CoT traces for tasks like Word Sorting, Tracking Shuffled Objects, Logical Deduction, Multistep Arithmetic, and Dyck Languages. Human annotators were recruited to identify mistake steps in these tasks, with automated annotation for Dyck Languages. Each JSONL file contains input questions, steps in the chain of thoughts, model's answer, correct answer, and the index of the first logical mistake.

Mastering GitHub Copilot for AI Paired Programming is a comprehensive course designed to equip you with the skills and knowledge necessary to harness the power of GitHub Copilot, an AI-driven coding assistant. Through a series of engaging lessons, you will learn how to seamlessly integrate GitHub Copilot into your workflow, leveraging its autocompletion, customizable features, and advanced programming techniques. This course is tailored to provide you with a deep understanding of AI-driven algorithms and best practices, enabling you to enhance code quality and accelerate your coding skills. By embracing the transformative power of AI paired programming, you will gain the tools and confidence needed to succeed in today's dynamic software development landscape.

PromptMage simplifies the process of creating and managing LLM workflows as a self-hosted solution. It offers an intuitive interface for prompt testing and comparison, incorporates version control features, and aims to improve productivity in both small teams and large enterprises. The tool bridges the gap in LLM workflow management, empowering developers, researchers, and organizations to make LLM technology more accessible and manageable for the next wave of AI innovations.

Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.

This repository is a collection of papers on Generative AI Machine Unlearning, categorized based on modality and applications. It includes datasets, benchmarks, and surveys related to unlearning scenarios in generative AI. The repository aims to provide a comprehensive overview of research in the field of machine unlearning for generative models.

关于如何编写大语言模型的prompt的一系列课

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

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 |

A website that tries to make sense of those three-letter airport codes. It provides detailed information about each airport, including its name, location, and a description. The site also includes a search function that allows users to find airports by name, city, or country. Airport content can be found in `/data` in individual files. Use the three-letter airport code as the filename (e.g. `phx.json`). Content in each `json` file: `id` = three-letter code (e.g. phx), `name` = airport name (Sky Harbor International Airport), `city` = primary city name (Phoenix), `state` = state name, if applicable (Arizona), `stateShort` = state abbreviation, if applicable (AZ), `country` = country name (USA), `description` = description, accepts markdown, use * for emphasis on letters, `imageCredit` = name of photographer, `imageCreditLink` = URL of photographer's Flickr page. You can also optionally add for aid in searching: `city2` = another city or country the airport may be known for. Adding a `json` file to `/data` will automatically render it. You do not need to manually add the path anywhere.

Awesome-Lists is a curated list of awesome lists across various domains of computer science and beyond, including programming languages, web development, data science, and more. It provides a comprehensive index of articles, books, courses, open source projects, and other resources. The lists are organized by topic and subtopic, making it easy to find the information you need. Awesome-Lists is a valuable resource for anyone looking to learn more about a particular topic or to stay up-to-date on the latest developments in the field.

Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

This repository contains a collection of tools that can be used with vastai. The tools are free to use, modify and distribute. If you find this useful and wish to donate your welcome to send your donations to the following wallets. BTC 15qkQSYXP2BvpqJkbj2qsNFb6nd7FyVcou XMR 897VkA8sG6gh7yvrKrtvWningikPteojfSgGff3JAUs3cu7jxPDjhiAZRdcQSYPE2VGFVHAdirHqRZEpZsWyPiNK6XPQKAg RVN RSgWs9Co8nQeyPqQAAqHkHhc5ykXyoMDUp USDT(ETH ERC20) 0xa5955cf9fe7af53bcaa1d2404e2b17a1f28aac4f Paypal PayPal.Me/cryptolabsZA

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)

An AI-Powered Tool for Detecting and Correcting Errors in Homework Problems

Assists with Flutter and Dart code generation and debugging

Friendly JSON, HTML, XML validator with detailed advice.

Manuscript editing assistant for writers.

I find and fix missing parentheses in code.

Your recruiting assistant (note, this is purely for entertainment purposes - consult a lawyer for any legal issues) Chat GTP may be prone to errors.

Enhances texts with figurative language, highlights changes, corrects major errors.

Expert in FiveM server development with tips, tricks, and forum searches.

An AI-powered assistant for Laravel developers.

An assistant replying to any question related to the Mac platform: macOS, computers and apps. Visit macexpert.io for human assistance.

Providing information on consumer credit laws, regulations and resources. Because when it comes to credit, what you don't know CAN hurt you.

I'm FlexiSearch Guru, your go-to for SAP Commerce Cloud's flexible search queries.

寻找解决方案的问题解决专家

Expert in WordPress and WooCommerce, using official resources.

I match students with PhD advisors.

I find the best GPT-powered service for you

Assists in finding suitable lawyers based on user needs. Disclaimer - always do your own extra research

Find the perfect match for your design needs

Analyzes manuscripts and recommends journals.

I help you find a Show or Sporting Event on a Streaming Platform or Channel.