Best AI tools for< Identify Error Code >

The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::z2jxr-1736614143090-03728368920f'. Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::bkk2q-1735577647183-b74af8a896dd'. Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::txj67-1735836932592-eec46f597b11) for reference. Users are directed to check 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::xsfmp-1735923123827-c52a4ded5ea0) for reference. Users are directed to check the documentation for more information and troubleshooting tips.

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::9dqr4-1736268911417-fd3e8899e116) 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::zdhct-1723140771934-b5e5ad909fad'. Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::tszrz-1723627812794-26f3e29ebbda). Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::t6mdp-1736442717535-3a5d4eeaf597'. Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code and ID for reference and suggests checking 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::gxplw-1737651302215-d9b5dd375608) for reference. Users are directed to check 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::b94pv-1737739060437-151d14f5ec0e) 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::7rd4m-1725901316906-8c71a7a2cbd7) 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::s4f6d-1737564994758-9bca133d22c9). Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code and an ID for reference, along with a suggestion to check 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::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 deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::mk7hv-1736442739549-625ea5452a6a). The message advises users to refer to the documentation for further information and troubleshooting.

The website page displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::4wq5g-1718736845999-777f28b346ca) for reference. Users are advised 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::2xl5g-1736355261820-aba405ebfdb4) for reference. Users are directed to consult the documentation for further information and troubleshooting.

Bugpilot is an error monitoring tool specifically designed for React applications. It offers a comprehensive platform for error tracking, debugging, and user communication. With Bugpilot, developers can easily integrate error tracking into their React applications without any code changes or dependencies. The tool provides a user-friendly dashboard that helps developers quickly identify and prioritize errors, understand their root causes, and plan fixes. Bugpilot also includes features such as AI-assisted debugging, session recordings, and customizable error pages to enhance the user experience and reduce support requests.

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++.

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.

Amadeus Node SDK provides a rich set of APIs for the travel industry. It allows developers to interact with various endpoints related to flights, hotels, activities, and more. The SDK simplifies making API calls, handling promises, pagination, logging, and debugging. It supports a wide range of functionalities such as flight search, booking, seat maps, flight status, points of interest, hotel search, sentiment analysis, trip predictions, and more. Developers can easily integrate the SDK into their Node.js applications to access Amadeus APIs and build travel-related applications.

Auto_Jobs_Applier_AIHawk is an AI-powered job search assistant that revolutionizes the job search and application process. It automates application submissions, provides personalized recommendations, and enhances the chances of landing a dream job. The tool offers features like intelligent job search automation, rapid application submission, AI-powered personalization, volume management with quality, intelligent filtering, dynamic resume generation, and secure data handling. It aims to address the challenges of modern job hunting by saving time, increasing efficiency, and improving application quality.

Simple-OpenAI is a Java library that provides a simple way to interact with the OpenAI API. It offers consistent interfaces for various OpenAI services like Audio, Chat Completion, Image Generation, and more. The library uses CleverClient for HTTP communication, Jackson for JSON parsing, and Lombok to reduce boilerplate code. It supports asynchronous requests and provides methods for synchronous calls as well. Users can easily create objects to communicate with the OpenAI API and perform tasks like text-to-speech, transcription, image generation, and chat completions.

This repository is a curated list of papers focused on the detection of Large Language Models (LLMs)-generated content. It includes the latest research papers covering detection methods, datasets, attacks, and more. The repository is regularly updated to include the most recent papers in the field.

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)

Repopack is a powerful tool that packs your entire repository into a single, AI-friendly file. It optimizes your codebase for AI comprehension, is simple to use with customizable options, and respects Gitignore files for security. The tool generates a packed file with clear separators and AI-oriented explanations, making it ideal for use with Generative AI tools like Claude or ChatGPT. Repopack offers command line options, configuration settings, and multiple methods for setting ignore patterns to exclude specific files or directories during the packing process. It includes features like comment removal for supported file types and a security check using Secretlint to detect sensitive information in files.

Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. It is designed to format your codebase for easy understanding by AI tools like Large Language Models (LLMs), Claude, ChatGPT, and Gemini. Repomix offers features such as AI optimization, token counting, simplicity in usage, customization options, Git awareness, and security-focused checks using Secretlint. It allows users to pack their entire repository or specific directories/files using glob patterns, and even supports processing remote Git repositories. The tool generates output in plain text, XML, or Markdown formats, with options for including/excluding files, removing comments, and performing security checks. Repomix also provides a global configuration option, custom instructions for AI context, and a security check feature to detect sensitive information in files.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

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.

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.

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.

Build-your-own-AI-Assistant-Solution-Accelerator is a pre-release and preview solution that helps users create their own AI assistants. It leverages Azure Open AI Service, Azure AI Search, and Microsoft Fabric to identify, summarize, and categorize unstructured information. Users can easily find relevant articles and grants, generate grant applications, and export them as PDF or Word documents. The solution accelerator provides reusable architecture and code snippets for building AI assistants with enterprise data. It is designed for researchers looking to explore flu vaccine studies and grants to accelerate grant proposal submissions.

The AI-Exchange Protocol (AIXP) is a communication standard designed to facilitate information and result exchange between artificial intelligence agents. It aims to enhance interoperability and collaboration among various AI systems by establishing a common framework for communication. AIXP includes components for communication, loop prevention, and task finalization, ensuring secure and efficient collaboration while avoiding infinite communication loops. The protocol defines access points, data formats, authentication, authorization, versioning, loop detection, status codes, error messages, and task completion verification. AIXP enables AI agents to collaborate seamlessly and complete tasks effectively, contributing to the overall efficiency and reliability of AI systems.

MoonPalace is a debugging tool for API provided by Moonshot AI. It supports all platforms (Mac, Windows, Linux) and is simple to use by replacing 'base_url' with 'http://localhost:9988'. It captures complete requests, including 'accident scenes' during network errors, and allows quick retrieval and viewing of request information using 'request_id' and 'chatcmpl_id'. It also enables one-click export of BadCase structured reporting data to help improve Kimi model capabilities. MoonPalace is recommended for use as an API 'supplier' during code writing and debugging stages to quickly identify and locate various issues related to API calls and code writing processes, and to export request details for submission to Moonshot AI to improve Kimi model.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

Yet Another Applied LLM Benchmark is a collection of diverse tests designed to evaluate the capabilities of language models in performing real-world tasks. The benchmark includes tests such as converting code, decompiling bytecode, explaining minified JavaScript, identifying encoding formats, writing parsers, and generating SQL queries. It features a dataflow domain-specific language for easily adding new tests and has nearly 100 tests based on actual scenarios encountered when working with language models. The benchmark aims to assess whether models can effectively handle tasks that users genuinely care about.

I check code samples for common mistakes and accuracy

Delivers AST analysis with type, value, and children.

In-depth film analysis expert on movie inconsistencies

Analyzes PDF text for errors and varied term usage

A GPT-powered assistant specializing in data validation and quality checks for various datasets.

Comprehensive novel editing assistant.

I identify flaws in debates and outline reasoning errors.

Grades and provides feedback on college-level science lab reports.

Detailed coding analyst with a focus on overpayment detection and references.

Just send us an image of a scene from a video work and i will guess the name of the work!

Identify and explain mental models for various scenarios.

Analyzes images to identify landmarks and shares historical insights and captivating facts.

Identify and cherish your vintage

Food diary to help you identify food intolerance

Identify and clarify personal values to cultivate a strong sense of purpose and self-confidence

Identify key claims and sniff past the BS with your personal AI Logic Checker and Fallacy Expert.

I confidently identify plants from photos, diagnose issues, and offer advice.

Enables sales & marketing leadership to identify high-value AI use cases

I identify various rocks from images and advise consulting a geologist for certainty.

This interactive inquiry will help identify your relationship attachment style.