Best AI tools for< Fix Code Errors >

Roboweb is an AI assistant for exploratory programming that embeds OpenAI's ChatGPT in JupyterLab to create an ideal environment for exploratory programming. It provides users with a seamless experience in fixing errors, deploying applications on Kubernetes, and enhancing their coding skills through interactive chat functionalities.

ChatGPT Deutsch is an intelligent chatbot tool developed by OpenAI that allows users to interact online with the large GPT language model through the OpenAI API function, enabling them to create text in AI language. The tool is equipped with many features to perform various tasks such as language translation, content creation, and programming support in just a few seconds. ChatGPT Deutsch offers unlimited conversation possibilities based on vast and reliable data sources from various information channels. Users of GPT Deutsch can start asking questions immediately without incurring any fees or complicated account registration.

Whybug is an AI tool designed to help developers debug their code by explaining errors. It utilizes a large language model trained on data from StackExchange and other sources to predict the causes of errors and provide solutions. Users can input error messages and receive explanations along with example fixes in code.

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++.

ProMind AI is an AI-powered tool that helps you generate text, code, and other content. It can be used for a variety of tasks, including writing tweets, creating blog posts, and generating code snippets. ProMind AI is easy to use and can help you save time and effort on your writing projects.

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.

Kropply is an AI-powered debugging tool that helps developers fix logic, package, and unit-level bugs in their codebase once they run the code. It integrates with VSCode to provide real-time insights and error correction, streamlining the debugging process and making coding more efficient.

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.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

Pandalyst is an AI-powered tool that helps users write SQL queries faster and more efficiently. It provides an intuitive interface and uses AI to generate high-performing SQL queries without errors, regardless of the user's skill level. Pandalyst is suitable for both SQL beginners and experienced users and can be accessed through a web browser on any device. It prioritizes data security and does not store any data in its system.

Commenter.ai is an AI-powered tool that helps you write better comments on code. It can help you identify and fix common coding errors, suggest improvements to your code, and even generate new code for you. Commenter.ai is a great way to improve the quality of your code and make it more readable and maintainable.

The website seems to be experiencing an application error, which indicates a technical issue preventing the proper functioning of the application. An application error typically occurs when there is a bug in the code or a server-related problem. Users encountering this message may need to refresh the page, clear their cache, or contact the website's support team for assistance.

The website appears to have encountered a 404 error, indicating that the page being requested is not found on the server. A 404 error typically occurs when a user tries to access a webpage that no longer exists or has been moved. It is a standard HTTP response code that informs the user that the server could not find the requested page. Users may encounter a 404 error due to mistyped URLs, broken links, or website restructuring. To resolve the issue, users can try refreshing the page, checking the URL for errors, or contacting the website administrator for assistance.

AI2SQL is an AI-powered SQL query builder and generator that allows users to create, optimize, and automate SQL queries without the need for expert skills. The tool transforms natural language instructions into precise SQL and NoSQL queries, simplifying database design and enhancing query performance. With features like Text2SQL, SQL Query Fixer, SQL Query Explainer, and SQL Query Optimizer, AI2SQL offers a streamlined solution for diverse SQL tasks. Trusted by industry leaders, AI2SQL saves time, reduces errors, and improves productivity for data analysts and developers.

The website seems to be experiencing an application error, which indicates a technical issue with the application. It is likely that users are unable to access the intended content or functionality due to this error. Application errors can occur for various reasons, such as bugs in the code, server issues, or database problems. Resolving application errors typically requires troubleshooting by developers or technical support teams to identify and fix the underlying cause.

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.

Programming Helper is a tool that helps you code faster with the help of AI. It can generate code, test code, and explain code. It also has a wide range of other features, such as a function from description, text description to SQL command, and code to explanation. Programming Helper is a valuable tool for any programmer, regardless of their skill level.

DecodeAI is an experimental concept for an automatic blog about AI, generated by AI and curated by human. The blog mainly focuses on AI-related GitHub open-source repositories but is not limited to that. It features tools like Cody, an AI coding assistant, Jan, an open-source offline AI desktop tool, and Open Interpreter, which allows language models to execute code locally. DecodeAI aims to provide valuable insights and resources for developers interested in AI technologies.

Cmd J – ChatGPT for Chrome is a Chrome extension that allows users to use ChatGPT on any tab without having to copy and paste. It offers a variety of features to help users improve their writing, generate blog posts, crush coding issues, boost their social engagement, and fix code bugs faster. The extension is easy to use and can be accessed with a simple keyboard shortcut.

Sourcegraph is a code intelligence platform that helps developers write, fix, and maintain code faster. It uses artificial intelligence to understand the code graph and provide insights that help developers focus on writing and shipping code. Sourcegraph is used by over 2.5 million engineers at companies like Google, Amazon, and Microsoft.

ChatGPT-VSCode is a Visual Studio Code integration that allows users to prompt OpenAI's GPT-4, GPT-3.5, GPT-3, and Codex models within the editor. It offers features like using improved models via OpenAI API Key, Azure OpenAI Service deployments, generating commit messages, storing conversation history, explaining and suggesting fixes for compile-time errors, viewing code differences, and more. Users can customize prompts, quick fix problems, save conversations, and export conversation history. The extension is designed to enhance developer experience by providing AI-powered assistance directly within VS Code.

Micro Agent is an AI tool designed to write and fix code for users by generating code that passes specified tests or matches design screenshots. It aims to streamline the code generation process by leveraging AI capabilities to iterate and improve code until desired outcomes are achieved. The tool focuses on test-driven development and provides interactive features for user feedback. Micro Agent is not intended to be a comprehensive development tool but rather a specialized agent for code generation and iteration.

Awesome AI-Powered Developer Tools is a curated list of AI-powered developer tools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and more. The repository includes a wide range of tools, from IDEs and Git clients to assistants, agents, app generators, UI generators, snippet generators, documentation tools, code generation tools, agent platforms, OpenAI plugins, search tools, and testing tools. These tools are designed to enhance developer productivity and streamline various development tasks by integrating AI capabilities.

gen.nvim is a tool that allows users to generate text using Language Models (LLMs) with customizable prompts. It requires Ollama with models like `llama3`, `mistral`, or `zephyr`, along with Curl for installation. Users can use the `Gen` command to generate text based on predefined or custom prompts. The tool provides key maps for easy invocation and allows for follow-up questions during conversations. Additionally, users can select a model from a list of installed models and customize prompts as needed.

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.

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)

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.

CodeCompanion.nvim is a Neovim plugin that provides a Copilot Chat experience, adapter support for various LLMs, agentic workflows, inline code creation and modification, built-in actions for language prompts and error fixes, custom actions creation, async execution, and more. It supports Anthropic, Ollama, and OpenAI adapters. The plugin is primarily developed for personal workflows with no guarantees of regular updates or support. Users can customize the plugin to their needs by forking the project.

Репозиторий содержит информацию о применении искусственного интеллекта в разработке программного обеспечения. В частности, рассматриваются кейсы использования ChatGPT и других языковых моделей для автоматизации задач разработки, таких как написание кода, тестирование, рефакторинг и генерация документации.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

ChatGPT-Arcana is an Emacs package that allows users to interact with ChatGPT directly from Emacs, enabling tasks such as chatting with GPT, operating on code or text, generating eshell commands from natural language, fixing errors, writing commit messages, and creating agents for web search and code evaluation. The package requires an API key from OpenAI's GPT-3 model and offers various interactive functions for enhancing productivity within Emacs.

Instructor is a tool designed to structure outputs from OpenAI and other OSS LLMs by coaxing them to return JSON that maps to a provided Ecto schema. It allows for defining validation logic to guide LLMs in making corrections, and supports automatic retries. Instructor is primarily used with the OpenAI API but can be extended to work with other platforms. The tool simplifies usage by creating an ecto schema, defining a validation function, and making calls to chat_completion with instructions for the LLM. It also offers features like max_retries to fix validation errors iteratively.

wtf.nvim is a Neovim plugin that enhances diagnostic debugging by providing explanations and solutions for code issues using ChatGPT. It allows users to search the web for answers directly from Neovim, making the debugging process faster and more efficient. The plugin works with any language that has LSP support in Neovim, offering AI-powered diagnostic assistance and seamless integration with various resources for resolving coding problems.

Thread is an AI-powered Jupyter alternative that integrates an AI copilot into your editing experience. It offers a familiar Jupyter Notebook editing experience with features like natural language code edits, generating cells to answer questions, context-aware chat sidebar, and automatic error explanations or fixes. The tool aims to enhance code editing and data exploration by providing a more interactive and intuitive experience for users. Thread can be used for free with Ollama or your own API key, and it runs locally for convenience and privacy.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=