Best AI tools for< Issue Engineer >

Stepsize AI is an AI-powered reporting tool for software development teams. It analyzes issue tracker activity to generate automated weekly updates on team and project progress. Stepsize AI provides metrics with automatic commentary, project-level AI insights, and intelligent delivery risk surfacing. It offers tailored insights, complete visibility, and unified focus, helping teams stay aligned and make timely decisions.

DigiCord is an AI-powered Discord bot that provides access to a wide range of large language models (LLMs) such as GPT-3.5, GPT-4, Claude, and more. It allows users to converse with AI, generate content, analyze images and data, and perform various tasks, all within the Discord server environment. DigiCord aims to democratize AI tools and technologies, making them more accessible, cost-efficient, and user-friendly for a diverse range of users, from students and digital artists to software engineers and entrepreneurs.

Elessar is an AI-powered platform designed to enhance engineering productivity by providing automatic documentation, reporting, and visibility for development teams. It seamlessly integrates with existing ecosystems, generates pull request changelogs, automates Notion documentation, offers Slack bot functionality, provides VS Code extension for easy code understanding, and links with Linear for issue tracking. Elessar ensures data privacy and security by following SOC II compliant policies and encrypting data at rest and in transit. It does not use data for training AI models. With Elessar, organizations can streamline communication, improve visibility, and boost productivity.

Devin AI, developed by Cognition Labs, is the world's first fully autonomous AI software engineer. It streamlines software development by handling complex tasks, allowing engineers to focus on more challenging aspects. Devin AI possesses advanced programming skills, can manage complex tasks, understands and learns contextually, integrates with developer tools, and offers collaborative features. It can build and deploy applications, detect and fix bugs, contribute to open-source projects, train AI models, and handle GitHub repositories. Devin AI has demonstrated strong performance in issue resolution, surpassing previous AI models. It is currently in early access, with plans for future enhancements and integration with various development tools and platforms.

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.

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 is currently experiencing a temporary service outage, indicated by the '503 Service Temporarily Unavailable' error message. This error typically occurs when the server is unable to handle the request due to maintenance, overload, or other issues. The 'nginx' reference suggests that the website is using the Nginx web server software. Users encountering this error are advised to wait and try accessing the site later.

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 is a simple error page indicating that the requested page is not found. It provides a message stating '404 - Not found' and 'Oops! Page not found'. The user is advised to go back home by clicking a link provided on the page.

LogRocket is a session replay, product analytics, and issue detection platform that helps software teams deliver the best web and mobile experiences. With LogRocket, you can see exactly what users experienced on your app, as well as DOM playback, console and network logs, errors, and performance data. You can also surface the most impactful user issues with JavaScript errors, network errors, stack traces, automatic triaging, and alerting. LogRocket also provides product analytics to help you understand how users are interacting with your app, and UX analytics to help you visualize how users experience your app at both the individual and aggregate level.

The website seems to be experiencing an application error, which indicates a technical issue preventing the proper functioning of the application. An application error can occur due to various reasons such as bugs in the code, server issues, or incorrect user inputs. It is essential for the website administrators to investigate and resolve the error promptly to ensure a seamless user experience.

The website is currently experiencing a temporary pause in deployment. It seems to be encountering an issue with the deployment process, resulting in a temporary halt. Users may need to wait until the issue is resolved for the deployment to resume successfully.

The website seems to be experiencing a technical issue as it is displaying a '500 Internal Server Error'. This error typically indicates a problem with the server hosting the website, preventing it from fulfilling the request made by the user. The '500 Internal Server Error' is a generic error message that does not provide specific details about the underlying issue. Users encountering this error are advised to wait and refresh the page later, as it may be a temporary problem that the website administrators are working to resolve.

SocialGuard.co is a website that currently faces an issue with an invalid SSL certificate, causing an error code 526. The website is hosted on Cloudflare and provides information on the SSL certificate error. Users visiting the site are advised to wait a few minutes if they encounter the error. For website owners, the error indicates a problem with the SSL certificate validation, possibly due to expiration or incorrect configuration. The site recommends contacting the hosting provider to resolve the issue.

The website appears to be encountering an application error, specifically a client-side exception. This error message indicates that there is an issue with the code running on the user's browser, prompting them to check the browser console for more detailed information. The website may be experiencing technical difficulties that need to be addressed by the developers to ensure proper functionality and user experience.

The website encountered an unexpected condition that prevented it from fulfilling the request. It is displaying a 500 Internal Server Error message, indicating a server-side issue. This error typically occurs due to misconfigurations, server overload, or software bugs. Users may need to wait for the website administrators to resolve the problem.

Simpleblog.ai is a website that unfortunately experienced a connection timeout issue, resulting in an Error code 522. The error occurred due to a timeout between Cloudflare's network and the origin web server, preventing the web page from being displayed. Visitors are advised to try accessing the website again after a few minutes, while website owners are encouraged to contact their hosting provider for assistance in resolving the issue. The error code 522 typically indicates that the request was able to connect to the web server but did not complete, often due to resource constraints on the server.

Myple is an AI application that enables users to build, scale, and secure AI applications with ease. It provides production-ready AI solutions tailored to individual needs, offering a seamless user experience. With support for multiple languages and frameworks, Myple simplifies the integration of AI through open-source SDKs. The platform features a clean interface, keyboard shortcuts for efficient navigation, and templates to kickstart AI projects. Additionally, Myple offers AI-powered tools like RAG chatbot for documentation, Gmail agent for email notifications, and AskFeynman for physics-related queries. Users can connect their favorite tools and services effortlessly, without any coding. Joining the beta program grants early access to new features and issue resolution prioritization.

Arize AI is an AI observability tool designed to monitor and troubleshoot AI models in production. It provides configurable and sophisticated observability features to ensure the performance and reliability of next-gen AI stacks. With a focus on ML observability, Arize offers automated setup, a simple API, and a lightweight package for tracking model performance over time. The tool is trusted by top companies for its ability to surface insights, simplify issue root causing, and provide a dedicated customer success manager. Arize is battle-hardened for real-world scenarios, offering unparalleled performance, scalability, security, and compliance with industry standards like SOC 2 Type II and HIPAA.

BlazeMeter by Perforce is an AI-powered continuous testing platform designed to automate testing processes and enhance software quality. It offers effortless test creation, seamless test execution, instant issue analysis, and self-sustaining maintenance. BlazeMeter provides a comprehensive solution for performance, functional, scriptless, API testing, and monitoring, along with test data and service virtualization. The platform enables teams to speed up digital transformation, shift quality left, and streamline DevOps practices. With AI analytics, scriptless test creation, and UX testing capabilities, BlazeMeter empowers users to drive innovation, accuracy, and speed in their test automation efforts.

Ahnlich is a tool that provides multiple components for storing and searching similar vectors using linear or non-linear similarity algorithms. It includes 'ahnlich-db' for in-memory vector key value store, 'ahnlich-ai' for AI proxy communication, 'ahnlich-client-rs' for Rust client, and 'ahnlich-client-py' for Python client. The tool is not production-ready yet and is still in testing phase, allowing AI/ML engineers to issue queries using raw input such as images/text and features off-the-shelf models for indexing and querying.

Tegon is an open-source AI-First issue tracking tool designed for engineering teams. It aims to simplify task management by leveraging AI and integrations to automate task creation, prioritize tasks, and enhance bug resolution. Tegon offers features like issues tracking, automatic title generation, AI-generated labels and assignees, custom views, and upcoming features like sprints and task prioritization. It integrates with GitHub, Slack, and Sentry to streamline issue tracking processes. Tegon also plans to introduce AI Agents like PR Agent and Bug Agent to enhance product management and bug resolution. Contributions are welcome, and the product is licensed under the MIT License.

Ape is an AI prompt engineer tool powered by the open-source library 'ape-core', developed by Weavel. It allows users to generate AI prompts efficiently and effectively. The tool is designed to enhance productivity by providing syntax highlighting for '.prompt' files and welcoming contributions to improve its capabilities and performance. Users can seek help and support through the issue tracker or join the Ape community Discord server. Ape is licensed under the MIT License and credits Stanford NLP's DSPy project for inspiration.

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 |

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

The AI Engineering Hub is a repository that provides in-depth tutorials on LLMs and RAGs, real-world AI agent applications, and examples to implement, adapt, and scale in projects. It caters to beginners, practitioners, and researchers, offering resources for all skill levels to experiment and succeed in AI engineering.

Bedrock Engineer is an autonomous software development agent application that utilizes Amazon Bedrock. It allows users to customize, create/edit files, execute commands, search the web, use a knowledge base, utilize multi-agents, generate images, and more. The tool provides an interactive chat interface with AI agents, file system operations, web search capabilities, project structure management, code analysis, code generation, data analysis, agent and tool customization, chat history management, and multi-language support. Users can select and customize agents, choose from various tools like file system operations, web search, Amazon Bedrock integration, and system command execution. Additionally, the tool offers features for website generation, connecting to design system data sources, AWS Step Functions ASL definition generation, diagram creation using natural language descriptions, and multi-language support.

This repository provides a collection of interview questions and answers for algorithm engineers. The questions are organized by topic, and each question includes a detailed explanation of the answer. This repository is a valuable resource for anyone preparing for an algorithm engineering interview.

This repository provides a comprehensive collection of methodologies, tools, and step-by-step instructions for successful training of large language models (LLMs) and multi-modal models. It is a technical resource suitable for LLM/VLM training engineers and operators, containing numerous scripts and copy-n-paste commands to facilitate quick problem-solving. The repository is an ongoing compilation of the author's experiences training BLOOM-176B and IDEFICS-80B models, and currently focuses on the development and training of Retrieval Augmented Generation (RAG) models at Contextual.AI. The content is organized into six parts: Insights, Hardware, Orchestration, Training, Development, and Miscellaneous. It includes key comparison tables for high-end accelerators and networks, as well as shortcuts to frequently needed tools and guides. The repository is open to contributions and discussions, and is licensed under Attribution-ShareAlike 4.0 International.

The Prompt Engineering Holy Grail repository is a curated resource for prompt engineering enthusiasts, providing essential resources, tools, templates, and best practices to support learning and working in prompt engineering. It covers a wide range of topics related to prompt engineering, from beginner fundamentals to advanced techniques, and includes sections on learning resources, online courses, books, prompt generation tools, prompt management platforms, prompt testing and experimentation, prompt crafting libraries, prompt libraries and datasets, prompt engineering communities, freelance and job opportunities, contributing guidelines, code of conduct, support for the project, and contact information.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

Dewhale is a GitHub-Powered AI tool designed for effortless development. It utilizes prompt engineering techniques under the GPT-4 model to issue commands, allowing users to generate code with lower usage costs and easy customization. The tool seamlessly integrates with GitHub, providing version control, code review, and collaborative features. Users can join discussions on the design philosophy of Dewhale and explore detailed instructions and examples for setting up and using the tool.

LLM4AD is an open-source Python-based platform leveraging Large Language Models (LLMs) for Automatic Algorithm Design (AD). It provides unified interfaces for methods, tasks, and LLMs, along with features like evaluation acceleration, secure evaluation, logs, GUI support, and more. The platform was originally developed for optimization tasks but is versatile enough to be used in other areas such as machine learning, science discovery, game theory, and engineering design. It offers various search methods and algorithm design tasks across different domains. LLM4AD supports remote LLM API, local HuggingFace LLM deployment, and custom LLM interfaces. The project is licensed under the MIT License and welcomes contributions, collaborations, and issue reports.

Dash AI is an open-source coding assistant for Flutter developers. It is designed to not only write code but also run and debug it, allowing it to assist beyond code completion and automate routine tasks. Dash AI is powered by Gemini, integrated with the Dart Analyzer, and specifically tailored for Flutter engineers. The vision for Dash AI is to create a single-command assistant that can automate tedious development tasks, enabling developers to focus on creativity and innovation. It aims to assist with the entire process of engineering a feature for an app, from breaking down the task into steps to generating exploratory tests and iterating on the code until the feature is complete. To achieve this vision, Dash AI is working on providing LLMs with the same access and information that human developers have, including full contextual knowledge, the latest syntax and dependencies data, and the ability to write, run, and debug code. Dash AI welcomes contributions from the community, including feature requests, issue fixes, and participation in discussions. The project is committed to building a coding assistant that empowers all Flutter developers.

OpenDevin is an open-source project aiming to replicate Devin, an autonomous AI software engineer capable of executing complex engineering tasks and collaborating actively with users on software development projects. The project aspires to enhance and innovate upon Devin through the power of the open-source community. Users can contribute to the project by developing core functionalities, frontend interface, or sandboxing solutions, participating in research and evaluation of LLMs in software engineering, and providing feedback and testing on the OpenDevin toolset.

CogAgent is an advanced intelligent agent model designed for automating operations on graphical interfaces across various computing devices. It supports platforms like Windows, macOS, and Android, enabling users to issue commands, capture device screenshots, and perform automated operations. The model requires a minimum of 29GB of GPU memory for inference at BF16 precision and offers capabilities for executing tasks like sending Christmas greetings and sending emails. Users can interact with the model by providing task descriptions, platform specifications, and desired output formats.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

Agentless is an open-source tool designed for automatically solving software development problems. It follows a two-phase process of localization and repair to identify faults in specific files, classes, and functions, and generate candidate patches for fixing issues. The tool is aimed at simplifying the software development process by automating issue resolution and patch generation.

The 'Taming LLMs' repository provides a practical guide to the pitfalls and challenges associated with Large Language Models (LLMs) when building applications. It focuses on key limitations and implementation pitfalls, offering practical Python examples and open source solutions to help engineers and technical leaders navigate these challenges. The repository aims to equip readers with the knowledge to harness the power of LLMs while avoiding their inherent limitations.

Dockershrink is an AI-powered Commandline Tool designed to help reduce the size of Docker images. It combines traditional Rule-based analysis with Generative AI techniques to optimize Image configurations. The tool supports NodeJS applications and aims to save costs on storage, data transfer, and build times while increasing developer productivity. By automatically applying advanced optimization techniques, Dockershrink simplifies the process for engineers and organizations, resulting in significant savings and efficiency improvements.

Gives structure to messy GitHub issues.

Translates GitHub issues from Japanese to English.

I'm Logic Pro X's manual. Let me answer your questions, troubleshoot whatever issue you're having and get you back into the groove!

The best assistant for IT admins, get to the root cause of any issue

Clone and replicate the source site using a screenshot, while enabling continuous development and optimization capabilities. - 通过截图复制源站点前端代码，同时具备持续开发和优化功能。Any Issue: contact me @X: https://twitter.com/tb_xy09

Translates network issues into Wireshark filter syntax.

Learn Linux by Hands-on Labs and AI

Prioritizes major 3D printing issues with solutions.

Analyzes code for accessibility issues & provides recommendations

Product Engineer helps find inventive solutions to engineering problems.

A JavaScript expert solving coding issues with clarity and depth.

An mechanical engineering tutor, aiding with concepts and problem-solving.

Provides expert help for Laravel development questions and challenges.

Expert in diagnosing and fixing GPT issues.

Guides thermal management solutions for efficient system performance.

An assistant to help audio DIY'ers of any level, and anyone curios about audio to identify issues, find information, and general assistance in their journey.

The pressing environmental issues we face today require novel approaches and technological advancements to effectively mitigate their impacts. GaiaAI offers a range of tools and modes to promote sustainable practices and enhance environmental stewardship.

Assists in resolving technical issues in field operations.

制定和实施质量管理体系；审核和改进质量管理体系；培训和指导员；处理质量问题；与其他部门协调；持续改进

Java Security Expert offering advice on best practices and resolving security issues.