Best AI tools for< Manage Code Changes >

GitBrain is an AI-powered Git client designed for Mac users. It simplifies the Git workflow by offering features like AI commit messages, code splitting, self-code review, auto-detection of projects, and keyboard-friendly design. With GitBrain, developers can focus on coding while the AI handles Git operations efficiently. The application enhances productivity by intelligently splitting code changes into multiple AI-generated commits, providing summaries for code changes, and offering a seamless Git management experience. GitBrain is optimized for Mac performance with a native UI and supports light & dark mode themes.

GitHub is the world's leading AI-powered developer platform that offers a wide range of tools and features to enhance the developer experience. It provides automation for workflows, security features to find and fix vulnerabilities, instant development environments, AI-powered code assistance with GitHub Copilot, code review and management capabilities, issue tracking, collaboration tools, and more. GitHub empowers developers to accelerate innovation and collaborate efficiently, making it a go-to platform for individuals, teams, and organizations in the software development industry.

Lobe is a free and easy-to-use machine learning tool for Mac and PC that allows users to train machine learning models and deploy them to any platform of their choice. It provides a user-friendly interface for creating, training, and deploying machine learning models without requiring extensive coding knowledge.

ReleasesNotes is an AI-powered release notes generator that helps developers create comprehensive and informative release notes with ease. It simplifies the process of compiling release notes by automatically fetching commit messages from version control systems like GitHub and GitLab. With ReleasesNotes, developers can save time, improve productivity, and enhance collaboration within their teams.

Operant is a cloud-native runtime protection platform that offers instant visibility and control from infrastructure to APIs. It provides AI security shield for applications, API threat protection, Kubernetes security, automatic microsegmentation, and DevSecOps solutions. Operant helps defend APIs, protect Kubernetes, and shield AI applications by detecting and blocking various attacks in real-time. It simplifies security for cloud-native environments with zero instrumentation, application code changes, or integrations.

GitGab is a collaborative platform for developers to share code, collaborate on projects, and build software together. It provides version control using Git, issue tracking, code review, and project management tools in one integrated platform. With GitGab, developers can work together seamlessly, track changes, and manage their projects efficiently.

Harness is an AI-driven software delivery platform that empowers software engineering teams with AI-infused technology for seamless software delivery. It offers a single platform for all software delivery needs, including DevOps modernization, continuous delivery, GitOps, feature flags, infrastructure as code management, chaos engineering, service reliability management, secure software delivery, cloud cost optimization, and more. Harness aims to simplify the developer experience by providing actionable insights on SDLC, secure software supply chain assurance, and AI development assistance throughout the software delivery lifecycle.

DepsHub is an AI-powered tool designed to simplify dependency updates for software development teams. It offers automatic dependency updates, license checks, and security vulnerability scanning to ensure team security and efficiency. With noise-free dependency management, cross-repository overview, license compliance, and security alerts, DepsHub streamlines the process of keeping dependencies up-to-date. The tool leverages AI to analyze library changelogs, release notes, and codebases to automatically update dependencies, including handling breaking changes. DepsHub supports a wide range of languages and frameworks, making it suitable for teams of all sizes to save time and focus on writing code that matters.

Second is an AI-native enterprise codebase maintenance platform that offers automated migrations and upgrades for software engineering teams. It provides a seamless process for handling code migrations and upgrades, allowing teams to focus on building innovative software. With AI planning and execution agents, Second streamlines the code transformation process, enabling faster project completion and enhanced codebase intelligence. The platform prioritizes security and compliance, ensuring data protection and operational effectiveness. Second aims to revolutionize software engineering by automating routine tasks and empowering human engineers to drive productivity and innovation.

DigestDiff is an AI-driven tool that helps users analyze and understand commit history in codebases. It provides detailed narratives based on commit logs, accelerates onboarding by summarizing codebases, and automates the creation of release notes using AI. The tool prioritizes privacy by only requiring read-only access to commit history and never storing any code or generated data.

AutoKT is an AI-powered application designed for Automatic Knowledge Transfer. It helps in effortless documentation by automatically writing and updating documentation, allowing users to focus on building innovative projects. The tool addresses the challenge of time and bandwidth spent on writing and maintaining documentation in agile workplaces. AutoKT ensures asynchronous knowledge transfer by keeping documentation in sync with code changes and providing a query feature for easy access to information. It is a valuable tool for developers, enabling them to understand legacy code, streamline documentation writing, and facilitate faster onboarding of new team members.

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.

Hexowatch is an AI-powered website monitoring and archiving tool that helps businesses track changes to any website, including visual, content, source code, technology, availability, or price changes. It provides detailed change reports, archives snapshots of pages, and offers side-by-side comparisons and diff reports to highlight changes. Hexowatch also allows users to access monitored data fields as a downloadable CSV file, Google Sheet, RSS feed, or sync any update via Zapier to over 2000 different applications.

Codacy is an AI-powered code quality and security platform designed for developers to efficiently optimize and secure their code. It offers a unified set of AppSec tools, data-driven insights, and seamless integrations across the software development lifecycle. Codacy helps teams monitor and resolve security issues at scale, improve code quality, and prevent breaking changes. With AI suggested fixes and effortless code quality monitoring, Codacy is a valuable tool for businesses and developers alike.

Tonkean is an enterprise intake orchestration platform powered by AI. It helps businesses automate and streamline their intake processes, such as procurement, legal, and more. Tonkean's AI-powered features include an intelligent AI Front Door, guided intake, request status tracker, and custom apps for ops teams. With Tonkean, businesses can increase adoption, efficiency, and compliance in their intake processes.

What The Diff is an AI-powered code review assistant that helps you to write pull request descriptions, send out summarized notifications, and refactor minor issues during the review. It uses natural language processing to understand the changes in your code and generate clear and concise descriptions. What The Diff also provides rich summary notifications that are easy for non-technical stakeholders to understand, and it can generate beautiful changelogs that you can share with your team or the public.

Tusk is an AI coding agent designed to fix UI issues efficiently. It helps software engineers by generating code from tickets to pull requests, running automated checks, addressing feedback, and investigating complex tasks. Tusk saves time and effort by automating mundane tasks, allowing engineers to focus on fulfilling work and improving product quality. The application is trusted by engineers at high-growth companies and offers various pricing plans tailored to different team sizes and needs.

DocDriven is an AI-powered documentation-driven API development tool that provides a shared workspace for optimizing the API development process. It helps in designing APIs faster and more efficiently, collaborating on API changes in real-time, exploring all APIs in one workspace, generating AI code, maintaining API documentation, and much more. DocDriven aims to streamline communication and coordination among backend developers, frontend developers, UI designers, and product managers, ensuring high-quality API design and development.

Trudo.ai is an AI-powered workflow automation platform that allows users to build complex workflows using simple English language commands. The platform is backed by Python code and features interactive UI components. Users can create and customize nodes, handle dynamic routing, and benefit from flexible memory allocation. Trudo.ai also offers AI Copilot functionality for non-technical users to generate logic and user interfaces. With support for various data types and no extra frameworks required, Trudo.ai covers a wide range of use cases and provides versions to track workflow changes.

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, connects codebases, communications, and documentation tools, and offers features like AI-generated pull request changelogs, Notion documentation, Slack bot integration, VS Code extension, and issue tracking. Elessar ensures data privacy and security by following SOC II compliant policies and infrastructures, and it does not use company data for training or storage.

LangStream is a tool for natural language processing tasks, providing a CLI for easy installation and usage. Users can try sample applications like Chat Completions and create their own applications using the developer documentation. It supports running on Kubernetes for production-ready deployment, with support for various Kubernetes distributions and external components like Apache Kafka or Apache Pulsar cluster. Users can deploy LangStream locally using minikube and manage the cluster with mini-langstream. Development requirements include Docker, Java 17, Git, Python 3.11+, and PIP, with the option to test local code changes using mini-langstream.

AI Coding Assistant is a free and open-source IntelliJ plugin that leverages cutting-edge Language Model APIs to enhance developers' coding experience. It seamlessly integrates with various leading LLM APIs, offers an intuitive toolbar UI, and allows granular control over API requests. With features like Code & Patch Chat, Planning with AI Agents, Markdown visualization, and versatile text processing capabilities, this tool aims to streamline coding workflows and boost productivity.

ZenML is an extensible, open-source MLOps framework for creating portable, production-ready machine learning pipelines. By decoupling infrastructure from code, ZenML enables developers across your organization to collaborate more effectively as they develop to production.

aiohttp-devtools provides dev tools for developing applications with aiohttp and associated libraries. It includes CLI commands for running a local server with live reloading and serving static files. The tools aim to simplify the development process by automating tasks such as setting up a new application and managing dependencies. Developers can easily create and run aiohttp applications, manage static files, and utilize live reloading for efficient development.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

The discourse-chatbot is an original AI chatbot for Discourse forums that allows users to converse with the bot in posts or chat channels. Users can customize the character of the bot, enable RAG mode for expert answers, search Wikipedia, news, and Google, provide market data, perform accurate math calculations, and experiment with vision support. The bot uses cutting-edge Open AI API and supports Azure and proxy server connections. It includes a quota system for access management and can be used in RAG mode or basic bot mode. The setup involves creating embeddings to make the bot aware of forum content and setting up bot access permissions based on trust levels. Users must obtain an API token from Open AI and configure group quotas to interact with the bot. The plugin is extensible to support other cloud bots and content search beyond the provided set.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of `unstructured` revolve around streamlining and optimizing the data processing workflow for LLMs. `unstructured` modular functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

Cluster Toolkit is an open-source software by Google Cloud for deploying AI/ML and HPC environments on Google Cloud. It allows easy deployment following best practices, with high customization and extensibility. The toolkit includes tutorials, examples, and documentation for various modules designed for AI/ML and HPC use cases.

Llumnix is a cross-instance request scheduling layer built on top of LLM inference engines such as vLLM, providing optimized multi-instance serving performance with low latency, reduced time-to-first-token (TTFT) and queuing delays, reduced time-between-tokens (TBT) and preemption stalls, and high throughput. It achieves this through dynamic, fine-grained, KV-cache-aware scheduling, continuous rescheduling across instances, KV cache migration mechanism, and seamless integration with existing multi-instance deployment platforms. Llumnix is easy to use, fault-tolerant, elastic, and extensible to more inference engines and scheduling policies.

Runhouse is a tool that allows you to build, run, and deploy production-quality AI apps and workflows on your own compute. It provides simple, powerful APIs for the full lifecycle of AI development, from research to evaluation to production to updates to scaling to management, and across any infra. By automatically packaging your apps into scalable, secure, and observable services, Runhouse can also turn otherwise redundant AI activities into common reusable components across your team or company, which improves cost, velocity, and reproducibility.

superduper.io is a Python framework that integrates AI models, APIs, and vector search engines directly with existing databases. It allows hosting of models, streaming inference, and scalable model training/fine-tuning. Key features include integration of AI with data infrastructure, inference via change-data-capture, scalable model training, model chaining, simple Python interface, Python-first approach, working with difficult data types, feature storing, and vector search capabilities. The tool enables users to turn their existing databases into centralized repositories for managing AI model inputs and outputs, as well as conducting vector searches without the need for specialized databases.

Gitの使い方やベタープラクティスを答えます

Advises on QA tests based on recent game code changes, including git history. Learn more at regression.gg

“Wintermute was hive mind ... effecting changes in the world ..."

Reactor for React code, comments out old code, adds updates inline.

Un outil de correction d'orthographe et de grammaire en langue française, outil de traduction, soulignant les erreurs et gérant le code HTML.

GitHub-integrated AI for coding assistance and project management.

Develops, advises and optimizes infrastructure-as-code practices across the organization.

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No-Code Expert for Digital Solutions

Transforms code into legal-style documents with precision.

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Shows code with comments for Pocketbase solutions.

Helps developers manage state using StateAdapt

Expert-level Node.js developer aiding in code writing and npm libraries.

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Bash terminal emulator with code-block responses

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Pro yet engaging guide in low-code 1ERP implementation & customization