Search Results for "tasks" - Page 47
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Showing 3766 open source projects for "tasks"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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golib
Golang packages used in frp and fft
golib is a collection of common Go packages extracted for reuse across the author’s projects, notably frp and fft. It serves as a shared foundation for IO helpers, messaging formats, and other utilities that would otherwise be copy-pasted between codebases. The repository is versioned and published as Go modules, making it easy to import stable subsets into downstream applications. Individual subpackages cover concerns like streaming IO and JSON message structures, keeping implementations... -
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Deep Learning Is Nothing
Deep learning concepts in an approachable style
...Implementations favor small, readable examples—often NumPy first—to show how forward and backward passes work without depending solely on high-level frameworks. Once the fundamentals are clear, the material extends to CNNs, RNNs, and attention mechanisms, explaining why each architecture suits particular tasks. Practical sections cover data pipelines, regularization, and evaluation, emphasizing reproducibility and debugging techniques. The goal is to replace buzzwords with intuition so learners can reason about architectures and training dynamics with confidence. -
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jstraining
Training materials designed to teach JavaScript
...It can be adapted for short bootcamps, brown-bag sessions, or self-guided study. Instructors benefit from ready-to-use outlines, while learners get runnable code and tasks that build muscle memory. -
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Learn Elixir
Learn the Elixir programming language to build functional web apps
...The repo walks you from installation on macOS, Ubuntu, and Windows to an interactive workflow using iex, Livebook, and even a one-line Docker run for a zero-install setup. It teaches Elixir’s core types and syntax with short, runnable examples, then moves into real project work using Mix for generating apps, compiling, running tasks, managing dependencies, and creating docs. You’ll learn to write idiomatic modules and functions, use the Enum module, and practice pattern matching and the pipe operator in small, composable functions. The guide also shows how to generate API docs with ex_doc, write and run tests with ExUnit and doctest, and measure coverage—forming a complete feedback loop. -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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Practical ASP.NET Core
Practical samples of ASP.NET Core 10 RC
practical-aspnetcore is a repository containing hundreds of sample projects, micro-applications, and code snippets across multiple versions of .NET Core (including 2.1, 3.1, 5.0, 6.0, 7.0, 8.0, 9.0, 10 RC) to illustrate real-world patterns, advanced topics, and features in .NET Core development. It is intended as a hands-on learning resource for building web APIs, middleware, authentication, real-time, microservices, etc. -
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Sidekiq
Simple, efficient background processing for Ruby
Sidekiq is a background job processing framework for Ruby that leverages multithreading to handle thousands of jobs concurrently with minimal memory overhead. It integrates seamlessly with Rails and other Ruby applications, letting developers offload tasks such as email delivery, file processing, and API calls so the main web process stays responsive. Sidekiq uses Redis as its backend, storing job queues, scheduling information, and retries, with support for delayed jobs and exponential backoff on failures. Its middleware architecture allows developers to inject custom logic around job execution, such as logging, tracing, or instrumentation. ... -
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Integrant
Micro-framework for data-driven architecture
Integrant is a minimalistic micro-framework for building applications following a data-driven architecture. It lets you define system components declaratively as configuration data and handles lifecycle actions (init, halt, resume) in dependency order, serving as a modern alternative to Component or Mount. Integrant was built as a reaction to fix some perceived weaknesses with Component. In Component, systems are created programmatically. Constructor functions are used to build records,... -
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Lithops
A multi-cloud framework for big data analytics
Lithops is an open-source serverless computing framework that enables transparent execution of Python functions across multiple cloud providers and on-prem infrastructure. It abstracts cloud providers like IBM Cloud, AWS, Azure, and Google Cloud into a unified interface and turns your Python functions into scalable, event-driven workloads. Lithops is ideal for data processing, ML inference, and embarrassingly parallel workloads, giving you the power of FaaS (Function-as-a-Service) without... -
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Sakura Boot
Framework on top of spring-boot that helps create back-ends
This framework, built on top of Spring Boot, is designed to speed up the development of robust backends. It ensures adherence to best practices while allowing a high degree of customization. The framework is structured using a modular architecture, making it easy to add or remove features based on the project’s specific needs. While Spring Boot speeds up the development process, developers still require extensive knowledge, must ensure adherence to best practices, and often write repetitive... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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emiT-C
A time travelling programming language
emiT is a language all about parallel timelines. At any given point you can send a variable back in time, and make it change things about the past, starting a new timeline where the result is different. You can kill variables, which destroys them permanantly- at least until you send another variable back in time to kill the variable doing the killing. This very quickly leads to a lot of confusion, with a constantly changing source code and the very easy possibility of creating a paradox or a... -
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AutoKeras
AutoML library for deep learning
...If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the best detailed configuration for you. Moreover, you can override the base classes to create your own block. -
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UXF
Framework for creating human behaviour experiments in Unity
...Allows you to programmatically define independent variables for your session, blocks and trials. Includes a pre-built UI for allowing the researcher to view and enter information about the session. All file IO tasks are performed concurrently in a separate thread to avoid any drops in the framerate. UXF works with any Unity project but is designed specifically for virtual reality human behavior experiments. -
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AG2
Framework for building and orchestrating multi-agent AI systems
AG2 is an open source framework designed to support the creation and coordination of multiple AI agents working together to solve complex tasks. It provides abstractions that allow developers to define agents with distinct roles, responsibilities, and communication patterns, enabling collaborative problem-solving workflows. AG2 focuses on making multi-agent systems more accessible by simplifying how agents are configured, connected, and executed. It includes mechanisms for agent-to-agent interaction, task delegation, and iterative reasoning, which are essential for building advanced AI-driven applications. ... -
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NVIDIA NeMo Agent Toolkit
Library for efficiently connecting and optimizing teams of AI agents
NVIDIA NeMo Agent Toolkit is an open-source framework designed to build, optimize, and manage AI agents across different development ecosystems. It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze... -
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OpenClaw Opik Observability Plugin
Official plugin for OpenClaw that exports agent traces to Opik
...The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a tool, accessing memory, or delegating to a sub-agent—the plugin records the full interaction and sends it to Opik for analysis and visualization. This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. ... -
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SiteDorks
Automate search engine dorking across hundreds of websites
...A built-in dataset contains hundreds of websites grouped into categories such as cloud services, developer platforms, documentation sites, social platforms, and communication tools. Users can also supply custom domain lists or CSV files to tailor searches for tasks like penetration testing, bug bounty research, or OSINT investigations. -
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Fulling
Full-stack Engineer Agent. Built with Next.js, Claude, shadcn/ui
...Instead of manually configuring development environments, the system automatically provisions the required infrastructure including a Linux environment, database services, and development tools. It integrates an AI pair programmer that can generate code, implement features, and assist with debugging tasks through natural language instructions. The environment also includes web-based terminals, file management tools, and version control capabilities to support collaborative software development workflows. Developers can connect external services by simply providing API credentials, allowing the AI system to automatically integrate features such as authentication or payment processing. -
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mergekit
Tools for merging pretrained large language models
...The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code. -
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Zypher Agent
A minimal yet powerful framework for creating AI agents
...It includes mechanisms like checkpointing to version agent decision states, concurrency protections, error handling, and operational interceptors to customize behavior after each reasoning step. Its API is built with TypeScript and is suitable for production contexts where agents must handle real tasks with configurability, logging, and observability. -
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Swift Concurrency Agent Skill
Add expert Swift Concurrency guidance to your AI coding tool
...Rather than teaching basic Swift, it targets the nuanced behaviors of concurrency primitives, actor isolation, and safety annotations like @MainActor and Sendable. It also clarifies how to reason about structured tasks, cancellation, and performance trade-offs. -
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Anthony Fu's Skills
Anthony Fu's curated collection of agent skills
Anthony Fu's Skills is an open-source collection of agent skills — modular instruction packages that teach AI coding assistants how to perform specific tasks automatically when relevant. These skills are typically simple, human-readable files that contain structured steps, rules, examples, and workflow logic, letting tools like Claude Code or Copilot CLI load and run them only when they apply to the user’s input. By offloading detailed task patterns into discrete skill modules, developers can greatly extend what coding agents can do without retraining the underlying language model itself. ... -
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nanobot
🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw
nanobot is an ultra-lightweight personal AI assistant designed to deliver powerful agent capabilities without unnecessary complexity. Built in just ~4,000 lines of clean, readable code, it offers a minimalist alternative to heavyweight agent frameworks while retaining core intelligence and extensibility. nanobot is optimized for speed and efficiency, enabling fast startup times and low resource usage across environments. Its research-ready architecture makes it easy for developers to... -
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InfiAgent
Build your own Cowork, AI Scientist and other SoTA Agents
infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. ... -
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kMCP
Kubernetes Controller for building, testing and deploying MCP servers
KMCP is a companion toolchain for building, testing, and deploying MCP servers with a workflow that spans local development through Kubernetes production deployments. It includes a CLI for day-to-day development tasks like scaffolding new MCP projects, managing tools, building container images, and running an MCP server locally for validation. For cluster operations, it includes a Kubernetes controller that manages MCP server lifecycles using a dedicated Custom Resource Definition (CRD), allowing MCP servers to be represented as native Kubernetes objects you can operate with familiar kubectl-driven patterns. ... -
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sqlite-utils
Python CLI utility and library for manipulating SQLite databases
sqlite-utils is both a Python library and a command-line tool for creating, inspecting, and transforming SQLite databases with minimal boilerplate. It focuses on making common tasks like importing CSV/JSON, exploring tables, and running ad-hoc queries feel ergonomic and scriptable. As a CLI, it lets you build databases from structured data in one line, run queries against local files or in-memory databases, output results as JSON, CSV, or pretty tables, and configure full-text search. As a library, it exposes high-level APIs for inserting records, creating or transforming tables, normalizing schemas, and running migrations that SQLite’s limited ALTER TABLE cannot handle directly. ...
