Search Results for "execute" - Page 10
Sort By:
Showing 1001 open source projects for "execute"
View related business solutions-
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.
-
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
-
1
Radar
The missing open source Kubernetes UI
...The platform combines multiple observability features such as topology graphs, event timelines, and traffic visualization into one cohesive UI. It allows users to inspect resources, edit YAML, view logs, and execute commands within containers from a browser-based interface. Radar emphasizes performance and simplicity, avoiding heavy agents or polling by using Kubernetes watch APIs for real-time updates. It also integrates with tools like Helm, ArgoCD, and Flux for deployment and GitOps workflows. Overall, it acts as a developer-friendly Kubernetes dashboard and IDE focused on speed, transparency, and local control. -
2
xurl CLI
The official CLI for the X API
xurl is a modern command-line HTTP client designed to provide a flexible and developer-friendly alternative to traditional tools like curl. It introduces a simplified syntax and enhanced usability, making it easier to construct and execute HTTP requests without memorizing complex command structures. The tool supports a wide range of HTTP operations, including GET, POST, PUT, and DELETE, while also providing features such as request templating and reusable configurations. It is designed for efficiency, allowing developers to quickly test APIs, debug endpoints, and automate network interactions directly from the terminal. xurl also includes support for structured output formats, making it easier to inspect responses and integrate with scripts or pipelines. ... -
3
Ollama4j
A simple Java library for interacting with Ollama server
...It integrates seamlessly into Java ecosystems through Maven or Gradle dependencies, and it works with standard Java environments starting from JDK 11 and above. Ollama4j also includes support for advanced features such as tool or function calling, enabling models to interact with external systems and execute more complex workflows. -
4
k-skill
Skill collection for Koreans - SRT, KTX, KakaoTalk, Hangul
The k-skill project is an AI skill management framework designed to organize, structure, and execute reusable capabilities within AI-driven development environments. It focuses on defining skills as modular, composable units that can be invoked by agents to perform specific tasks such as coding, reasoning, or automation. The system provides a standardized structure for skills, enabling consistency across different workflows and improving interoperability between tools. -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
5
Open Agents
An open source template for building cloud agents
The Open Agents project is an experimental platform developed to explore the design and deployment of open, composable AI agents. It focuses on enabling developers to create agents that can collaborate, execute tasks, and interact with tools in a structured environment. The framework provides abstractions for agent communication, task orchestration, and tool integration, allowing multiple agents to work together toward shared objectives. It emphasizes openness and interoperability, making it easier to integrate with different models, APIs, and external systems. ... -
6
quickjs-emscripten
Safely execute untrusted Javascript in your Javascript
quickjs-emscripten is a JavaScript library that compiles the QuickJS engine into WebAssembly using Emscripten, enabling developers to run JavaScript code inside a sandboxed environment within browsers or server-side JavaScript runtimes. It provides a secure and isolated execution context, making it particularly useful for running untrusted or user-generated code safely. The library abstracts the complexity of loading and initializing the WebAssembly module, offering convenient APIs to create... -
7
Wasmi
Efficient and versatile WebAssembly interpreter for embedded systems
wasmi is a lightweight WebAssembly interpreter written in Rust that is designed to execute Wasm binaries efficiently in constrained or embedded environments. Unlike JIT-based runtimes, wasmi focuses on interpretation, prioritizing portability, determinism, and low resource usage over maximum raw performance. It is particularly well-suited for blockchain systems, embedded devices, and other contexts where predictable execution and minimal dependencies are critical. -
8
wazero
The zero dependency WebAssembly runtime for Go developers
wazero is a zero-dependency WebAssembly runtime written in Go that enables developers to execute WebAssembly modules directly within Go applications without relying on external toolchains or CGO. It fully implements the WebAssembly core specification and supports both interpreter and compiler execution modes, allowing developers to choose between portability and performance. One of its defining characteristics is its pure Go implementation, which simplifies cross-compilation and deployment across different platforms. ... -
9
AI Agent Deep Dive
AI Agent Source Code Deep Research Report
...The project is organized as a learning resource rather than a standalone framework, making it particularly useful for developers who want to move beyond surface-level prompt engineering into full agent system design. It explores how agents interact with environments, execute tasks, and maintain context over time, highlighting both strengths and limitations of current approaches. The repository likely includes diagrams, annotated code samples, and conceptual walkthroughs that mirror real production systems. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
10
Godot MCP
MCP server for interfacing with Godot game engine
...It acts as a bridge between AI systems and the Godot editor, providing capabilities such as launching projects, running games in debug mode, and capturing runtime output for analysis. The tool is particularly valuable for AI-assisted game development, as it creates a feedback loop where agents can execute code, observe results, and iteratively improve their outputs. It also includes advanced features for manipulating scenes, managing assets, and editing project structures, making it possible to automate large portions of the development process. By exposing Godot functionality through a standardized MCP interface, it ensures compatibility with various AI clients such as Claude Code or Cursor. -
11
Embabel Agent Framework
Agent framework for the JVM. Pronounced Em-BAY-bel
Embabel Agent Framework is a JVM-based framework for building advanced AI agent systems that combine structured programming with large language model interactions to execute complex, goal-oriented workflows. The framework introduces a planning-driven approach where agents dynamically determine sequences of actions required to achieve objectives, rather than relying on fixed pipelines or predefined flows. It models agent behavior through concepts such as goals, actions, and conditions, allowing systems to adapt in real time based on changing inputs and outcomes. ... -
12
BehaviorTree.CPP
C++ behavior tree library for robotics and AI decision systems
BehaviorTree.CPP is a C++ library designed to create, manage, and execute behavior trees, a widely used model for decision-making in robotics and artificial intelligence systems. It provides a flexible and modular framework that allows developers to define complex behaviors as reusable tree structures composed of nodes. BehaviorTree.CPP emphasizes performance and real-time execution, making it particularly suitable for robotics applications where responsiveness is critical. -
13
kubectl-ai
AI assistant for managing Kubernetes clusters from the terminal
kubectl-ai is an AI-powered command-line assistant designed to help users manage and interact with Kubernetes clusters through natural language queries. It acts as an intelligent interface that interprets user intent and translates it into appropriate Kubernetes operations and commands. By integrating large language models, it enables users to ask questions or request actions in plain language instead of manually crafting complex Kubernetes commands. kubectl-ai runs directly in the terminal... -
14
Apache Hamilton
Helps data scientists define testable self-documenting dataflows
...The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph representing the pipeline, allowing the system to execute transformations in the correct order. This approach encourages modular, testable, and maintainable data pipelines because each transformation is isolated and easily unit tested. The framework also automatically tracks lineage and metadata about how data is produced, which improves debugging, reproducibility, and transparency in data workflows. -
15
Deepnote
Deepnote is a drop-in replacement for Jupyter
...Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. Deepnote emphasizes team-based data science by enabling real-time collaboration similar to shared document editors, allowing multiple users to work simultaneously on the same notebook environment. -
16
BrowserNode
Make websites accessible for AI agents. Automate tasks online
...Built as an implementation compatible with the Browser-use ecosystem, Browsernode allows agents to perform actions such as navigating pages, extracting information, filling forms, or interacting with dynamic web interfaces. The system integrates with Playwright to control Chromium-based browsers and execute automation scripts in a reliable environment. Developers can configure the framework to connect to different language model providers so that AI agents can interpret instructions and decide which browser actions to perform. -
17
KIS Open API
Korea Investment & Securities Open API Github
...The project is designed primarily for Python developers and AI automation environments that want to build investment applications, algorithmic trading systems, or financial analytics tools using the brokerage’s infrastructure. It includes example scripts that demonstrate how to authenticate with the service, retrieve financial data, and execute trading operations through REST and WebSocket interfaces. The repository organizes its examples into two main groups: code designed for direct user implementation and simplified examples intended for large language model agents or automation workflows. -
18
HyperAgent
AI Browser Automation
...Instead of manually writing logic for clicking elements, extracting data, or navigating web pages, developers can instruct the agent in plain language and allow the AI layer to interpret and execute the task. This approach reduces the brittleness commonly associated with traditional automation scripts that break when the DOM structure changes. HyperAgent includes APIs such as page.ai() and page.extract() that allow structured data extraction and dynamic task execution through AI reasoning. -
19
BrowserGym
A Gym environment for web task automation
...It is intended for researchers building web agents rather than for end users looking for a consumer automation product. The project provides a common environment where agents can interact with websites, execute tasks, and be evaluated against standardized benchmarks. One of its main strengths is that it bundles several important benchmarks by default, including MiniWoB, WebArena, VisualWebArena, WorkArena, AssistantBench, WebLINX, and OpenApps. This gives researchers a unified way to compare agent behavior across diverse web environments and task types without stitching together separate evaluation stacks. ... -
20
OM1
Modular AI runtime for robots
...The project focuses on creating a modular architecture where language models can coordinate with external tools, APIs, and knowledge sources to accomplish multi-step objectives. Instead of operating as simple conversational systems, OM1 agents can plan actions, retrieve information, and execute tasks across different services. The framework integrates reasoning modules, planning strategies, and tool interfaces that allow agents to operate in dynamic environments. Developers can extend the system by connecting new tools, services, or data sources to the agent architecture. The platform also includes mechanisms for coordinating workflows and managing the state of ongoing tasks. -
21
nono
Secure, kernel-enforced sandbox CLI and SDKs for AI agents
nono is an open-source, kernel-enforced capability shell designed to safely run AI agents and other untrusted processes under strict operating system controls. The project addresses a growing security concern: modern coding agents typically execute with full user permissions, which means they can potentially read sensitive files, modify system configurations, or exfiltrate credentials if compromised. nono solves this by applying default-deny sandboxing at the kernel level using technologies such as Landlock on Linux and Seatbelt on macOS, making unauthorized actions structurally impossible rather than merely discouraged. ... -
22
Personal AI Infrastructure
Agentic AI Infrastructure for magnifying HUMAN capabilities
...Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code editing, execution, and more into a continuous Observe → Think → Plan → Execute → Verify → Learn cycle, letting the system refine its behavior with each use. Its architecture supports long-term memory, verification of actions, and ongoing self-improvement, blurring the line between “assistant” and persistent, evolving collaborator. -
23
Monty
A minimal, secure Python interpreter written in Rust for use by AI
...Rather than offering a full “general-purpose Python runtime with everything enabled,” Monty is designed to be minimal and controlled, making it easier to reason about what code can do and what it cannot. It prioritizes guardrails like resource limits and restricted capabilities, which is especially useful for agentic workflows that need to execute small pieces of Python for data transforms, validation, or tool-like computations. Because it’s written in Rust, it’s positioned to deliver a compact, portable runtime that can be embedded into larger systems that need dependable isolation. -
24
Upscheme
Database migrations and schema updates made easy
...With support for major relational database systems via Doctrine DBAL, Upscheme enables cross-platform migrations with minimal code, reducing friction when evolving your application’s data model. The project includes tools to generate migration files, handle dependencies between tasks, and execute changes reliably across environments without requiring low-level SQL scripting. By focusing on upgrades and avoiding potentially unsafe downgrades, it prioritizes safety and predictability for real-world application upgrades. -
25
Superduper
Superduper: Integrate AI models and machine learning workflows
...This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.