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Showing 2489 open source projects for "source code billing"
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Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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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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SEO Machine
A specialized Claude Code workspace for creating long-form
SEO Machine is an AI-powered content production system built as a structured workspace for generating long-form, SEO-optimized blog content through automated workflows. It integrates research, writing, analysis, and optimization into a single pipeline, allowing users to produce high-quality articles tailored to search engine performance. The system uses specialized commands and agents to perform tasks such as keyword research, competitor analysis, content drafting, and optimization. It... -
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ZML
Any model. Any hardware. Zero compromise
ZML is a high-performance machine learning inference stack designed to run AI models efficiently across heterogeneous hardware environments using a modern systems programming approach. Built with technologies such as Zig, MLIR, and Bazel, it focuses on production-grade deployment where performance, portability, and scalability are critical. The system allows models to be compiled and executed across multiple types of accelerators, including GPUs and TPUs, even when distributed across... -
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Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
Google Kubernetes Engine (GKE) Samples repository is a comprehensive collection of sample applications and reference implementations designed to demonstrate how to build, deploy, and manage workloads on Google Kubernetes Engine (GKE). It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. The repository is organized into multiple categories such... -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation... -
PRTG Catches Network Issues Before They Cause DowntimeReactive troubleshooting usually means hearing about a problem from frustrated users, not your monitoring tool. PRTG sets threshold-based alerts across devices, servers and applications, notifying your team by email, SMS or push the moment a metric crosses a set limit. That means catching a failing disk or overloaded server before it becomes an outage and getting time back from firefighting. Start a free trial and set your first alerts today.
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TypeAgent Python
Structured RAG: ingest, index, query
TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language... -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
micrograd is a tiny, educational automatic differentiation engine focused on scalar values, built to show how backpropagation works end to end with minimal code. It constructs a dynamic computation graph as you perform math operations and then computes gradients by walking that graph backward, making it an approachable “from scratch” autograd reference. On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple... -
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Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
Hugging Face Skills is a repository of standardized task definitions that package instructions, scripts, and resources so coding agents can reliably perform AI and machine learning workflows. Each skill is a self-contained folder with structured metadata and guidance that tells an agent how to execute tasks such as dataset creation, model training, evaluation, or Hub operations. The project is designed to be interoperable across major agent ecosystems, including Claude Code, OpenAI Codex,... -
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papermill
Parameterize, execute, and analyze notebooks
papermill is a Python library and command-line tool that transforms Jupyter Notebooks into repeatable, parameterized workflows by allowing users to define editable parameters within notebooks and then programmatically execute them with different inputs. Instead of manually opening and running a notebook inside JupyterLab or Notebook every time, Papermill lets you inject new values into a specially tagged parameters cell and execute the entire notebook automatically via a script or automation... -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
Antigravity Awesome Skills is a playful yet practical repository that curates a set of clever, expressive, and sometimes whimsical AI agent skill templates designed to help users bootstrap agent behavior quickly. Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. The project... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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Trellis AI
All-in-one AI framework & toolkit for Claude Code & Cursor
Trellis is an advanced workflow and agent orchestration framework designed for building, managing, and scaling intelligent applications that coordinate numerous autonomous components. At its core, Trellis lets developers define units of work — called tasks or agents — and compose them into rich workflows that can operate with concurrency, conditional logic, and dynamic branching, all without sacrificing readability or control. It emphasizes modular design, encouraging users to encapsulate... -
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StoryMem
Official code for StoryMem: Multi-shot Long Video Storytelling
StoryMem is a narrative-focused memory accumulation system that lets users build, store, and reference past conversational context or story elements with an AI, effectively enabling the AI to maintain and recall personalized story memories or character arcs over time. Instead of treating each interaction as stateless, it tracks user-defined memory nodes, tags, and story threads so that future interactions can draw on established narrative context like character traits, past events, or... -
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Motor
The async Python driver for MongoDB and Tornado or asyncio
Motor is an asynchronous Python driver for MongoDB that enables developers to work with MongoDB using non-blocking I/O patterns, making it ideal for high-performance and scalable applications. Built on top of Python’s Tornado and asyncio frameworks, Motor lets you issue database operations without blocking the event loop, enabling concurrency in web servers, real-time systems, and microservices. It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can... -
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D4RL
Collection of reference environments, offline reinforcement learning
D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm... -
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llm.c
LLM training in simple, raw C/CUDA
llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and... -
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pangu.py
Paranoid text spacing in Python
pangu.py is a Python port of the Pangu spacing tool that automatically inserts proper whitespace between CJK characters and Latin letters, numbers, or symbols. Mixed-script text often becomes cramped or ambiguous, and this library applies simple but effective typography rules to make it instantly more readable. It works both as a Python library and a command-line utility, so you can process strings in code, tidy files in bulk, or wire it into documentation and build pipelines. The... -
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PPTAgent
PPTAgent: Generating and Evaluating Presentations
PPTAgent is a research system for generating and evaluating slide decks that goes beyond simple text-to-slides. It follows a two-stage, edit-based workflow: first it analyzes reference presentations to infer slide roles and structure, then it drafts an outline and iteratively performs editing actions to produce new slides. The project includes both the generation agent and an evaluation framework, PPTEval, to score content quality, design, and coherence. The repository highlights the EMNLP... -
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Taipy
Turns Data and AI algorithms into production-ready web applications
From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape.... -
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SWE-agent
SWE-agent takes a GitHub issue and tries to automatically fix it
SWE-agent turns LMs (e.g. GPT-4) into software engineering agents that can resolve issues in real GitHub repositories. On the SWE-bench, the SWE-agent resolves 12.47% of issues, achieving state-of-the-art performance on the full test set. We accomplish our results by designing simple LM-centric commands and feedback formats to make it easier for the LM to browse the repository, and view, edit, and execute code files. We call this an Agent-Computer Interface (ACI). -
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Stable Baselines3
PyTorch version of Stable Baselines
Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines. You can read a detailed presentation of Stable Baselines3 in the v1.0 blog post or our JMLR paper. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around... -
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GEF
Modern experience for GDB with advanced debugging capabilities
GEF is a set of commands for x86/64, ARM, MIPS, PowerPC and SPARC to assist exploit developers and reverse-engineers when using old-school GDB. It provides additional features to GDB using the Python API to assist during the process of dynamic analysis and exploit development. Application developers will also benefit from it, as GEF lifts a great part of regular GDB obscurity, avoiding repeating traditional commands or bringing out the relevant information from the debugging runtime. -
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Changelog CI
Changelog CI is a GitHub Action that enables a project
Changelog CI is a GitHub Action that enables a project to automatically generate changelogs. Changelog CI can be triggered on pull_request, workflow_dispatch, and any other events that can provide the required inputs. Changelog CI uses python and GitHub API to generate a changelog for a repository. First, it tries to get the latest release from the repository (If available). Then, it checks all the pull requests/commits merged after the last release using the GitHub API. After that, it... -
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HASS Configurator
Configuration UI for Home Assistant
The HASS Configurator is a small web app (you access it via a web browser) that provides a filesystem browser and text-editor to modify files on the machine the configurator is running on. It has been created to allow easy configuration of Home Assistant. It is powered by Ace editor, which supports syntax highlighting for various code/markup languages. YAML files (the default language for Home Assistant configuration files) will be automatically checked for syntax errors while editing. The... -
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Mosec
A high-performance ML model serving framework, offers dynamic batching
Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. -
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nbstripout
strip output from Jupyter and IPython notebooks
Opens a notebook, strips its output, and writes the outputless version to the original file. Useful mainly as a git filter or pre-commit hook for users who don't want to track output in VCS. This does mostly the same thing as the Clear All Output command in the notebook UI. You can download and install the latest version of nbstripout from PyPI, the Python package index. Strip output from IPython / Jupyter / Zeppelin notebook (modifies the file in-place). Usually, nbstripout is installed per... -
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pre-commit-hooks
Some out-of-the-box hooks for pre-commit
Some out-of-the-box hooks for pre-commit. Using pre-commit-hooks with pre-commit. Instead of loading the files, simply parse them for syntax. A syntax-only check enables extensions and unsafe constructs which would otherwise be forbidden. Using this option removes all guarantees of portability to other yaml implementations. Detect symlinks which are changed to regular files with a content of a path that that symlink was pointing to. This usually happens on Windows when a user clones a...
