Search Results for "loop" - Page 6
Sort By:
Showing 514 open source projects for "loop"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
-
1
Unstract
No-code LLM Platform to launch APIs and ETL Pipelines
Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to... -
2
Interface Design
Design engineering for Claude Code
...It also offers commands to inspect the current design system status, audit inconsistencies, and extract patterns back into a reusable format, making it a live feedback loop for quality UI work. -
3
latexify
A library to generate LaTeX expression from Python code
...Users can control rendering details for names and operators so the output conforms to a project’s notation style. Because it works directly from Python source, it enables a tight authoring loop. -
4
TensorFlow Model Garden
Models and examples built with TensorFlow
...To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU). -
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.
-
5
RestorePhotos.io
Restoring old and blurry face photos with AI
RestorePhotos.io is an AI web app for restoring old, blurry, or low-quality face photos and bringing them back to life. It wraps the GFPGAN model (served via Replicate) behind a friendly Next.js front end, so non-technical users can upload an image and receive an enhanced version without ever touching ML code. The workflow is straightforward: you upload a photo, the serverless API route sends it to Replicate, and the restored image is returned and displayed in the UI. The project is... -
6
Context Hub
Makes coding agents get smarter with every task
Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls,... -
7
Claude Autoresearch
Claude Autoresearch Skill, autonomous goal-directed iteration
...The system likely integrates with external data sources, allowing it to gather information from diverse inputs and organize it into structured outputs. Its iterative loop enables deeper exploration of topics over time, making it particularly useful for complex or open-ended research questions. The architecture emphasizes autonomy, reducing the need for constant user input while still producing meaningful insights. It may also include summarization and reporting capabilities to present findings in a digestible format. ... -
8
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. -
9
CGraph
A general, three-party dependency-free, cross-platform
...It allows developers to model computational processes as graph structures, where nodes represent tasks and edges define dependencies, enabling efficient scheduling and execution. The framework includes a pipeline system that supports sequential and parallel execution, conditional branching, aggregation, and loop control, making it highly flexible for advanced workflows. Developers can extend the system by defining custom nodes and grouping them into logical structures, allowing fine-grained control over execution behavior. CGraph also supports features such as pausing, resuming, and timeout management, which are critical for real-world systems requiring robustness and reliability. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
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... -
11
ANE Training
Training neural networks on Apple Neural Engine via APIs
...It explores the internal software stack of the Apple Neural Engine by interfacing with private classes such as _ANEClient and compiling custom compute graphs in the MIL format. The project includes performance benchmarks and kernel breakdowns that show how different components of the training loop are distributed between the ANE and CPU. It is primarily intended as a research and educational proof of concept rather than a production library, highlighting what is technically possible with undocumented hardware access. -
12
Localflare
local cloudflare
...The D1 experience is more than a viewer: it includes a SQL editor and a data browser with inline editing, filtering, sorting, bulk operations, and even dummy data generation so you can iterate quickly. For KV and R2 it provides practical file-and-record management, letting you view, update, delete, upload, and download as part of your normal dev loop. It also includes tools for testing queue behavior by sending messages and inspecting results, which helps validate event-driven logic without deploying. -
13
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 migrate or write MongoDB code in Python without having to learn a completely new interface. Because it integrates with popular async ecosystems like FastAPI, Sanic, and aiohttp, Motor is a natural fit for modern async Python stacks where throughput and responsiveness matter. ... -
14
Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can... -
15
Open Source Vizier
Python-based research interface for blackbox
...A wide collection of objective functions and methods to benchmark and compare algorithms. Define a problem statement and study configuration. Setup a local server, setup a client to connect to the server, perform a typical tuning loop, and use other client APIs. -
16
React Three Fiber
A React renderer for Three.js
...It merely expresses three.js in JSX, <mesh /> becomes new THREE.Mesh(), and that happens dynamically. There is no additional overhead. Components participate in a unified render loop outside of React. It outperforms three.js at scale due to React's scheduling abilities.Y ou need to be versed in both React and three.js before rushing into this. If you are unsure about React consult the official React docs, especially the section about hooks. -
17
Process Component
The Process component executes commands in sub-processes
...The clearOutput() method clears the contents of the output and clearErrorOutput() clears the contents of the error output. You can also use the Symfony\Component\Process\Process class with the for each construct to get the output while it is generated. By default, the loop waits for new output before going to the next iteration -
18
Open SWE
Open source async coding agent that plans, codes, and opens PRs
...It integrates directly with development workflows by responding to triggers from tools like GitHub, enabling users to initiate tasks through issues or comments. Open SWE is capable of creating commits and automatically opening pull requests once implementation is complete, effectively closing the loop on development tasks. It also supports interactive feedback during execution, allowing users to guide or adjust the process mid-task. Despite its advanced capabilities, the project has been officially marked as deprecated. -
19
Flock
Flock is a workflow-based low-code platform for building chatbots
...The platform supports multi-agent collaboration, allowing developers to design workflows where different agents handle specialized tasks within the same system. Flock also includes features such as intent recognition, code execution nodes, and human-in-the-loop approval processes that make it suitable for production AI applications. -
20
UIforETW
User interface for recording and managing ETW traces
...It standardizes trace collection profiles, launches WPR/xperf with the right providers, and organizes the resulting .etl files for repeatable investigations. The tool streamlines the entire loop—record, annotate, open in WPA/XperfView—so engineers can focus on finding scheduling stalls, I/O bottlenecks, GC pauses, or GPU hitches instead of memorizing command-line incantations. It also manages symbol settings and capture templates, making it much easier to get actionable call stacks on developer machines and CI bots alike. ... -
21
Toloka-Kit
Toloka-Kit is a Python library for working with Toloka API
Toloka-Kit is a Python library for working with Toloka API. The API allows you to build scalable and fully automated human-in-the-loop ML pipelines, and integrate them into your processes. The toolkit makes integration easier. You can use it with Jupyter Notebooks. Support for all common Toloka use cases: creating projects, adding pools, uploading tasks, and so on. Toloka entities are represented as Python classes. You can use them instead of accessing the API using JSON representations. ... -
22
Agentic Inbox
A self-hosted email client with an AI agent, running entirely on Cloud
Agentic Inbox is a self-hosted email client that integrates an AI agent directly into the inbox experience, enabling automated reading, organization, and drafting of emails. It runs entirely on Cloudflare Workers, using serverless infrastructure to manage incoming and outgoing messages without relying on external email services. Each mailbox is isolated with its own storage, ensuring data separation and security while maintaining performance. The system supports full email functionality,... -
23
Folia
Fork of Paper which adds regionized multithreading
...Traditional Minecraft servers run most game logic on a single main thread, which creates performance bottlenecks when many players are active simultaneously. Folia addresses this limitation by dividing the game world into independent regions composed of nearby chunks and assigning each region its own tick loop. These regions run concurrently on multiple threads within a thread pool, allowing server hardware with many CPU cores to process gameplay events in parallel. This architecture significantly increases scalability for large multiplayer environments where players are distributed across different areas of the world. Because the project fundamentally changes how the server processes game logic, many existing plugins are not immediately compatible and must be adapted for the new threading model. -
24
MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. By... -
25
Deep Search Agent
Implement a concise and clear Deep Search Agent from 0
Deep Search Agent is an experimental demonstration project that showcases an autonomous AI agent designed to perform multi-step research and information gathering tasks. The repository illustrates how large language models can be orchestrated with tools and planning logic to execute complex search workflows rather than single-prompt responses. It typically combines reasoning, retrieval, and iterative refinement so the agent can break down questions, gather evidence, and synthesize structured...
