Search Results for "task" - Page 21
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Showing 2026 open source projects for "task"
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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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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.
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Deployer
Deployment tool with support for popular frameworks out of the box
...Deployer can be easily installed via composer or as phar archive. By default deployer keeps the last 5 releases, but you can increase this number by modifying the associated parameter. You may want to run some task before/after other tasks. Configuring that is really simple! Defining a host in Deployer is necessary to deploy your application. It can be a remote machine, a local machine or Amazon EC2 instances. Each host contains a hostname, a stage, one or more roles and configuration parameters. -
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rustlings
Small exercises to get you used to reading and writing Rust code
...For every topic there is an additional README file with some resources to get you started on the topic. We really recommend that you have a look at them before you start. The task is simple. Most exercises contain an error that keeps them from compiling, and it's up to you to fix it! Some exercises are also run as tests, but rustlings handles them all the same. -
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Build Your Own OpenClaw
A step-by-step guide to build your own AI agent
Build Your Own OpenClaw is a step-by-step educational framework that teaches developers how to construct a fully functional AI agent system from scratch, gradually evolving from a simple chat loop into a multi-agent, production-ready architecture. The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable... -
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Magnitude
Vision AI browser agent for automation, testing, and extraction
...Developers can use it to automate repetitive web tasks, integrate services without APIs, or build advanced browser-based agents. It also provides flexible abstraction levels, allowing both high-level task execution and precise low-level control of actions like mouse movements and keyboard input. -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations... -
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Flock
Flock is a workflow-based low-code platform for building chatbots
Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on... -
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Prompt in-context learning
Resources for in-context learning and prompt engineering
...The project gathers research papers, tutorials, prompt examples, and practical guides that help developers and researchers learn how to design effective prompts for models such as GPT-3, ChatGPT, and other foundation models. In-context learning refers to the ability of language models to learn a task directly from examples provided in the prompt without updating the modelâs parameters, allowing them to perform new tasks through demonstration alone. The repository organizes this growing field by categorizing materials related to prompt design strategies, chain-of-thought reasoning, agents, and general large language model usage. ... -
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ERNIE
The official repository for ERNIE 4.5 and ERNIEKit
ERNIE is an open-source large-model toolkit and model family from the PaddlePaddle ecosystem that focuses on training, fine-tuning, compression, and practical application of ERNIE large language models. The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment. It supports both full-parameter training and parameter-efficient approaches so teams can choose... -
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Excalidraw MCP
Fast and streamable Excalidraw MCP App
...Rather than being just a static whiteboard, Excalidraw-MCP serves diagrams in real time using an MCP backend and streams interactive visual output back to the client, letting AI tools create shapes, connectors, text, and entire diagrams as part of conversational or task-based sessions. Its design supports fast, streamable rendering with smooth viewport control and optional fullscreen editing so that diagrams feel live and fluid as they evolve. Users can deploy it locally or via services like Vercel, then configure their MCP host to point at the Excalidraw-MCP endpoint, so prompts like âdraw an architecture diagramâ yield immediate visual results within chat. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhereâacross 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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Zypher Agent
A minimal yet powerful framework for creating AI agents
Zypher Agent is an open-source framework for building full-featured AI agents that can be embedded directly into applications, enabling reactive decision loops where the agent dynamically chooses its next actions. Unlike workflow-style orchestrators, it uses a reactive agent loop that interprets the task, reasons about next steps via LLMs, and integrates directly with extensible tools and external services. Zypher prioritizes native support for multiple model providers such as OpenAI and Anthropic Claude, while also offering a rich set of tools for file system operations, search, and terminal execution. It includes mechanisms like checkpointing to version agent decision states, concurrency protections, error handling, and operational interceptors to customize behavior after each reasoning step. ... -
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nanobot
đ 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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MAI-UI
Real-World Centric Foundation GUI Agents
...Unlike traditional UI frameworks, MAI-UI emphasizes realistic deployment by supporting agentâuser interaction (clarifying ambiguous instructions), integration with external tool APIs using MCP calls, and a deviceâcloud collaboration mechanism that dynamically routes computation to on-device or cloud models based on task state and privacy constraints. -
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Prompt Engineering Techniques
Collection of tutorials for Prompt Engineering techniques
...It contains around twenty-plus hands-on Jupyter notebooks, each dedicated to a specific technique such as basic prompt structures, prompt templates and variables, zero-shot prompting, few-shot prompting, chain-of-thought, self-consistency, constrained generation, role prompting, task decomposition, and more. The tutorials are designed to be practical; you can run them directly, examine the prompts, and see how small changes affect model behavior and quality. The repository is framed as a âtechniques libraryâ that complements a more detailed book, which expands on the same topics with deeper explanations and exercises. ... -
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GenAI Agents
Implementations for various Generative AI Agent techniques
...The repo is structured by categories like beginner agents, framework tutorials, educational agents, business agents, creative agents, analysis agents, news bots, shopping assistants, task management agents, QA bots, and advanced systems such as controllable RAG agents. For each agent, you typically get an overview, implementation notes, and external resources (blog posts, videos, documentation) to deepen understanding. -
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Go Backend Clean Architecture
A Go (Golang) Backend Clean Architecture project with Gin, MongoDB
This repository is a production-minded Go backend starter that applies Clean Architecture to keep business logic independent from frameworks, databases, and delivery mechanisms. It organizes code into layersâdomain, use cases, interfaces/adaptersâso swapping an HTTP framework or database does not ripple through core logic. The template includes well-chosen scaffolding for configuration, logging, dependency injection, error handling, and request validation so teams can focus on business... -
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OpenAI CS Agents Demo
Demo of a customer service use case implemented with the OpenAI Agents
This repository is a customer service agent demo built using the OpenAI Agents SDK to showcase how to build a production-style conversational assistant for use cases like airline customer support. It consists of two major parts: a Python backend that orchestrates agent logic (tool calls, handoffs, memory, routing) and a Next.js UI for chat interaction and visualizing agent state. The demo covers tasks youâd expect in customer service: changing flights, checking status, answering FAQs, etc.... -
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Whenever
Cron jobs in Ruby
Whenever (javan/whenever) is a Ruby gem that provides a clean, Ruby DSL for defining and managing cron jobs within your application. Rather than editing system cron tables by hand, you describe scheduled tasks in a schedule.rb file using methods like every, runner, command, or rake. The gem then compiles this schedule into a standard crontab format and installs it for you, handling all the necessary quoting, environment setup, and command path resolution. It supports specifying execution... -
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Dockside
Develop, stage and test on-prem or in your private cloud
Develop, stage, and test on-prem or in your private cloud. Dockside is a tool for provisioning lightweight access-controlled IDEs, staging environments, and sandboxes - aka 'devtainers' - on local machines, on-premises raw metal or VM, or in the cloud. Dockside is a tool for provisioning lightweight access-controlled IDEs, staging environments and sandboxes - aka devtainers - on the local machines, self-hosted on-premises on bare metal or VM, or in the cloud. By provisioning a devtainer for... -
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Habitat-Lab
A modular high-level library to train embodied AI agents
Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks. Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. Configuring and... -
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KaibanJS
JS-native framework for building and managing multi-agent systems
...Harness the power of specialization by configuring AI agents to excel in distinct, critical functions within your projects. This approach enhances the effectiveness and efficiency of each task, moving beyond the limitations of generic AI. Just as professionals use specific tools to excel in their tasks, enable your AI agents to utilize tools like search engines, calculators, and more to perform specialized tasks with greater precision and efficiency. -
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gradle-maven-publish-plugin
A Gradle plugin that publishes your Android and Kotlin libraries
A Gradle plugin that publishes your Android and Kotlin libraries, including sources and javadoc, to Maven Central or any other Nexus instance. Gradle plugin that creates a publish task to automatically upload all of your Java, Kotlin or Android libraries to any Maven instance. This plugin is based on Chris Banes initial implementation and has been enhanced to add Kotlin support and keep up with the latest changes. No need to know how publishing works for different project types. AGP provides an API to configure publishing, java-library too, Kotlin Multiplatform does most things automatically but not everything. ... -
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipelineâs efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. -
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Suave
Suave is a simple web development F# library
Suave is a simple web development F# library providing a lightweight web server and a set of combinators to manipulate route flow and task composition. Suave is inspired in the simplicity of Happstack and born out of the necessity of embedding web server capabilities in my own applications. Suave supports Websocket, HTTPS, multiple TCP/IP bindings, Basic Access Authentication, Keep-Alive. Suave also takes advantage of F# asynchronous workflows to perform non-blocking IO. -
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Healthchecks
A cron monitoring tool written in Python & Django
...When your job does not ping Healthchecks.io on time, Healthchecks.io alerts you! Update your job to send an HTTP request to the ping URL every time the job runs. A list of your checks, one for each Cron job, daemon or scheduled task you want to monitor. Give names and assign tags to your checks to easily recognize them later. -
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Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
...By design, both encoder and decoder produces a list of tensors, from fine (high-resolution, indexed 0) to coarse (low-resolution) feature maps. Access to all intermediate feature maps is beneficial if you want to apply deep supervision losses on them or encoder-decoder of object detection task.
