Search Results for "task" - Page 15
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Showing 2024 open source projects for "task"
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DeerFlow
Deep Research framework, combining language models with tools
...“planner,” “searcher,” “coder,” “report generator”) that collaborate in a structured workflow, allowing tasks like literature reviews, data gathering, data analysis, code execution, and final report generation to be largely automated. It supports asynchronous task coordination, modular tool integration, and orchestrates the data flow between agents — making it suitable for large-scale or multi-stage research pipelines. Users can deploy it locally or on server infrastructure, integrate custom tools, and benefit from its flexible configuration. -
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Super Magic
All-in-one AI productivity platform with agents, workflows, and IM
Magic is an open source all-in-one AI productivity platform designed to help organizations build, deploy, and scale AI-driven applications efficiently. It is not a single tool but a complete product ecosystem composed of multiple integrated systems that work together to enhance productivity across different business scenarios. Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error... -
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Android Use
Automate native Android apps with AI using accessibility APIs
android-action-kernel is an open source Python library designed to let AI agents control and automate native Android applications running on real devices or emulators. It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state... -
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ADK Go
Code-first Go toolkit for building, evaluating, and deploying AI agent
...ADK-Go applies traditional software engineering principles to agent development, making it easier to structure, test, and maintain complex agent-based systems. It supports building both simple task-oriented agents and more advanced multi-agent architectures that collaborate to perform workflows. It is designed to be modular and flexible, allowing developers to integrate custom tools, external services, or existing functionality into agent workflows. Although optimized for certain AI ecosystems, ADK-Go is model-agnostic and can work with different models and deployment environments. -
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The Pope Bot
Autonomous AI agent that you can configure and build
The Pope Bot is an autonomous AI agent framework that lets users configure and run an AI-powered agent that can perform tasks continuously, day in and day out, by leveraging GitHub Actions, commit history, and secure workflows. It’s designed so that every action taken by the agent is logged as a git commit, giving users complete visibility into what the agent did, why it did it, and when, which makes actions auditable and reversible. The framework treats the repository itself as the agent’s... -
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Docspell
Assist in organizing your piles of documents
...You can associate tags, set correspondent,s and lots of other predefined and custom metadata. If your documents are associated with such metadata, you can quickly find them later using the search feature. However adding this manually is a tedious task. Docspell can help by suggesting correspondents, guessing tags or finding dates using machine learning. It can learn metadata from existing documents and find things using NLP. This makes adding metadata to your documents a lot easier. For machine learning, it relies on the free (GPL) Stanford Core NLP library. -
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Projectile
Project Interaction Library for Emacs
...Projectile will auto-detect pretty much every popular project type out of the box and you can easily extend it with additional project types. Projectile tries to be practical - portability is great, but if some external tools could speed up some task substantially and the tools are available, Projectile will leverage them. -
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sbt
sbt, the interactive build tool
...One of the examples of a Scala-specific feature is the ability to cross-build your project against multiple Scala versions. build.sbt is a Scala-based DSL to express parallel processing task graph. Typos in build.sbt will be caught as a compilation error. With Zinc incremental compiler and file watch (~), edit-compile-test loop is fast and incremental. Adding support for new tasks and platforms (like Scala.js) is as easy as writing build.sbt. Join 100+ community-maintained plugins to share and reuse sbt tasks. Continuous compilation and testing with triggered execution. ... -
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The Minimalist Entrepreneur
Claude Code skills based on The Minimalist Entrepreneur
The Minimalist Entrepreneur repository is a curated collection of structured “skills” designed to enhance the capabilities of AI systems by providing reusable patterns, workflows, and domain-specific knowledge. It acts as a modular layer that can be integrated into AI agents to improve how they perform tasks such as reasoning, coding, communication, and decision-making. The project emphasizes composability, allowing individual skills to be combined into larger workflows that solve more... -
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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Magentic UI
A research prototype of a human-centered web agent
Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight. -
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ANTIRTOS
Function pointers queues classes library for Arduino
ANTIRTOS is a compact real-time operating system (RTOS) written in ANSI C for microcontrollers and embedded systems. It is designed to be simple, portable, and efficient, making it ideal for resource-constrained environments such as IoT devices, robotics, and educational hardware projects. ANTIRTOS features a basic scheduler, support for cooperative and preemptive multitasking, and offers portability across different CPU architectures with minimal changes. Its simplicity and clarity make it... -
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FastAgency
The fastest way to bring multi-agent workflows to production
FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks. -
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sktime
A unified framework for machine learning with time series
...It features dedicated time series algorithms and tools for composite model building such as pipelining, ensembling, tuning, and reduction, empowering users to apply an algorithm designed for one task to another. -
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LaravelS
LaravelS is an out-of-the-box adapter between Laravel/Lumen and Swoole
LaravelS is an out-of-the-box adapter between Laravel/Lumen and Swoole. LaravelS uses Swoole's Synchronous IO mode, the larger the worker_num setting, the better the concurrency performance, but it will cause more memory usage and process switching overhead. If one request takes 100ms, in order to provide 1000QPS concurrency, at least 100 Worker processes need to be configured. Create WebSocket Handler class, and implement interface WebSocketHandlerInterface. The instant is automatically... -
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Better Harness
Help your coding agents get better at getting better
Better Harness is an open-source evaluation system for improving the workflows used by AI coding agents. Instead of reviewing only the final code change, it examines how an agent understood the task, executed work, validated results, delivered safely, and captured reusable lessons. It gathers project and session evidence while marking missing or unobserved behavior explicitly. Reports organize findings across five Agent Work Loop dimensions and connect each conclusion to visible supporting evidence. Supported gaps become prioritized recommendations with expected outcomes, repair boundaries, and acceptance checks. ... -
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Claude Code Router
Use Claude Code as the foundation for coding infrastructure
Claude Code Router is a tool for routing Claude Code requests to different model providers and customizing how those requests are handled. It acts as a configurable layer between Claude Code and multiple LLM backends, allowing users to control routing, provider selection, transformations, and workflow behavior. The project is useful for developers who want to keep the Claude Code interface while experimenting with different models, cost profiles, and specialized request handling. It supports... -
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AutoAgent AI
Autonomous harness engineering
AutoAgent is an experimental AI framework focused on autonomous agent engineering, where a meta-agent iteratively improves another agent’s architecture without direct human intervention. Instead of manually tuning prompts or workflows, developers define high-level goals in a configuration file, and the system continuously modifies its own tools, orchestration, and logic based on benchmark performance. It operates through a loop of testing, analyzing failures, and refining the agent’s... -
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Open Agents
An open source template for building cloud 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. The project also includes examples and templates that demonstrate how to build and deploy agents for real-world applications. ... -
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Factory AI
Agent-Native Software Development
Factory is an agent-native software development platform designed to automate and accelerate the entire software engineering lifecycle by leveraging AI agents that can understand, modify, and manage codebases in real time. At its core, the system introduces the concept of “Droids,” specialized AI agents that operate across development environments such as the command line, web interfaces, project management tools, and communication platforms, enabling seamless interaction with engineering... -
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OpenSpace
OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving
OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also focuses on cost efficiency by reducing redundant computations and reusing successful workflows, significantly lowering token usage in repeated tasks. ... -
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Oh My codeX (OMX)
Your codex is not alone. Add hooks, agent teams, HUDs
Oh My codeX (OMX) is a multi-agent orchestration layer designed to extend the capabilities of OpenAI Codex CLI by introducing structured teamwork, automation, and advanced workflow management. It addresses limitations in the base Codex environment, such as the lack of hooks, agent coordination, and persistent execution, by layering a shell-based system that enables richer interaction patterns. The project transforms a single AI coding assistant into a coordinated system of specialized agents... -
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Big-AGI
AI suite powered by state-of-the-art models and providing advanced AI
Big-AGI is a comprehensive, open-source AI workspace built to serve as a powerful multi-model interface for developers, researchers, and professionals who want deep control over generative AI workflows and outputs. It unifies access to multiple large language models (LLMs) and AI services through a modern web UI that emphasizes efficient interaction, flexibility, and extensibility, enabling users to conduct multi-model chats, execute code, generate images, and perform voice or text-based... -
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Deep Research
Use any LLMs (Large Language Models) for Deep Research
Deep Research is a local-first research agent that orchestrates multiple LLMs to generate in-depth reports in minutes. It combines “thinking” and “task” model roles with live internet access to plan, search, read, and synthesize findings into structured outputs. The project emphasizes privacy: processing and storage happen locally, avoiding server-side retention of your queries and notes. A simple web UI lets you enter topics and configure models, while the backend streams progress as sources are fetched and arguments are weighed. ... -
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HumanEval
Code for the paper "Evaluating Large Language Models Trained on Code"
...It consists of hand-written programming problems with unit tests, designed to assess functional correctness rather than superficial metrics like text similarity. Each task includes a natural language prompt and a function signature, requiring the model to generate an implementation that passes all provided tests. The benchmark has become a standard for evaluating code generation models, including those in the Codex and GPT families. Researchers can use the dataset to run reproducible comparisons across models and track improvements in functional code synthesis. ... -
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CLIP
CLIP, Predict the most relevant text snippet given an image
...It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. The repository provides code for model architecture, preprocessing transforms, evaluation pipelines, and example inference scripts. Because it generalizes to arbitrary labels via text prompts, CLIP is a powerful tool for tasks that involve interpreting images in terms of descriptive language.
