Search Results for "tasks" - Page 23
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Showing 1208 open source projects for "tasks"
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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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Ralph Orchestrator
An improved implementation of the Ralph Wiggum technique
Ralph Orchestrator is an AI workflow orchestration system designed to coordinate multiple agents, tools, and processes into structured pipelines that can execute complex tasks autonomously. It provides a framework for defining workflows where different components, such as LLMs, APIs, and custom functions, collaborate to achieve specific objectives. The system emphasizes modularity and composability, allowing developers to design workflows as reusable building blocks that can be combined or extended as needed. ... -
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LiteParse
A fast, helpful, and open-source document parser
...It also includes mechanisms for validation and error handling, ensuring that outputs conform to expected schemas and reducing the need for manual postprocessing. The library is particularly useful for tasks such as data extraction, document processing, and building pipelines that require structured outputs from natural language input. -
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CodeMachine
CLI tool for multi-agent workflows and automated code generation
CodeMachine CLI is a command-line orchestration engine designed to run coordinated multi-agent workflows locally. It enables developers to transform high-level specifications into production-ready code by managing planning, architecture, implementation, testing, and validation within a unified environment. CodeMachine CLI supports parallel execution through multiple specialized agents, allowing faster development cycles and scalable automation. Built for flexibility, it can handle anything... -
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One-Person Company
One-Person Company AI Tools Series
One Person Company is an open-source project that provides a conceptual and technical framework for building fully automated businesses powered by AI agents, enabling individuals to operate scalable digital ventures with minimal human intervention. It explores the idea of leveraging AI tools for tasks such as content generation, marketing, customer support, and product development, effectively replacing traditional team structures with intelligent automation. The repository includes workflows, strategies, and system designs that demonstrate how multiple AI agents can collaborate to run different aspects of a business in a coordinated manner. ... -
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OSMO
The developer-first platform for scaling complex Physical AI workloads
...The platform addresses what NVIDIA refers to as the “three computer problem” by unifying these stages into a single pipeline defined through simple YAML configurations. It enables users to orchestrate tasks across Kubernetes clusters, automatically managing dependencies, scheduling, and resource allocation without requiring deep infrastructure expertise. -
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VIPER
AI-powered red team platform for adversary simulation toolkit
...It includes a large collection of built-in modules that cover multiple stages of the MITRE ATT&CK framework, enabling realistic and structured attack simulations. Viper also incorporates automation features and workflow orchestration, helping teams streamline repetitive tasks and maintain continuous monitoring of target environments. A notable aspect of the project is its integration of a large language model agent, which assists with decision-making, parameter handling, and analysis during operations. -
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Claude Code Hooks Mastery
Master Claude Code Hooks
...Although the project itself doesn’t include a single coherent application, it functions as a curated collection of advanced hook examples, best practices, and coding patterns that show how to tailor Claude Code to specific use cases such as automated CI workflows, custom command triggers, and integrations with external tools. The repository is part of a larger ecosystem of Claude Code tooling that enables natural-language-driven coding tasks, and the hooks contained here help users go beyond default behaviors to solve real problems efficiently. -
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Zero
Experience email the way you want with Mail0
...It combines a unified inbox experience with privacy-first architecture so your email data stays under your control without third-party tracking or data harvesting. The system enhances traditional email workflows by integrating AI assistance for tasks such as summarizing messages, suggesting replies, prioritizing conversations, and helping users manage their inbox more intelligently. With a clean, customizable web interface built on modern technologies, Zero makes it pleasant to navigate mail, search through messages, and organize threads without feeling cluttered or slow. -
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Deep Learning Is Nothing
Deep learning concepts in an approachable style
...Implementations favor small, readable examples—often NumPy first—to show how forward and backward passes work without depending solely on high-level frameworks. Once the fundamentals are clear, the material extends to CNNs, RNNs, and attention mechanisms, explaining why each architecture suits particular tasks. Practical sections cover data pipelines, regularization, and evaluation, emphasizing reproducibility and debugging techniques. The goal is to replace buzzwords with intuition so learners can reason about architectures and training dynamics with confidence. -
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AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
AWorld (Agent World) is an agent runtime/framework. It supports building, evaluating, and training self-improving intelligent agents and multi-agent systems (MAS). It is designed to provide infrastructure for agent orchestration, iterative learning, and environment interaction at scale. Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). The system is intended to help agents evolve via experience. It provides features to... -
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AlphaGenome
Programmatic access to the AlphaGenome model
...The model analyzes DNA sequences of up to 1 million base pairs in length and can deliver predictions at single-base-pair resolution for most outputs. AlphaGenome achieves state-of-the-art performance across a range of genomic prediction benchmarks, including numerous diverse variant effect prediction tasks. -
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Godot RL Agents
An Open Source package that allows video game creators
godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training set). ... -
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AutoKeras
AutoML library for deep learning
...If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the best detailed configuration for you. Moreover, you can override the base classes to create your own block. -
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MimiClaw
Run OpenClaw on a $5 chip
...By running pure C on a bare-metal chip, MimiClaw brings AI interactions and persistent memory to a tiny USB-powered device you can carry in your pocket. You connect the device to Wi-Fi and chat with it using Telegram, making it a convenient always-on assistant for tasks like reminders, quick lookups, or custom AI interactions. Even though it’s running on minimal hardware, MimiClaw maintains local memory that persists across power cycles, enabling context continuity over time without relying on cloud services. Its architecture emphasizes privacy, low power, and portability, ideal for personal or hobbyist use cases where privacy and local control matter. -
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Zypher Agent
A minimal yet powerful framework for creating AI agents
...It includes mechanisms like checkpointing to version agent decision states, concurrency protections, error handling, and operational interceptors to customize behavior after each reasoning step. Its API is built with TypeScript and is suitable for production contexts where agents must handle real tasks with configurability, logging, and observability. -
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InfiAgent
Build your own Cowork, AI Scientist and other SoTA Agents
infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. ... -
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GenAI Agents
Implementations for various Generative AI Agent techniques
...It spans a spectrum from simple conversational bots and basic question-answering agents to complex multi-agent systems that coordinate on research, education, business workflows, and creative tasks. The implementations leverage modern frameworks such as LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, and more, showing how each can be wired into realistic agent workflows. 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. ... -
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Janus
Unified Multimodal Understanding and Generation Models
...The design tackles long-standing conflicts in multimodal models: namely that the visual encoder has to serve both analysis (understanding) and synthesis (generation) roles. By splitting those pathways but keeping one unified core transformer, Janus maintains flexibility and achieves strong performance across tasks previously requiring distinct architectures. The repository includes pretrained checkpoints (for example 1.3B and 7B parameter versions), a Gradio demo, and guidance for local deployment. -
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Sol Advisor
Codex-native architect orchestration with Luna and Terra
...Its default native workflow delegates implementation to a Terra agent and then requires a fresh Sol review in a separate context. An alternative Luna lane can create user-visible Codex application tasks when the user explicitly authorizes that mode. This separation is intended to reduce context contamination while preserving clear responsibility for quality and architectural decisions. The workflow can monitor implementation, inspect diffs, request corrections, coordinate dependent work, and control final approval. It is distributed as a Codex plugin with companion custom-agent definitions for the native execution path. -
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i-have-adhd
A skill for your coding agent to stop it from burying the answer
i-have-adhd is a compact instruction skill that makes coding assistants produce more direct and ADHD-friendly responses. It asks the agent to lead with the next action instead of opening with background, praise, or conversational filler. Multi-step tasks are numbered, tangents are suppressed, and lists are intentionally kept short. The style also restates the current state, makes completed progress visible, and describes errors without unnecessary drama. Every response should end with one concrete next step rather than a generic invitation or closing phrase. The skill can be installed as a plugin for Claude Code and Codex, with guidance available for other coding agents. ... -
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TencentDB Agent Memory
TencentDB Agent Memory delivers fully local long-term memory for AI
TencentDB Agent Memory is a local long-term memory system for AI agents. It uses symbolic short-term memory and layered long-term memory instead of storing everything as flat vector fragments. For active tasks, it offloads heavy logs into external files and keeps a compact Mermaid canvas in the agent context. For personalization, it organizes memory from raw conversations into atoms, scenarios, and persona-level knowledge. The design keeps high-level memory inspectable while preserving a drill-down path back to raw evidence. It is built for OpenClaw and Hermes-style agent workflows that need lower token usage, better continuity, and no external API dependency. -
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Codey
The home for Codey releases, updates, and the developer community
...Codey combines a fast keyboard-driven TUI with a cross-platform desktop app for developers who want AI assistance close to their coding workflow. It can help read, write, refactor, and inspect code while also running commands and coordinating multi-step engineering tasks. The project uses the Model Context Protocol to connect agent workflows with external tools and richer development context. This repository does not contain the private application source, but it hosts releases, installers, updater metadata, guides, prompts, skills, workflows, issues, and discussions. It is useful for developers who want to install Codey, follow updates, contribute resources, or participate in the project community. -
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Harness-1
Ultra Recipe for Training Long-Horizon Search Agents
Harness-1 is a 20B search agent trained with reinforcement learning inside a stateful retrieval harness. It is designed for long-horizon search tasks where the model must search, inspect documents, curate evidence, verify claims, and decide when enough evidence has been gathered. The harness externalizes search state, including candidate documents, evidence links, verification records, and budget-aware context. This lets the policy focus on higher-level decisions instead of trying to keep every detail inside the model context. ... -
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Claude Code Router
Use Claude Code as the foundation for coding infrastructure
...It supports project-level configuration, making it possible to adapt behavior depending on the codebase or use case. It also includes an extensible agent-oriented architecture for custom tools and workflows, including support for image-related tasks. Overall, it gives technical users more control over Claude Code infrastructure without abandoning the familiar coding assistant workflow.
