27 projects for "decomposition" with 2 filters applied:

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  • 1
    Qwen-Image-Layered

    Qwen-Image-Layered

    Qwen-Image-Layered: Layered Decomposition for Inherent Editablity

    Qwen-Image-Layered is an extension of the Qwen series of multimodal models that introduces layered image understanding, enabling the model to reason about hierarchical visual structures — such as separating foreground, background, objects, and contextual layers within an image. This architecture allows richer semantic interpretation, enabling use cases such as scene decomposition, object-level editing, layered captioning, and more fine-grained multimodal reasoning than with flat image encodings alone. By combining text and structured image representations, it aims to facilitate tasks where both descriptive and structural understanding are important, such as detailed image QA, interactive image editing via prompt layers, and image-conditioned generation with structural control. ...
    Downloads: 1 This Week
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  • 2
    super-agent-party

    super-agent-party

    All-in-one AI companion! Desktop girlfriend + virtual streamer

    ...The platform is primarily intended as a research and demonstration environment for experimenting with agent collaboration strategies. Developers can use it to study coordination patterns, communication protocols, and task decomposition in multi-agent systems.
    Downloads: 1 This Week
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  • 3
    Learn Claude Code

    Learn Claude Code

    Bash is all you need, write a claude code with only 16 line code

    Learn Claude Code is an educational repository that teaches how modern AI coding agents work by walking learners through a sequence of progressively more complex agent implementations, starting with a minimal Bash-based agent and culminating in agents with explicit planning, subagents, and skills. It emphasizes a hands-on learning path where each version (from v0 to v4) adds conceptual building blocks like the core agent loop, todo planning, task decomposition, and domain knowledge skills, illuminating the patterns behind what makes a true AI agent tick. The goal is to demystify agent architectures like Claude Code by having learners build simplified versions themselves and observe how tools, memory management, planning constraints, and context isolation contribute to reliable agent behavior. ...
    Downloads: 1 This Week
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  • 4
    DeepSeek Prover V2

    DeepSeek Prover V2

    Advancing Formal Mathematical Reasoning via Reinforcement Learning

    DeepSeek-Prover-V2 is DeepSeek’s specialized model for formal theorem proving, particularly targeting proof in Lean 4. The repository describes how they use recursive proof decomposition by prompting DeepSeek-V3 to break complex theorems into subgoals, synthesize proof sketches, and then combine them to bootstrap training data. They then fine-tune via reinforcement learning with binary correct/incorrect feedback to integrate informal reasoning with formal proof behavior. The repo releases two model sizes (7B and 671B) and provides evaluation performance (e.g. pass rates on MiniF2F, results on ProverBench) as well as prompt / usage examples for proof generation in Lean 4. ...
    Downloads: 0 This Week
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  • 5
    OpenManus

    OpenManus

    Open-source AI agent framework

    OpenManus is an open-source AI agent framework designed to autonomously execute complex, multi-step tasks by combining reasoning, planning, and tool use. It enables developers to build agents that can think, act, and iterate toward goals rather than simply responding to prompts. The platform emphasizes task decomposition, allowing agents to break down objectives into smaller steps and execute them sequentially or recursively. OpenManus supports integration with external tools, APIs, and environments, making it suitable for real-world automation workflows. It is built to be flexible and extensible, enabling customization of agent behaviors, tools, and reasoning strategies. ...
    Downloads: 10 This Week
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  • 6
    AGI

    AGI

    The first distributed AGI system

    ...It aims to provide a foundation for creating agents that can reason, plan, and execute tasks across diverse domains by integrating multiple AI capabilities into a unified system. The project typically explores concepts such as agent orchestration, memory systems, task decomposition, and decision-making loops, enabling the development of more generalized and adaptive AI behaviors. It is designed to be extensible, allowing developers to plug in different models, tools, and data sources to enhance agent performance. The framework encourages experimentation with AGI-like architectures, making it useful for researchers and developers interested in advancing beyond narrow AI applications.
    Downloads: 2 This Week
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  • 7
    Oh My OpenAgent

    Oh My OpenAgent

    The best agent harness

    Oh My OpenAgent is a large-scale, open-source agent orchestration framework that aims to provide a fully unified and extensible environment for AI-powered software development and automation. It builds on the idea that no single model is sufficient, instead enabling coordinated use of multiple models for reasoning, creativity, speed, and cost efficiency within a single workflow. The system is designed as a comprehensive agent harness where tasks are automatically decomposed, delegated, and...
    Downloads: 5 This Week
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  • 8
    Rust Port

    Rust Port

    The Rust workspace under rust/ is the current systems-language port

    Rust Port is an open-source reconstruction and experimentation framework derived from leaked or reverse-engineered versions of advanced AI coding agents, designed to replicate and extend the capabilities of agentic development systems. It functions as a programmable coding assistant that operates through autonomous workflows, enabling users to generate, modify, and analyze code with minimal manual intervention. The project emphasizes agent-based execution, where tasks are broken down into...
    Downloads: 1 This Week
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  • 9
    AI Agents From Scratch

    AI Agents From Scratch

    Demystify AI agents by building them yourself. Local LLMs

    ...It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. By building agents incrementally, the project helps learners grasp concepts such as decision loops, task decomposition, and environment interaction.
    Downloads: 2 This Week
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  • 10
    Auto-Deep-Research

    Auto-Deep-Research

    Your Fully-Automated Personal AI Assistant

    Auto-Deep-Research is a system designed to fully automate deep research workflows using language models, retrieval, planning, and multi-stage reasoning to produce structured research artifacts such as surveys, benchmarks, reports, and even prototypes without heavy human intervention. Users provide a research topic or multifaceted goal, and the system autonomously breaks the objective down into subtasks like literature collection, critical summarization, cross-comparison, citation extraction,...
    Downloads: 0 This Week
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  • 11
    SAG

    SAG

    SQL-Driven RAG Engine

    SAG is an open-source SQL-driven retrieval-augmented generation engine that dynamically constructs knowledge graphs during query processing. Instead of relying on a static knowledge graph prepared in advance, the system automatically builds relational structures between entities while processing user queries. Documents are first decomposed into atomic semantic events, which are then represented using multidimensional natural language vectors. These vectors allow the system to identify...
    Downloads: 1 This Week
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  • 12
    CoStrict

    CoStrict

    Strict AI coder for enterprises, quality first

    ...Unlike typical AI coding tools that prioritize speed over rigor, CoStrict introduces a “strict mode” methodology that enforces disciplined processes such as requirements analysis, architecture planning, task decomposition, and test generation before producing code. This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. ...
    Downloads: 0 This Week
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  • 13
    AG2

    AG2

    Framework for building and orchestrating multi-agent AI systems

    AG2 is an open source framework designed to support the creation and coordination of multiple AI agents working together to solve complex tasks. It provides abstractions that allow developers to define agents with distinct roles, responsibilities, and communication patterns, enabling collaborative problem-solving workflows. AG2 focuses on making multi-agent systems more accessible by simplifying how agents are configured, connected, and executed. It includes mechanisms for agent-to-agent...
    Downloads: 1 This Week
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  • 14
    Youtu-GraphRAG

    Youtu-GraphRAG

    Vertically Unified Agents for Graph Retrieval-Augmented Reasoning

    Youtu-GraphRAG is a research framework developed by Tencent for performing complex reasoning using graph-based retrieval-augmented generation. The system combines knowledge graphs, retrieval mechanisms, and agent-based reasoning into a unified architecture designed to handle knowledge-intensive tasks. Instead of relying solely on text retrieval, the framework organizes information into structured graph schemas that represent entities, relationships, and attributes. These structures allow the...
    Downloads: 0 This Week
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  • 15
    Fractals

    Fractals

    Fractals is a recursive task orchestrator for agent swarm

    ...The framework runs these subtasks in isolated Git worktrees so agents can work on separate components of a project without interfering with one another. By coordinating these agents through a recursive task decomposition strategy, the system allows large problems to be solved collaboratively by multiple AI processes. The architecture is designed to experiment with large-scale agent coordination and distributed problem solving.
    Downloads: 0 This Week
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  • 16
    Prompt Engineering Techniques

    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 “techniques library” that complements a more detailed book, which expands on the same topics with deeper explanations and exercises. ...
    Downloads: 0 This Week
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  • 17
    Armadillo

    Armadillo

    fast C++ library for linear algebra & scientific computing

    * Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:...
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    Downloads: 2,695 This Week
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  • 18
    Free-Auto-GPT

    Free-Auto-GPT

    Free AutoGPT enables autonomous AI tasks without paid APIs

    ...It is suitable for developers, learners, and hobbyists who want to explore AI-driven automation without subscription requirements. It provides a lightweight implementation that highlights core AutoGPT concepts such as task decomposition, iteration, and independent execution in a simplified environment.
    Downloads: 1 This Week
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  • 19
    Computational Linear Algebra for Coders

    Computational Linear Algebra for Coders

    Free online textbook of Jupyter notebooks

    ...Instead of emphasizing purely theoretical mathematics, the project takes a programming-oriented approach that helps developers understand how linear algebra algorithms are implemented in real computational systems. The course explores topics such as matrix decomposition, numerical stability, and optimization techniques that are essential for machine learning and data science applications.
    Downloads: 0 This Week
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  • 20
    SHOP2 is a domain-independent automated-planning system based on ordered task decomposition, a type of Hierarchical Task Network (HTN) planning. Development is no longer done on sf; only file hosting now. WARNING: Java code here is not maintained....
    Downloads: 2 This Week
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  • 21
    ...It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
    Downloads: 0 This Week
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  • 22
    BADGr

    BADGr

    Toolbox for Box Approximation, Decomposition, and Grasping

    BADGr, the BoxGrasping toolbox, is a package for Box Approximation, Decomposition, and Grasping. The toolbox was developed in the Computer Vision & Active Perception Lab, at the Royal Institute of Technology, as a participant of the EU research project PACO-PLUS, and published at the project's end in Summer 2010. BADGr provides modules to approximate the shape of a point cloud (possibly from sensor data) by box primitives.
    Downloads: 1 This Week
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  • 23
    superseded by SgpDec http://sgpdec.sf.net Java implementation of the holonomy algorithm for the algebraic hierarchical decomposition of finite state automata.
    Downloads: 0 This Week
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  • 24
    The aim of the PL-PSF project is to create a generic domain-independent combinatorial problem solver. It uses a petri-nets based model to represent the problems and problem decomposition/abstraction with graph topology analysis to solve them.
    Downloads: 0 This Week
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  • 25
    SB-MASE is aimed at students and researchers in AI, for simulation and control of agents and robots. It uses task based decomposition and the subsumption architecture as its core control mechanisms and includes numerous possibilities for adding plug-ins.
    Downloads: 0 This Week
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