Showing 782 open source projects for "or-tools"

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    Agentic Data Scientist

    Agentic Data Scientist

    An end-to-end Data Scientist

    ...Each agent is designed to independently call functions, interact with data sources, and adapt to uncertainties during processing, enabling iterative refinement of models without manual coordination. The framework supports interoperability with existing data tools and libraries, letting the agents leverage libraries like pandas, scikit-learn, and visualization frameworks to perform real computations rather than mock demonstrations.
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  • 2
    HN Time Capsule

    HN Time Capsule

    Analyzing Hacker News discussions from a decade ago in hindsight

    HN Time Capsule is a creative and nostalgic project that captures and preserves snapshots of Hacker News content over time, providing a historical look at how topics, discussions, and popular threads have evolved. Rather than functioning like a live aggregator, it stores periodic captures of posts and comments, creating a time capsule that lets researchers, enthusiasts, and historians trace changes in sentiment, technology trends, and community priorities across different eras of the Hacker...
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  • 3
    Engram

    Engram

    A New Axis of Sparsity for Large Language Models

    ...Engineered with speed and memory efficiency in mind, Engram supports batched indexing, incremental updates, and custom distance metrics so developers can tailor search behaviors to their domain’s needs. In addition to raw similarity search, the project includes tools for clustering, ranking, and filtering results, enabling richer user experiences like “related content”, semantic auto-completion, and contextual filtering.
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  • 4
    Anthropic's Original Performance

    Anthropic's Original Performance

    Anthropic's original performance take-home, now open for you to try

    ...The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under constraints. This take-home includes starter code, tests, and tools to debug performance, aiming to measure how effectively one can apply algorithmic improvements and optimizations. Because it’s framed around beating baseline scores — and even outperforming previous automated systems — it encourages both deep knowledge of Python and creative problem-solving.
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  • 5
    Atropos

    Atropos

    Language Model Reinforcement Learning Environments frameworks

    Atropos is a comprehensive open-source framework for reinforcement learning (RL) environments tailored specifically to work with large language models (LLMs). Designed as a scalable ecosystem of environment microservices, Atropos allows researchers and developers to collect, evaluate, and manage trajectories (sequences of actions and outcomes) generated by LLMs across a variety of tasks—from static dataset benchmarks to dynamic interactive games and real-world scenario environments. It...
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  • 6
    Coconut

    Coconut

    Training Large Language Model to Reason in a Continuous Latent Space

    Coconut is the official PyTorch implementation of the research paper “Training Large Language Models to Reason in a Continuous Latent Space.” The framework introduces a novel method for enhancing large language models (LLMs) with continuous latent reasoning steps, enabling them to generate and refine reasoning chains within a learned latent space rather than relying solely on discrete symbolic reasoning. It supports training across multiple reasoning paradigms—including standard...
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  • 7
    SlowFast

    SlowFast

    Video understanding codebase from FAIR for reproducing video models

    SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without...
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  • 8
    Omnara

    Omnara

    Talk to Your AI Agents from Anywhere

    Omnara is an open-source agent control platform that empowers developers to turn autonomous AI tools (e.g., Claude Code, Cursor, GitHub Copilot) into collaborative teammates by offering real-time dashboards, push notifications, and remote guidance across terminals, web, and mobile. Omnara transforms your AI agents (Claude Code, Codex CLI, n8n, and more) from silent workers into communicative teammates. Get real-time visibility into what your agents are doing, and respond to their questions instantly from a single dashboard on web and mobile. ...
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  • 9
    Agno

    Agno

    Lightweight framework for building Agents with memory, knowledge, etc.

    Agno is a modular, open-source artificial general intelligence (AGI) research platform that allows developers to build, evaluate, and experiment with cognitive architectures in a composable way. It provides a flexible framework for modeling reasoning, memory, decision-making, and planning, aimed at long-term AI research beyond narrow learning. Agno embraces multi-agent environments and symbolic reasoning as part of its core design, enabling experiments with structured knowledge,...
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  • 10
    imgclsmob Deep learning networks

    imgclsmob Deep learning networks

    Sandbox for training deep learning networks

    imgclsmob is a deep learning research repository focused on implementing and experimenting with convolutional neural networks for computer vision tasks. The project serves as a sandbox for training and evaluating a wide variety of neural network architectures used in image analysis. It includes implementations of models used for tasks such as image classification, object detection, semantic segmentation, and pose estimation. The repository also contains scripts that help train models,...
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  • 11
    AgentHandover

    AgentHandover

    AgentHandover observes, learns and teaches agents with skills

    AgentHandover is a Mac-focused system that observes how a user works and converts repeated workflows into reusable, self-improving skills for AI agents. It is designed for tools such as Claude Code, OpenClaw, Codex, Hermes, Cursor, Windsurf, and other MCP-compatible environments. Instead of asking users to manually write long prompts or static automation instructions, it records real actions, infers decision logic, and produces skills that include steps, strategy, guardrails, selection criteria, and writing style. ...
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  • 12
    Khazix Skills

    Khazix Skills

    Digital Life Kazik Open Source AI Skills Collection

    ...By enforcing a consistent schema, the project ensures interoperability between skills and simplifies deployment across environments. This makes it especially useful for teams building modular AI agents that rely on external tools or open-source repositories.
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  • 13
    Fli

    Fli

    Google Flights MCP and Python Library

    ...The library supports a wide range of flight search capabilities, including filtering by airline, departure time, number of stops, cabin class, and sorting by price or duration, making it suitable for both casual queries and advanced travel analysis. In addition to its CLI interface, fli includes a Model Context Protocol (MCP) server that allows AI assistants to interact with flight data using structured tools, enabling natural language queries and automation workflows.
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  • 14
    MolmoWeb

    MolmoWeb

    Open multimodal web agent built by Ai2

    ...The system takes natural language instructions and translates them into sequences of browser actions such as clicking, typing, scrolling, and navigating, effectively performing tasks on behalf of the user. Unlike traditional automation tools that rely on structured HTML parsing or predefined APIs, MolmoWeb operates directly from screenshots of web pages, interpreting visual content in the same way a human user would. This approach allows it to generalize across different websites without requiring site-specific integrations, making it highly adaptable to diverse web environments.
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  • 15
    OpenSage

    OpenSage

    An agent framework that enables AI to create their own agent

    OpenSage is an emerging open-source AI agent development framework designed to automate the creation, orchestration, and evolution of intelligent agents through a self-programming paradigm. Unlike traditional agent frameworks that require developers to manually define workflows, tools, and structures, OpenSage introduces a system where large language models can dynamically generate their own agent architectures, including sub-agents, toolchains, and execution strategies. The framework is built around the concept of an Agent Development Kit (ADK), providing structured components for memory, reasoning, and task decomposition while allowing agents to iteratively improve their own design. ...
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  • 16
    OpenMemory

    OpenMemory

    Local long-term memory engine for AI apps with persistent storage

    ...It supports multiple embedding strategies, including synthetic and semantic embeddings, allowing developers to balance speed and accuracy depending on their use case. OpenMemory integrates with various AI tools and environments, offering SDKs and APIs that simplify adding memory capabilities to applications. OpenMemory also includes features like memory decay, reinforcement, and temporal filtering to ensure relevant information remains prioritized while outdated data gradually loses importance.
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  • 17
    LoLLMs WEBUI

    LoLLMs WEBUI

    Local AI WebUI for running and managing large language models offlineA

    ...It provides users with a centralized environment to interact with multiple AI models, making it suitable for experimentation, development, and personal use. lollms-webui emphasizes offline capability, allowing users to maintain privacy and control over their data while still accessing advanced AI features. It integrates model management tools that help users download, configure, and switch between different language models with ease. It is built to be user-friendly while still offering advanced customization options for power users who want deeper control over model behavior. Additionally, it supports extensibility through plugins or modular components, enabling users to expand functionality as needed. ...
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  • 18
    Conversational Health Agents (CHA)

    Conversational Health Agents (CHA)

    A Personalized LLM-powered Agent Frameworks

    CHA, or Conversational Health Agents, is an open-source framework designed to build intelligent healthcare assistants powered by large language models and external data sources. The system enables developers to create personalized AI agents that can interact with users through natural language while performing multi-step reasoning and task execution. It integrates orchestration capabilities that allow the agent to gather information from APIs, knowledge bases, and external services in order...
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  • 19
    ShortGPT

    ShortGPT

    AI framework for automated short video creation and editing tools

    ShortGPT is an experimental AI-powered framework designed to automate the creation of short-form and long-form video content. It provides a structured system that handles multiple stages of the content creation workflow, including script generation, asset sourcing, voiceover synthesis, and video editing. ShortGPT uses large language models to generate scripts and prompts that guide the automated editing and production process. ShortGPT includes specialized content engines that manage...
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  • 20
    TimeMixer

    TimeMixer

    Decomposable Multiscale Mixing for Time Series Forecasting

    TimeMixer is a deep learning framework designed for advanced time series forecasting and analysis using a multiscale neural architecture. The model focuses on decomposing time series data into multiple temporal scales in order to capture both short-term seasonal patterns and long-term trends. Instead of relying on traditional recurrent or transformer-based architectures, TimeMixer is implemented as a fully multilayer perceptron–based model that performs temporal mixing across different...
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  • 21
    FISSURE

    FISSURE

    The RF and reverse engineering framework for everyone

    FISSURE is an open-source radio frequency analysis and signal intelligence framework built to support software-defined radio research, wireless security experimentation, and protocol reverse engineering. The project brings together tools for capturing, inspecting, decoding, replaying, and analyzing RF signals across a wide range of wireless technologies. It is designed as a practical environment for researchers and operators who need to move from raw spectrum observation to structured investigation without stitching together too many separate utilities by hand. The platform supports workflows related to signal discovery, demodulation, packet inspection, fuzzing, and attack simulation, making it useful for both defensive research and controlled lab testing. ...
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  • 22
    Diffusion for World Modeling

    Diffusion for World Modeling

    Learning agent trained in a diffusion world model

    Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within...
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  • 23
    TensorFlow Quantum

    TensorFlow Quantum

    Open-source Python framework for hybrid quantum-classical ml learning

    TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages...
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  • 24
    C3

    C3

    The goal of CLAIMED is to enable low-code/no-code rapid prototyping

    ...The system emphasizes reproducibility and scalability, allowing researchers and engineers to reuse existing components and integrate them into larger scientific or data engineering workflows. It also aims to support trusted and explainable AI systems by integrating tools for fairness analysis, explainability, and adversarial robustness.
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  • 25
    face.evoLVe

    face.evoLVe

    High-Performance Face Recognition Library on PaddlePaddle & PyTorch

    face.evoLVe is a high-performance face recognition library designed for research and real-world applications in computer vision. The project provides a comprehensive framework for building and training modern face recognition models using deep learning architectures. It includes components for face alignment, landmark localization, data preprocessing, and model training pipelines that allow developers to construct end-to-end facial recognition systems. The repository supports multiple neural...
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