Showing 1907 open source projects for "open"

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    Cloud tools for web scraping and data extraction

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  • 1
    openbench

    openbench

    Provider-agnostic, open-source evaluation infrastructure

    openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves.
    Downloads: 0 This Week
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  • 2
    PokeeResearch-7B

    PokeeResearch-7B

    Pokee Deep Research Model Open Source Repo

    PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response.
    Downloads: 0 This Week
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  • 3
    Surya

    Surya

    Implementation of the Surya Foundation Model for Heliophysics

    Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture, thereby enabling improved space weather forecasting. ...
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  • 4
    Appfl

    Appfl

    Advanced Privacy-Preserving Federated Learning framework

    APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups.
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  • BoldTrail Real Estate CRM Icon
    BoldTrail Real Estate CRM

    A first-of-its-kind homeownership solution that puts YOU at the center of the coveted lifetime consumer relationship.

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  • 5
    Agent Squad

    Agent Squad

    Flexible and powerful framework for managing multiple AI agents

    Agent-Squad is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries and maintains context across interactions, offering pre-built components for quick deployment and easy integration of custom agents.
    Downloads: 0 This Week
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  • 6
    MCP Bridge

    MCP Bridge

    A middleware to provide an openAI compatible endpoint

    MCP-Bridge serves as a middleware that connects the OpenAI API with MCP tools, allowing developers to utilize MCP functionalities through the OpenAI API interface. It provides endpoints compatible with OpenAI, facilitating seamless integration and enabling the use of MCP tools without requiring explicit MCP support in clients. ​
    Downloads: 0 This Week
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  • 7
    Xiyan MCP Server

    Xiyan MCP Server

    A Model Context Protocol (MCP) server

    The XiYan MCP Server is a Model Context Protocol (MCP) server that enables natural language queries to databases, powered by XiYan-SQL, a state-of-the-art text-to-SQL model. It allows users to interact with databases using conversational language, simplifying data retrieval processes. ​
    Downloads: 0 This Week
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  • 8
    Legion MCP

    Legion MCP

    A server that helps people access and query data in databases

    The Legion MCP Server is designed to help users access and query data in databases using the Legion Query Runner, integrated with the Model Context Protocol (MCP) Python SDK. It facilitates efficient data retrieval and analysis through standardized interfaces. ​
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  • 9
    MCP Server Qdrant

    MCP Server Qdrant

    An official Qdrant Model Context Protocol (MCP) server implementation

    The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. ​
    Downloads: 0 This Week
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  • Zendesk: The Complete Customer Service Solution Icon
    Zendesk: The Complete Customer Service Solution

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  • 10
    Browser Use MCP Server

    Browser Use MCP Server

    Browse the web, directly from Cursor etc.

    A browser automation server implementing the Model Context Protocol, designed to allow AI assistants to browse the web directly from applications like Cursor. It supports natural language commands for web navigation and interaction. ​
    Downloads: 0 This Week
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  • 11
    TalkingHeads

    TalkingHeads

    A library to communicate with ChatGPT, Claude, Copilot, Gemini

    TalkingHeads is a Python library designed to facilitate communication with various AI chat agents, including ChatGPT, Claude, Copilot, Gemini, HuggingChat, and Pi. It provides a unified interface for interacting with these platforms, simplifying the integration of conversational AI capabilities into applications. TalkingHeads supports browser automation and offers tools to manage sessions, handle prompts, and process responses effectively.
    Downloads: 0 This Week
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  • 12
    Tianji

    Tianji

    Evaluation suite designed to assess the performance of LLMs

    Tianji is a comprehensive evaluation suite designed to assess the performance of large language models (LLMs) across multiple dimensions. It focuses on measuring general capabilities such as reasoning, knowledge, commonsense, and language understanding. Tianji provides a curated set of benchmarks and a unified framework for systematically comparing LLMs, making it useful for research and model selection.
    Downloads: 0 This Week
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  • 13
    PettingZoo

    PettingZoo

    An API standard for multi-agent reinforcement learning environments

    PettingZoo is a standardized API and library for multi-agent reinforcement learning (MARL) environments. It provides a broad set of environments and tools to facilitate the development and evaluation of multi-agent algorithms.
    Downloads: 0 This Week
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  • 14
    DeepSparse

    DeepSparse

    Sparsity-aware deep learning inference runtime for CPUs

    A sparsity-aware enterprise inferencing system for AI models on CPUs. Maximize your CPU infrastructure with DeepSparse to run performant computer vision (CV), natural language processing (NLP), and large language models (LLMs).
    Downloads: 0 This Week
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  • 15
    openTSNE

    openTSNE

    Extensible, parallel implementations of t-SNE

    openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets. openTSNE incorporates the latest improvements to the t-SNE algorithm, including the ability to add new data points to existing embeddings [2], massive speed improvements [3] [4] [5], enabling t-SNE to scale to millions of data points, and various tricks to improve the global alignment of the resulting...
    Downloads: 0 This Week
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  • 16
    Advanced Solutions Lab

    Advanced Solutions Lab

    This repos contains notebooks for the Advanced Solutions Lab

    This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level.
    Downloads: 0 This Week
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  • 17
    Autodistill

    Autodistill

    Images to inference with no labeling

    Autodistill uses big, slower foundation models to train small, faster supervised models. Using autodistill, you can go from unlabeled images to inference on a custom model running at the edge with no human intervention in between. You can use Autodistill on your own hardware, or use the Roboflow hosted version of Autodistill to label images in the cloud.
    Downloads: 0 This Week
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  • 18
    fugue

    fugue

    A unified interface for distributed computing

    Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites.
    Downloads: 0 This Week
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  • 19
    Alibi Explain

    Alibi Explain

    Algorithms for explaining machine learning models

    Alibi is a Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models.
    Downloads: 0 This Week
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  • 20
    KerasTuner

    KerasTuner

    A Hyperparameter Tuning Library for Keras

    KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search...
    Downloads: 0 This Week
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  • 21
    TensorFlow Datasets

    TensorFlow Datasets

    TFDS is a collection of datasets ready to use with TensorFlow,

    TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets.
    Downloads: 0 This Week
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  • 22
    AudioLM - Pytorch

    AudioLM - Pytorch

    Implementation of AudioLM audio generation model in Pytorch

    Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it...
    Downloads: 0 This Week
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  • 23
    DreamO

    DreamO

    A Unified Framework for Image Customization

    DreamO is a unified, open-source framework from ByteDance for advanced image customization and generation that consolidates multiple “image manipulation” tasks into a single system, rather than requiring separate specialized models. Built on a diffusion-transformer (DiT) backbone, it supports a diverse set of tasks — including identity preservation, virtual “try-on” (e.g. clothing, accessories), style transfer, IP adaptation (objects/characters), and layout/condition-aware customizations — all handled within the same unified architecture. ...
    Downloads: 0 This Week
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  • 24
    Matrix

    Matrix

    Multi-Agent daTa geneRation Infra and eXperimentation framework

    ...That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. It supports both open-source LLMs and proprietary models (via integration with model backends), and works with containerized or sandboxed environments for safe tool execution or external code runs.
    Downloads: 0 This Week
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  • 25
    Bailing

    Bailing

    Bailing is a voice dialogue robot similar to GPT-4o

    Bailing is an open-source voice-dialogue assistant designed to deliver natural voice-based conversations by combining automatic speech recognition (ASR), voice activity detection (VAD), a large language model (LLM), and text-to-speech (TTS) in a single pipeline. Its goal is to offer a “voice-first” chat experience similar to what one might expect from a system like GPT-4o, but fully open and deployable by users.
    Downloads: 0 This Week
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