Showing 5016 open source projects for "can"

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  • $300 Free Credits to Build on Google Cloud Icon
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    MongoDB Atlas runs apps anywhere

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  • 1
    Hiring Agent

    Hiring Agent

    AI agent to evaluate and score resumes

    ...It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence, bonus points, and deductions. It can run locally with Ollama or use Google Gemini, which makes it flexible for teams that want either private local processing or hosted model access.
    Downloads: 0 This Week
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  • 2
    Meli-Action

    Meli-Action

    Download files from direct links, YouTube, Telegram, Google Play

    ...It uses GitHub-hosted workflow runners to fetch content from direct links, YouTube, Telegram, Google Play, SoundCloud, and web pages. Downloaded files are committed into the user’s repository so they can be retrieved later through normal GitHub access. The project includes workflows for different content sources, plus a Python script that can render and save web pages as MHTML archives using a headless browser. It also handles large direct-download files by splitting them into smaller chunks that fit repository limits. Its main value is offering a cloud-run, no-local-install workflow for saving files and pages when direct access is unreliable or blocked.
    Downloads: 0 This Week
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  • 3
    Super Magic

    Super Magic

    All-in-one AI productivity platform with agents, workflows, and IM

    ...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 correction. Alongside this, Magic includes a visual workflow engine that enables users to design complex AI processes using a drag-and-drop interface without requiring extensive coding knowledge. It also provides an enterprise-grade instant messaging system that integrates AI conversations with internal communication, allowing teams to collaborate while leveraging intelligent assistants. ...
    Downloads: 4 This Week
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  • 4
    RL with PyTorch

    RL with PyTorch

    Clean, Robust, and Unified PyTorch implementation

    ...It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL approaches. The repository is structured so that users can easily experiment with different algorithms and training environments. Many examples demonstrate how agents learn to interact with simulated environments through trial and error using reinforcement learning principles. The codebase emphasizes clarity and modular design so that researchers can extend the implementations or use them for experimentation and benchmarking.
    Downloads: 0 This Week
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    Ship Agents Faster

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  • 5
    machine_learning_examples

    machine_learning_examples

    A collection of machine learning examples and tutorials

    ...The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. Many of the examples are accompanied by tutorials and educational materials that explain how the algorithms work and how they can be applied in real-world projects. The code is organized into small independent experiments so that learners can explore specific algorithms or techniques without needing to understand the entire codebase.
    Downloads: 0 This Week
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  • 6
    VGGSfM

    VGGSfM

    VGGSfM: Visual Geometry Grounded Deep Structure From Motion

    ...Version 2.0 adds support for dynamic scene handling, dense point cloud export, video-based reconstruction (1000+ frames), and integration with Gaussian Splatting pipelines. It leverages tools like PyCOLMAP, poselib, LightGlue, and PyTorch3D for feature matching, pose estimation, and visualization. With minimal configuration, users can process single scenes or full video sequences, apply motion masks to exclude moving objects, and train neural radiance or splatting models directly from reconstructed outputs.
    Downloads: 4 This Week
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  • 7
    Qwen3 Embedding

    Qwen3 Embedding

    Designed for text embedding and ranking tasks

    Qwen3-Embedding is a model series from the Qwen family designed specifically for text embedding and ranking tasks. It builds upon the Qwen3 base/dense models and offers several sizes (0.6B, 4B, 8B parameters), for both embedding and reranking, with high multilingual capability, long‐context understanding, and reasoning. It achieves state-of-the-art performance on benchmarks like MTEB (Multilingual Text Embedding Benchmark) and supports instruction-aware embedding (i.e. embedding task...
    Downloads: 4 This Week
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  • 8
    FastHTML

    FastHTML

    The fastest way to create an HTML app

    Built on solid web foundations, not the latest fads - with FastHTML you can get started on anything from simple dashboards to scalable web applications in minutes.
    Downloads: 1 This Week
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  • 9
    ipychart

    ipychart

    The power of Chart.js with Python

    ...The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. All the types of charts present in Chart.js are exposed in ipychart. Even complex features such as mixed-types charts are available. Charts are highly customizable and all Chart.js options are available in ipychart. ...
    Downloads: 0 This Week
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  • 10
    GitSavvy

    GitSavvy

    Full git and GitHub integration with Sublime Text

    ...Also, GitSavvy takes advantage of modern features of Sublime Text (like annotations). For the best experience, use the latest Sublime Text dev build. The documentation is probably outdated. Yeah it's sad but you can contribute and I will eventually get onto it but every special view has help available, just press ?. GitSavvy requires Git versions at or greater than 2.18.0. basic Git functionality; init, add, commit, amend, checkout, pull, push, etc. Rebasing just from that "Repo History". Edit a commit, reword a commit, autosquash commits, apply a fixup, whatever... the [r] menu. git diff view, allowing user to stage, unstage and reset (discard) files, hunks or individual lines. ...
    Downloads: 4 This Week
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  • 11
    AutoKeras

    AutoKeras

    AutoML library for deep learning

    ...The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. 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.
    Downloads: 0 This Week
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  • 12
    UltiSnips

    UltiSnips

    Snippet solution for Vim

    ...You should first expand the #! snippet, then the class snippet. The completion menu comes from YouCompleteMe, UltiSnips also integrates with deoplete, and more. You can jump through placeholders and add text while the snippet inserts text in other places automatically: when you add Animal as a base class, __init__ gets updated to call the base class constructor. When you add arguments to the constructor, they automatically get assigned to instance variables. You can then insert your personal snippet for print debugging.
    Downloads: 0 This Week
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  • 13
    Outlines

    Outlines

    Structured Outputs

    Outlines is a Python library for making language models generate predictable, structured outputs. Instead of repairing malformed responses afterward, it constrains generation to match a requested type or format. Developers can require predefined choices, primitive Python types, Pydantic models, JSON schemas, regular expressions, function signatures, or custom grammars. The same interface works with local models, inference servers, and hosted APIs from several providers. Supported integrations include Transformers, llama.cpp, vLLM, Ollama, OpenAI, and Gemini. ...
    Downloads: 2 This Week
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  • 14
    python-whatsapp-bot

    python-whatsapp-bot

    Build AI WhatsApp Bots with Pure Python

    ...The project provides a practical implementation of a messaging automation system using the Flask web framework to handle webhook events and process incoming messages in real time. Developers can configure the bot to receive user messages through the WhatsApp API, route them through application logic, and generate automated responses powered by AI services such as large language models. The repository includes example scripts and project structures that illustrate how to integrate OpenAI or similar AI models into the bot workflow, enabling conversational agents capable of answering questions or performing automated tasks.
    Downloads: 10 This Week
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  • 15
    nbdev

    nbdev

    Create delightful software with Jupyter Notebooks

    nbdev is a notebook-driven development platform (by fast.ai/AnswerDotAI) enabling you to write code, tests, documentation, and deploy software, all from Jupyter Notebooks. It provides a unified literate programming workflow where you can tag notebook cells for export to Python modules, auto-generate documentation via Quarto (and host it on GitHub Pages), run tests embedded in notebooks, manage clean notebooks with Git-friendly metadata hooks, and seamlessly publish packages to PyPI/conda, all while keeping source and documentation in sync.
    Downloads: 2 This Week
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  • 16
    Pretty Jupyter

    Pretty Jupyter

    Creates dynamic html report from jupyter notebook.

    Pretty Jupyter is an easy-to-use package that allows to create beautiful & dynamic HTML reports. Most of the features require little to no work to get working and greatly improve the quality of the output report, or even the developer’s comfort when creating the report. For example, tabs make some visualizations much more comfortable. The features are integrated directly into the output page, therefore there is no need to have an interpreter running in the backend. This makes the HTML easily...
    Downloads: 2 This Week
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  • 17
    MetricFlow

    MetricFlow

    MetricFlow allows you to define, build, and maintain metrics in code

    ...Because metric definitions live centrally, you avoid duplication across teams and tools, reduce risk of inconsistent numbers, and make it easier to audit and evolve the logic over time. The project emphasizes explainability, performance and portability: you define metrics once and then they can be consumed in BI tools, notebooks, or even AI/agent-driven workflows.
    Downloads: 4 This Week
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  • 18
    Misago

    Misago

    Misago is fully featured modern forum application

    ...Site admins may require users to confirm validity of their e-mail addresses via e-mail sent activation link, or limit user account activation to administrator action. They can use custom Q&A challenge, ReCAPTCHA, Stop Forum Spam or IP's blacklist to combat spam registrations. Pletora of settings are available to control user account behavior, like username lengths or avatar restrictions. Presence features let site members know when other users are online, offline or banned. Individual users have setting to hide their activity from non-admins.
    Downloads: 4 This Week
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  • 19
    Pacu

    Pacu

    The AWS exploitation framework, designed for testing security

    ...Automating components of the assessment not only improves efficiency but also allows our assessment team to be much more thorough in large environments. What used to take days to manually enumerate can be now be achieved in minutes. There are currently over 35 modules that range from reconnaissance, persistence, privilege escalation, enumeration, data exfiltration, log manipulation, and miscellaneous general exploitation.
    Downloads: 4 This Week
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  • 20
    GitDiagram

    GitDiagram

    AI tool that converts GitHub repositories into interactive diagrams

    ...These diagrams provide a high-level overview of a codebase, making it easier for developers to explore unfamiliar projects or understand large and complex repositories. Users can interact with the generated diagrams by clicking components to navigate directly to related files or directories within the repository. GitDiagram combines a modern web frontend with a backend service that processes repository data and generates diagrams dynamically.
    Downloads: 3 This Week
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  • 21
    Kaggle Solutions

    Kaggle Solutions

    Collection of Kaggle Solutions and Ideas

    ...The repository also highlights important machine learning concepts such as feature engineering, cross-validation strategies, ensemble modeling, and post-processing methods commonly used in winning solutions. Because the content is organized by competition categories such as computer vision, natural language processing, tabular data, and time-series forecasting, users can explore techniques relevant to specific problem types.
    Downloads: 3 This Week
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  • 22
    Made With ML

    Made With ML

    Learn how to develop, deploy and iterate on production-grade ML

    Made-With-ML is an open-source educational repository and course designed to teach developers how to build production-grade machine learning systems using modern MLOps practices. The project focuses on bridging the gap between experimental machine learning notebooks and real-world software systems that can be deployed, monitored, and maintained at scale. It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets, train models, evaluate performance, and deploy inference services. The repository organizes these concepts into modular Python scripts that follow software engineering best practices such as testing, configuration management, logging, and version control. ...
    Downloads: 3 This Week
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  • 23
    Agentic Context Engine

    Agentic Context Engine

    Make your agents learn from experience

    ...The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and curation, enabling agents to refine strategies across repeated tasks. In this workflow, one component generates solutions, another reflects on outcomes, and a third curates useful knowledge so it can be reused in future interactions. This architecture allows agents to gradually build persistent operational memory without requiring additional training datasets or model retraining.
    Downloads: 3 This Week
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  • 24
    OSS-Fuzz

    OSS-Fuzz

    OSS-Fuzz - continuous fuzzing for open source software

    OSS-Fuzz is a large-scale fuzz testing platform developed by Google to improve the security and reliability of widely used open source software. Fuzz testing is a proven method for uncovering programming errors such as buffer overflows and memory leaks, which can lead to severe security vulnerabilities. By leveraging guided in-process fuzzing, Google has already identified thousands of issues in projects like Chrome, and this initiative extends the same capabilities to the broader open source community. OSS-Fuzz integrates modern fuzzing engines with sanitizers and runs them at scale in a distributed environment, providing automated testing and continuous monitoring. ...
    Downloads: 3 This Week
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  • 25
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    ...The repo supports multiple encodings (e.g. “cl100k_base”) and lets users switch encoding names to match different model contexts. It also offers extension mechanisms so that custom encodings can be registered. Internally, it includes the core tokenizer logic (often implemented in Rust or efficient lower-level code), APIs for encoding, decoding, and counting tokens, and binding layers to Python (and sometimes other languages) for easy use.
    Downloads: 3 This Week
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