Search Results for "python-gtksourceview2" - Page 86

Showing 19323 open source projects for "python-gtksourceview2"

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  • 1
    Koila

    Koila

    Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code

    Koila is a lightweight Python library designed to help developers avoid memory errors when training deep learning models with PyTorch. The library introduces a lazy evaluation mechanism that delays computation until it is actually required, allowing the framework to better estimate the memory requirements of a model before execution. By building a computational graph first and executing operations only when necessary, koila reduces the risk of running out of GPU memory during the forward pass of neural network training. ...
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  • 2
    douyin

    douyin

    Open source Douyin crawler for collecting and downloading public data

    DouyinCrawler is an open source data collection tool designed to gather publicly available information from the Douyin platform. It demonstrates how to build a Python-based web crawler combined with a graphical interface and command line functionality. It allows users to collect data from various types of Douyin content, including user profiles, videos, hashtags, and music pages. DouyinCrawler supports both automated scraping and batch operations to process multiple targets efficiently. It also integrates with the Aria2 download utility to enable large-scale downloading of videos and images associated with collected content. ...
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  • 3
    diskover-community

    diskover-community

    Open source file indexing & storage analytics powered by Elasticsearch

    ...By indexing file metadata from sources such as local file systems, network shares like NFS and SMB, and cloud storage, the tool provides a centralized way to analyze heterogeneous storage environments. Diskover also helps identify outdated or unused files, duplicate data, and inefficient storage usage that can waste resources or increase operational costs. A Python-based indexing engine performs the scanning and indexing tasks.
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  • 4
    kg-gen

    kg-gen

    Knowledge Graph Generation from Any Text

    kg-gen is an open-source framework developed by the STAIR Lab that automatically generates knowledge graphs from unstructured text using large language models. The system is designed to transform plain text sources such as documents, articles, or conversation transcripts into structured graphs composed of entities and relationships. Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing...
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  • 5
    E2B Cookbook

    E2B Cookbook

    Examples of using E2B

    E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code...
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  • 6
    Jenkins-Zero-To-Hero

    Jenkins-Zero-To-Hero

    Install Jenkins and configure Docker

    ...From there, it covers installing plugins like Docker Pipeline, configuring Docker as an agent, and wiring up multi-stage and multi-agent pipelines. The folder structure includes practical examples such as java-maven-sonar-argocd-helm-k8s and python-jenkins-argocd-k8s, showing real CI/CD flows that build, test, analyze, containerize, and deploy apps to Kubernetes via Argo CD in a GitOps style. The README walks through detailed step-by-step commands and screenshots, making it accessible to beginners who are unfamiliar with Jenkins, AWS, or pipelines.
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  • 7
    Agentex

    Agentex

    Open source codebase for Scale Agentex

    AgentEX is an open framework from Scale for building, running, and evaluating agentic workflows, with an emphasis on reproducibility and measurable outcomes rather than ad-hoc demos. It treats an “agent” as a composition of a policy (the LLM), tools, memory, and an execution runtime so you can test the whole loop, not just prompting. The repo focuses on structured experiments: standardized tasks, canonical tool interfaces, and logs that make it possible to compare models, prompts, and tool...
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  • 8
    Standard Webhooks

    Standard Webhooks

    The Standard Webhooks specification

    ...The project defines strict guidelines covering aspects like signature formats, headers, timestamps, replay protection, and forward compatibility. It includes reference implementations for signature verification and signing across multiple languages such as Python, JavaScript/TypeScript, Go, Rust, Ruby, PHP, C#, Java, and Elixir, along with additional community SDKs. The initiative is guided by a technical steering committee with members from companies like Zapier, Twilio, Mux, ngrok, Supabase, Svix, and Kong. Standard Webhooks matters because it eliminates the fragmentation of webhook implementations, reducing consumer effort and enabling seamless verification in apps or even directly in API gateways. ...
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  • 9
    Flama

    Flama

    Fire up your models with the flame

    Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs.
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  • 10
    Griptape

    Griptape

    Python framework for AI workflows and pipelines with chain of thought

    The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. The framework allows developers to transition...
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  • 11
    TurboGears

    TurboGears

    Python web framework with full-stack layer

    TurboGears is a hybrid web framework able to act both as a Full Stack framework or as a Microframework. TurboGears helps you get going fast and gets out of your way when you want it! TurboGears can be used both as a full stack framework or as a microframework in single-file mode. TurboGears 2 is built on top of the experience of several next-generation web frameworks including TurboGears 1 (of course), Django, and Rails. All of these frameworks had limitations that frustrated us, and TG2 was...
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  • 12
    Anymail

    Anymail

    Django email backends and webhooks for Amazon SES, Mailgun, Mailjet

    ...Anymail maintains compatibility with all Django versions that are in mainstream or extended support, plus (usually) a few older Django versions, and is extensively tested on all Python versions supported by Django.
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  • 13
    Healthchecks

    Healthchecks

    A cron monitoring tool written in Python & Django

    We notify you when your nightly backups, weekly reports, cron jobs, and scheduled tasks don't run on time. Healthchecks is a cron job monitoring service. It listens for HTTP requests and email messages ("pings") from your cron jobs and scheduled tasks ("checks"). When a ping does not arrive on time, Healthchecks sends out alerts. Healthchecks comes with a web dashboard, API, 25+ integrations for delivering notifications, monthly email reports, WebAuthn 2FA support, and team management...
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  • 14
    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases.
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  • 15
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images.
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  • 16
    PySyft

    PySyft

    Data science on data without acquiring a copy

    Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data...
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  • 17
    Klavis AI

    Klavis AI

    MCP integration platforms for AI agents to use tools at any scale

    ...The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher accuracy and 83%+ success on complex workflows. Developers can integrate via Python/TypeScript SDKs or REST API, with support for OpenAI, Claude, Gemini, LangChain, LlamaIndex, and CrewAI. Features include built-in authentication, multi-tenancy, hosted servers, Docker support, and enterprise security guardrails. Licensed under Apache 2.0, Klavis simplifies AI development by eliminating complex authentication management and enabling seamless workflow automation across multiple applications.
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  • 18
    InvokeAI

    InvokeAI

    InvokeAI is a leading creative engine for Stable Diffusion models

    InvokeAI is an implementation of Stable Diffusion, the open source text-to-image and image-to-image generator. It provides a streamlined process with various new features and options to aid the image generation process. It runs on Windows, Mac and Linux machines, and runs on GPU cards with as little as 4 GB or RAM. InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies....
    Downloads: 4 This Week
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  • 19
    DeepMatch

    DeepMatch

    A deep matching model library for recommendations & advertising

    DeepMatch is an open-source deep matching library built for recommendation and advertising systems. It helps developers train models that learn vector representations for users and items. These representations can be exported and used in approximate nearest neighbor search for large-scale retrieval. The library supports familiar Keras workflows through model.fit() and model.predict(). Its model collection includes FM, DSSM, YouTubeDNN, NCF, SDM, MIND, and ComiRec. It is designed to make...
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  • 20
    Copy Fail - CVE-2026-31431

    Copy Fail - CVE-2026-31431

    epository that demonstrates and analyzes a Linux kernel vulnerability

    Copy Fail - CVE-2026-31431 is a proof-of-concept repository that demonstrates and analyzes a specific Linux kernel vulnerability identified as CVE-2026-31431. The project provides experimental scripts and documentation to reproduce and study the exploit in controlled environments. It is designed for security researchers and engineers who want to understand the mechanics of the vulnerability. The repository includes tested configurations across multiple Linux distributions and kernel...
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  • 21
    TurboQuant PyTorch

    TurboQuant PyTorch

    From-scratch PyTorch implementation of Google's TurboQuant

    TurboQuant PyTorch is a specialized deep learning optimization framework designed to accelerate neural network inference and training through advanced quantization techniques within the PyTorch ecosystem. The project focuses on reducing the computational and memory footprint of models by converting floating-point representations into lower-precision formats while preserving performance. It provides tools for experimenting with different quantization strategies, enabling developers to balance...
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  • 22
    PyTorch Image Models

    PyTorch Image Models

    The largest collection of PyTorch image encoders / backbones

    timm (PyTorch Image Models) is a premier library hosting a vast collection of state-of-the-art image classification models and backbones such as ResNet, EfficientNet, NFNet, Vision Transformer, ConvNeXt, and more. Created by Ross Wightman and now maintained by Hugging Face, it includes pretrained weights, data loaders, augmentations, optimizers, schedulers, and reference scripts for training, evaluation, inference, and model export. It's an essential toolkit for vision research and...
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  • 23
    Notte

    Notte

    Opensource browser using agents

    Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications.
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  • 24
    ContextGem

    ContextGem

    ContextGem: Effortless LLM extraction from documents

    ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval.​
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  • 25
    Bittensor

    Bittensor

    Internet-scale Neural Networks

    Bittensor is a decentralized machine learning protocol that allows AI models to collaborate, learn, and earn tokens within a global network. It introduces a blockchain-based economy for neural networks, where participants are incentivized to contribute valuable knowledge and compute power. Bittensor combines peer-to-peer learning with on-chain rewards, creating a self-governing, scalable AI system that evolves without centralized control. It is a novel approach to aligning incentives in AI...
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