Search Results for "python-gtksourceview2" - Page 78
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Showing 16624 open source projects for "python-gtksourceview2"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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BCC (BPF Compiler Collection)
Tools for BPF-based Linux IO analysis, networking, monitoring, etc.
BCC is a toolkit that simplifies creating efficient kernel tracing, monitoring, and manipulation programs by leveraging extended Berkeley Packet Filters (eBPF). It includes a rich set of example tools and scripting interfaces in C, Python, and Lua. BCC makes BPF programs easier to write, with kernel instrumentation in C (and includes a C wrapper around LLVM), and front-ends in Python and lua. It is suited for many tasks, including performance analysis and network traffic control. With a BPF-specific frontend, one should be able to write in a language and receive feedback from the compiler on the validity as it pertains to a BPF backend. ... -
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AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models,... -
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Instructor
Structured outputs for llms
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of... -
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nb-clean
Clean Jupyter notebooks of outputs, metadata, and empty cells
...It provides both a Git filter and pre-commit hook to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library. It can determine if a notebook is clean or not, which can be used as a check in your continuous integration pipelines. nb-clean can also be used as a pre-commit hook. You may prefer this to the Git filter if your project already uses the pre-commit framework. Note that the Git filter and pre-commit hook work differently, with different effects on your working directory. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Airtest
UI Automation Framework for Games and Apps
...It allows writing instructions in Python, to achieve more advanced automation. -
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YData Synthetic
Synthetic data generators for tabular and time-series data
...This repository contains material related to Generative Adversarial Networks for synthetic data generation, in particular regular tabular data and time-series. It consists a set of different GANs architectures developed using Tensorflow 2.0. Several example Jupyter Notebooks and Python scripts are included, to show how to use the different architectures. YData synthetic has now a UI interface to guide you through the steps and inputs to generate structure tabular data. The streamlit app is available form v1.0.0 onwards. -
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Mangum
AWS Lambda support for ASGI applications
Mangum is an adapter for running ASGI applications in AWS Lambda to handle Function URL, API Gateway, ALB, and Lambda@Edge events. Event handlers for API Gateway HTTP and REST APIs, Application Load Balancer, Function URLs, and CloudFront Lambda@Edge. Compatibility with ASGI application frameworks, such as Starlette, FastAPI, Quart and Django. Support for binary media types and payload compression in API Gateway using GZip or Brotli. Works with existing deployment and configuration tools,... -
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dynaconf
Configuration Management for Python
Inspired by the 12-factor application guide. Settings management (default values, validation, parsing, templating). Protection of sensitive information (passwords/tokens). Multiple file formats toml|yaml|json|ini|py and also customizable loaders. Full support for environment variables to override existing settings (dotenv support included). Optional layered system for multi environments [default, development, testing, production] (also called multi profiles). Built-in support for Hashicorp... -
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OpenVINO Training Extensions
Trainable models and NN optimization tools
OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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tf2onnx
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. -
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis. TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions. Since TFP inherits the benefits of TensorFlow, you can build, fit, and deploy a model using a single language throughout the lifecycle of model exploration and production. ... -
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Amazon Braket PennyLane Plugin
A plugin for allowing Xanadu PennyLane to use Amazon Braket devices
The Amazon Braket PennyLane plugin offers two Amazon Braket quantum devices to work with PennyLane. The Amazon Braket Python SDK is an open-source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. PennyLane is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations. Once the Pennylane-Braket plugin is installed, the provided Braket devices can be accessed straight away in PennyLane, without the need to import any additional packages. ... -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. This project includes many examples of Jupyter notebooks. ... -
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
...The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models in Keras, MXNet, PyTorch, Tensorflow, CoreML, DarkNet and more. Start using TVM with Python today, build out production stacks using C++, Rust, or Java the next day. -
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Cookiecutter Django
Framework for jumpstarting production-ready Django projects quickly
Powered by Cookiecutter, Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly. Cookiecutter Django works with Python 3.9 and renders Django projects with 100% starting test coverage. It has 12-Factor based settings via django-environment. Secure by default, beacuse we believe in SSL. Optimized development and production settings. Registration is handled via django-allauth. It comes with custom user model ready to go. Provides an optional basic ASGI setup for Websockets and an optional custom static build using Gulp and livereload. ... -
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GPTCache
Semantic cache for LLMs. Fully integrated with LangChain
ChatGPT and various large language models (LLMs) boast incredible versatility, enabling the development of a wide range of applications. However, as your application grows in popularity and encounters higher traffic levels, the expenses related to LLM API calls can become substantial. Additionally, LLM services might exhibit slow response times, especially when dealing with a significant number of requests. To tackle this challenge, we have created GPTCache, a project dedicated to building a... -
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handson-ml3
Fundamentals of Machine Learning and Deep Learning
handson-ml3 contains the Jupyter notebooks and code for the third edition of the book Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow. It guides readers through modern machine learning and deep learning workflows using Python, with examples spanning data preparation, supervised and unsupervised learning, deep neural networks, RL, and production-ready model deployment. The third edition updates the content for TensorFlow 2 and Keras, introduces new chapters (for example on reinforcement learning or generative models), and offers best-practice code that reflects current ecosystems. ... -
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Flexprice
Usage-based pricing and billing for developers
Flexprice is an open-source dynamic pricing engine designed to help online businesses and marketplaces automate and optimize their pricing strategies. It allows developers and data scientists to experiment with pricing algorithms using real-time market data, inventory levels, and historical sales to maximize revenue, conversion, or competitiveness. Built with flexibility in mind, Flexprice can be integrated into existing e-commerce infrastructure via APIs and supports simulation and A/B... -
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CTranslate2
Fast inference engine for Transformer models
CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many advanced optimizations: layer fusion, padding removal, batch reordering, in-place operations, caching mechanism, etc. ... -
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tldr-pages
Collaborative cheatsheets for console commands
The tldr-pages project is a collection of community-maintained help pages for command-line tools, that aims to be a simpler, more approachable complement to traditional man pages. The tldr pages are a community effort to simplify the beloved man pages with practical examples. Maybe you are new to the command-line world? Or just a little rusty? Or perhaps you can't always remember the arguments to lsof, or tar? There seems to be room for simpler help pages, focused on practical examples. This... -
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mise
Dev tools, env vars, task runner
Mise (formerly RTX) is a cross-language CLI tool and task runner that manages developer tools, environment variables, and project tasks in a unified configuration (mise.toml). It handles tool installation (e.g., Node, Python, Terraform), env var profiles, and repeatable command scripting. -
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QSV
Blazing-fast Data-Wrangling toolkit
qsv is a fast, command-line CSV data toolkit written in Rust that extends the capabilities of xsv. It’s designed to make working with CSV files at scale easy and efficient, offering over 40 powerful subcommands for tasks like querying, sampling, splitting, deduplicating, and more. qsv is ideal for data engineers, analysts, and developers who need high-performance CSV manipulation on the command line. -
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geo-seo-claude
GEO-first SEO skill for Claude Code
geo-seo-claude is an AI-powered tool designed to automate the creation of geographically optimized SEO content using large language models, helping businesses improve their visibility in local search results. It leverages AI to generate location-specific content tailored to different regions, allowing users to scale SEO efforts across multiple cities or markets without manual content creation. The system focuses on producing structured and keyword-optimized pages that align with search... -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
Basic Memory is an open source knowledge system that turns AI conversations into persistent, structured knowledge you control. Instead of losing context after each chat, it stores information as simple Markdown files on your device, allowing both you and AI to read and write to the same knowledge base. It uses the Model Context Protocol (MCP) so compatible AI tools can access, update, and build on your notes across sessions. Basic Memory creates a semantic knowledge graph by linking related... -
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FAY
Framework for building AI-powered interactive digital humans and agent
Fay is an open source framework designed to build and deploy interactive digital humans powered by large language models. It acts as a middleware layer that connects digital character technologies with conversational AI systems and business applications. Fay supports various types of digital humans, including 2.5D and 3D avatars, and can be integrated with applications running on mobile devices, PCs, web platforms, and embedded systems. Its architecture allows developers to combine different...
