Search Results for "find" - Page 2
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Showing 487 open source projects for "find"
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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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SeaGOAT
local-first semantic code search engine
...Instead of relying solely on traditional keyword search, it uses vector embeddings to represent the meaning of code and queries, allowing users to perform semantic searches that find relevant code even when the exact keywords are not present. The tool runs locally on a developer’s machine and processes repositories using a combination of embedding models and conventional search utilities, enabling both semantic and text-based retrieval methods. By combining vector search with tools like ripgrep, SeaGOAT provides a hybrid approach that supports both natural language queries and precise keyword matching in source files. ... -
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SAM 3
Code for running inference and finetuning with SAM 3 model
SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an... -
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hosts
Consolidate and extend hosts files from several well-curated sources
...The combined products are stored in the alternates folder. Data for extensions are stored in the extensions folder. You manage extensions by curating this folder tree, where you will find the data for fakenews, social, gambling, and porn extension data that we maintain and provide for you. Create an optional blacklist file. The contents of this file (containing a listing of additional domains in hosts file format) are appended to the unified hosts file during the update process. A sample blacklist is included, and may be modified as you need. -
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Nafas
Breathing Gymnastics Application
Breathing gymnastics is a system of breathing exercises that focuses on the treatment of various diseases and general health promotion. Nafas is a collection of breathing gymnastics designed to reduce the exhaustion of long working hours. With multiple breathing patterns, Nafas helps you find your way to a detoxified energetic workday and also improves your concentration by increasing the oxygen level. No need to walk away to take a break, just sit comfortably, run Nafas and let the journey begin. Nafas means breath in Persian. -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. -
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Cozette
A bitmap programming font optimized for coziness
...That prompted me to make the bitmap font I always wished existed: Cozette; a small-but-not-tiny bitmap font with great coverage of all the glyphs you might encounter in the terminal. I'm intentionally putting the emphasis on "you" - although Cozette already has all the glyphs I've seen in my CLI tools so far, you might find it's missing a glyph you wish it had. If that's the case, please file an issue! It's an important goal for Cozette to be a useful bitmap alternative to Nerd Fonts. Bitmap fonts are, effectively, just that - bitmaps. -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
...It is recommended to explore them. All of the commands and features supported by graph notebook are explained in detail with examples within the sample notebooks. You can find them here. As this project has evolved, many new features have been added. If you are already familiar with graph-notebook but want a quick summary of new features added, a good place to start is the Air-Routes notebooks in the 02-Visualization folder. -
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Goose Developer Agent
Goose is a developer agent that operates from your command line
...Goose can interact with a multitude of tools via external APIs such as Jira, GitHub, Slack, infrastructure and data pipelines, and more -- if your task uses a shell command or can be carried out by a Python script, Goose can do it for you too! Like semi-autonomous driving, Goose handles the heavy lifting, allowing you to focus on other priorities. Simply set it on a task and return later to find it completed, boosting your productivity with less manual effort. -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via... -
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NetworkX
Network analysis in Python
...Open source 3-clause BSD license. Well tested with over 90% code coverage. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Find the shortest path between two nodes in an undirected graph. Python’s None object is not allowed to be used as a node. It determines whether optional function arguments have been assigned in many functions. And it can be used as a sentinel object meaning “not a node”. -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
...By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly discover reputable and well-maintained repositories. This way one can survey state-of-the-art projects, find learning resources, or pick stable libraries for production — without manually sifting through hundreds of repos. The repository is openly licensed under MIT, making it easy to fork, extend, or contribute updates (e.g. adding newer projects or reordering by recent popularity). -
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PandasAI
PandasAI is a Python library that integrates generative AI
...PandasAI makes pandas (and all the most used data analyst libraries) conversational, allowing you to ask questions to your data in natural language. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will return a DataFrame containing only those rows. -
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Awesome-Quant
A curated list of insanely awesome libraries, packages and resources
...It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards. -
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Masonite
The Modern And Developer Centric Python Web Framework
...Events you can listen for to execute listeners that perform your tasks when certain events happen in your app. A BEAUTIFUL Active Record style ORM called Masonite ORM. Amazingness at your fingertips. Many more features you need which you can find in the docs! -
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n8n Workflows
All of the workflows of n8n i could find (also from the site itself)
This repository aggregates a well-organized collection of community-submitted automation workflows built for n8n, a fair-code, self-hostable automation tool. It serves as an index for discovering ready-made flows to automate tasks across multiple services and platforms. 2,057 workflows with meaningful, searchable names. 365 unique integrations across popular platforms. 29,445 total nodes with professional categorization. Quality assurance - All workflows analyzed and categorized. -
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Conda
OS-agnostic, system-level binary package manager
...Conda easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a different version of Python, you do not need to switch to a different environment manager because conda is also an environment manager. With just a few commands, you can set up a totally separate environment to run that different version of Python, while continuing to run your usual version of Python in your normal environment. -
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HelloGitHub
Share interesting, entry-level open source projects on GitHub
...At first, I just wanted to collect interesting, high-quality, and easy-to-use projects that I found in the process of browsing GitHub, so that it would be easier to find and learn later. Later, I plan to share these interesting and valuable open source projects with you. I ended up writing this website for easy viewing and sharing. Open source projects in various languages, tools to make life better, books, study notes, tutorials, and more. Through these projects, you will learn more programming knowledge, improve your programming skills, and discover the joy of programming. -
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Patroni
A template for PostgreSQL high availability with Etcd, Consul, etc.
Patroni is a template for you to create your own customized, high-availability solution using Python and - for maximum accessibility - a distributed configuration store like ZooKeeper, etcd, Consul or Kubernetes. Database engineers, DBAs, DevOps engineers, and SREs who are looking to quickly deploy HA PostgreSQL in the datacenter-or anywhere else-will hopefully find it useful. We call Patroni a "template" because it is far from being a one-size-fits-all or plug-and-play replication system. It will have its own caveats. Use wisely. Currently supported PostgreSQL versions 9.3 to 14. Patroni originated as a fork of Governor, the project from Compose. It includes plenty of new features. For an example of a Docker-based deployment with Patroni, see Spilo, currently in use at Zalando. -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. -
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Cleanlab
The standard data-centric AI package for data quality and ML
...To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you find label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box. -
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Unofficial TikTok API in Python
The Unofficial TikTok API Wrapper In Python
...With this API you are able to call most trending and fetch specific user information as well as much more. If you run into an issue please check the closed issues on GitHub, although feel free to re-open a new issue if you find an issue that's been closed for a few months. The codebase can and does run into similar issues as it has before because TikTok changes things up. To run the example scripts from the repository root, make sure you use them an option on python. You can access the dictionary type of an object using .as_dict. On a video, this may look like this, although TikTok changes its structure from time to time so it's worth investigating the structure of the dictionary when you use this package. ... -
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BayesianOptimization
A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes. -
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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 algorithms. -
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Python LSP Server
Fork of the python-language-server project
Fork of the python-language-server project, maintained by the Spyder IDE team and the community. A Python 3.7+ implementation of the Language Server Protocol. The base language server requires Jedi to provide Completions, Definitions, Hover, References, Signature Help, and Symbols. Like all language servers, the configuration can be passed from the client that talks to this server (i.e. your editor/IDE or another tool that has the same purpose). The details of how this is done depend on the... -
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MTEB
MTEB: Massive Text Embedding Benchmark
...MTEB spans 8 embedding tasks covering a total of 58 datasets and 112 languages. Through the benchmarking of 33 models on MTEB, we establish the most comprehensive benchmark of text embeddings to date. We find that no particular text embedding method dominates across all tasks. This suggests that the field has yet to converge on a universal text embedding method and scale it up sufficiently to provide state-of-the-art results on all embedding tasks.
