Search Results for "python code" - Page 17
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Showing 2491 open source projects for "python code"
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Build experiences that drive engagement and increase transactionsSendbird's chat, voice, and video APIs power conversations and communities in hundreds of the most innovative apps and products. Sendbird’s feature-rich platform, and pre-fab UI components make developers more productive. We take care of a ton of operational complexity under the hood, so you can power a rich chat service, and life-like voice, and video experiences, and not worry about features, edge cases, reliability, or scale.
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Django Lifecycle Hooks
Declarative model lifecycle hooks, an alternative to Signals
This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django's built-in approach to offering lifecycle hooks is Signals. However, my team often finds that Signals introduce unnecessary indirection and are at odds with Django's "fat models" approach. Django Lifecycle Hooks supports Python 3.7, 3.8 and 3.9, Django 2.0.x, 2.1.x, 2.2.x, 3.0.x, 3.1.x, and 3.2.x. For simple cases, you might always want something to happen at a... -
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RenderCV
LaTeX CV generator from a YAML/JSON input file
RenderCV is a LaTeX CV/resume framework. It allows you to create a high-quality CV as a PDF from a YAML file with full Markdown syntax support and complete control over the LaTeX code. RenderCV offers built-in LaTeX and Markdown templates ready to produce high-quality CVs. However, the templates are entirely arbitrary and can easily be updated to leverage RenderCV's capabilities with your custom CV themes. -
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AgenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills
AgenticSeek is a fully local autonomous AI assistant designed as a privacy-focused alternative to cloud-based agent platforms. It runs entirely on the user’s hardware and can autonomously browse the web, write code, and plan multi-step tasks without sending data to external services. The system is optimized for local reasoning models and emphasizes zero cloud dependency to maintain full user control. AgenticSeek includes intelligent agent selection, allowing it to determine the best internal... -
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SeedVR2 Upscaler ComfyUI
Official SeedVR2 Video Upscaler for ComfyUI
ComfyUI-SeedVR2 Video Upscaler is an open-source integration node for the ComfyUI workflow environment that brings the advanced SeedVR2 video upscaling and restoration model directly into visual AI pipelines. This project packages the SeedVR2 architecture as a custom node for ComfyUI, letting users upscale low-resolution video or imagery inside a node-based interface without needing to write code manually. The underlying SeedVR2 model is known for delivering high-quality video enhancement... -
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python-for-android
Turn your Python application into an Android APK
python-for-android is an open source build tool to let you package Python code into standalone android APKs. These can be passed around, installed, or uploaded to marketplaces such as the Play Store just like any other Android app. This tool was originally developed for the Kivy cross-platform graphical framework, but now supports multiple bootstraps and can be easily extended to package other types of Python apps for Android. python-for-android supports two major operations; first, it can compile the Python interpreter, its dependencies, backend libraries and python code for Android devices. ... -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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omegaml
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud. -
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
OWL (Optimized Workforce Learning) is a sophisticated open-source framework built on the CAMEL-AI ecosystem for orchestrating teams of AI agents to collaboratively solve complex, real-world tasks with dynamic planning and automation capabilities. Unlike single-agent systems, it treats task completion as a collaborative workforce where agents take on specialized roles (planning, execution, analysis) and coordinate via a modular multi-agent architecture that supports flexible teamwork across... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
Connecteam Employee Management SoftwareConnecteam is an award-winning all-in-one employee management solution for daily operations, communications, and human resource management.
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Qwen3
Qwen3 is the large language model series developed by Qwen team
Qwen3 is a cutting-edge large language model (LLM) series developed by the Qwen team at Alibaba Cloud. The latest updated version, Qwen3-235B-A22B-Instruct-2507, features significant improvements in instruction-following, reasoning, knowledge coverage, and long-context understanding up to 256K tokens. It delivers higher quality and more helpful text generation across multiple languages and domains, including mathematics, coding, science, and tool usage. Various quantized versions,... -
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BioEmu
Inference code for scalable emulation of protein equilibrium ensembles
Biomolecular Emulator (BioEmu for short) is a model that samples from the approximated equilibrium distribution of structures for a protein monomer, given its amino acid sequence. By default, unphysical structures (steric clashes or chain discontinuities) will be filtered out, so you will typically get fewer samples in the output than requested. The difference can be very large if your protein has large disordered regions, which are very likely to produce clashes. BioEmu outputs structures... -
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Google Research: Language
Shared repository for open-sourced projects from the Google AI Lang
Google Research: Language is a shared repository maintained by Google Research that contains open-source projects developed by the Google AI Language team. The repository hosts multiple subprojects related to natural language processing, machine learning, and large-scale language understanding systems. Many of the projects included in the repository correspond to research papers released by Google researchers and provide implementations of new NLP algorithms or experimental frameworks. These... -
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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. It includes implementations for a wide range of AI topics... -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),... -
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Thinc
A refreshing functional take on deep learning
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,... -
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Freqtrade
Free, open source crypto trading bot
...We strongly recommend you have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. -
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SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image... -
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Writer Framework
No-code in the front, Python in the back. An open-source framework
Writer Framework is an open source platform designed to help developers build AI-powered applications by combining a visual interface builder with a Python-based backend architecture. It follows a hybrid approach where user interfaces are created using a drag-and-drop editor while business logic is implemented in Python, allowing teams to balance speed and flexibility without sacrificing control. The framework is particularly focused on AI use cases, enabling developers to integrate large... -
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System Design Primer
Learn how to design large-scale systems
System Design Primer is a curated, open source collection of resources that helps engineers learn how to design large-scale systems. The project is structured as a comprehensive guide covering core system design concepts, trade-offs, and patterns necessary for building scalable, reliable, and maintainable systems. It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview... -
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Schemathesis
Guarantee flawless API functionality with test scenarios
Guarantee flawless API functionality with thorough, high-quality test scenarios generated from your API specification. Schemathesis is a specification-centric API testing tool for Open API and GraphQL-based applications. It reads the application schema and generates test cases, which will ensure that your application is compliant with its schema and never crashes. The application under test could be written in any language; the only thing you need is a valid API schema in a supported format.... -
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Django Rules
Awesome Django authorization, without the database
rules is a tiny but powerful app providing object-level permissions to Django, without requiring a database. At its core, it is a generic framework for building rule-based systems, similar to decision trees. It can also be used as a standalone library in other contexts and frameworks. Versatile. Decorate callables to build complex graphs of predicates. Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions,... -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ... -
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Zeep
A Python SOAP client
A fast and modern Python SOAP client. Compatible with Python 3.7, 3.8, 3.9, 3.10, 3.11, and PyPy. Build on top of lxml and requests. Support for Soap 1.1, Soap 1.2 and HTTP bindings. Support for WS-Addressing headers. Support for WSSE (UserNameToken / x.509 signing) Support for asyncio via httpx. Experimental support for XOP messages. Zeep inspects the WSDL document and generates the corresponding code to use the services and types in the document. -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ... -
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Bracket
Selfhosted tournament system
Bracket is an open-source tool that tracks and manages data access across your PostgreSQL database. It provides visibility into which parts of your codebase are accessing which tables and columns, enabling data governance, security auditing, and architectural insights. Bracket is particularly helpful for growing teams needing better observability in complex applications.
