Search Results for "frameworks" - Page 66
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Showing 8064 open source projects for "frameworks"
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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Tiled
Flexible level editor
Tiled is a free and open source, easy to use, and flexible level editor. Tiled is highly flexible. It can be used to create maps of any size, with no restrictions on tile size, or the number of layers or tiles that can be used. Maps, layers, tiles, and objects can all be assigned arbitrary properties. Tiled's map format (TMX) is easy to understand and allows multiple tilesets to be used in any map. Tilesets can be modified at any time. Tiled is a general purpose tile map editor for all... -
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redis-py
Redis Python client
...It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
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DoctrineExtensions
Doctrine2 behavioral extensions, Translatable, Sluggable, etc
...It provides additional features such as timestamping, versioning, and nested set support, making it a valuable tool for applications that require advanced data management. The extensions integrate seamlessly with Symfony and other PHP frameworks that use Doctrine. -
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Pickr
Flat, simple, multi-themed, responsive Color-Picker library
Flat, simple, multi-themed, responsive, and hackable Color-Picker library. No dependencies, no jQuery. Compatible with all CSS Frameworks e.g. Bootstrap, Materialize. Supports alpha channel, rgba, hsla, hsva and more. -
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ZeroBot-Plugin
OneBot plugin based on ZeroBot
ZeroBot-Plugin is a Go-based plugin collection for the ZeroBot ecosystem and OneBot-compatible bot frameworks. It packages many bot capabilities into a ready-to-run project that can be used through release binaries, direct local execution, or custom compilation. The repository is aimed mainly at QQ and OneBot-style chatbot deployments, with plugins that can be enabled, modified, or extended by developers. It is designed for users who want a richer bot feature set without writing every plugin from scratch. ... -
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agents-cli
CLI to turn coding assistants into expert at deploying AI agents
agents-cli is a command-line tool developed to simplify the creation, management, and execution of AI agents directly from the terminal. It provides developers with a structured interface for defining agent behavior, configuring tools, and running workflows. The tool integrates with agent frameworks and supports modular extensions for adding new capabilities. It emphasizes productivity by enabling rapid iteration and testing of agent logic without complex setup. agents-cli is designed to fit into modern developer workflows, particularly those that rely on automation and scripting. It allows users to orchestrate tasks, manage configurations, and monitor execution in a streamlined environment. ... -
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Tree
tree is a library for working with nested data structures
Tree (dm-tree) is a lightweight Python library developed by Google DeepMind for manipulating nested data structures (also called pytrees). It generalizes Python’s built-in map function to operate over arbitrarily nested collections — including lists, tuples, dicts, and custom container types — while preserving their structure. This makes it particularly useful in machine learning pipelines and JAX-based workflows, where complex parameter trees or hierarchical state representations are... -
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Logbook
An extensible Java library for HTTP request and response logging
Logbook is an extensible Java library to enable complete request and response logging for different client- and server-side technologies. It satisfies a special need by a) allowing web application developers to log any HTTP traffic that an application receives or sends b) in a way that makes it easy to persist and analyze it later. This can be useful for traditional log analysis, meeting audit requirements or investigating individual historic traffic issues. Logbook is ready to use out of... -
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Smart Money Concepts
Discover our Python package designed for algorithmic trading
...These indicators are inspired by ICT trading principles and are used to identify trends, reversals, and potential entry or exit points in financial markets. The system is modular, allowing users to combine different indicators and integrate them into backtesting frameworks or live trading bots. It is particularly useful for traders working in forex, crypto, or equities who rely on price action rather than traditional indicators. -
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Zero to Mastery Machine Learning
All course materials for the Zero to Mastery Machine Learning
...The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from problem definition to model deployment. The course introduces essential tools such as NumPy, pandas, Matplotlib, and scikit-learn before moving on to deep learning with frameworks like TensorFlow and Keras. It also includes milestone projects that demonstrate how to build end-to-end machine learning systems using real datasets, including classification and regression tasks. -
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PHP: The Right Way
An easy-to-read, quick reference for PHP best practices
...It covers essential topics such as coding style, dependency management, error handling, security, and testing, emphasizing modern PHP features and ecosystem tools. The project encourages developers to adopt frameworks, libraries, and patterns that align with current community conventions. Regular updates ensure that the content reflects the evolving state of the PHP language and industry standards, making it one of the most trusted educational references for PHP developers. -
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Swift
The Swift Programming Language
Swift is a high-performance, general-purpose programming language built with a modern approach to safety, performance, and software design patterns. With a clean and modern syntax, it offers seamless access to existing C and Objective-C code and frameworks. Swift makes it easy to write software that is incredibly fast and safe by design. It comes packaged with core features like flow control, data structures and functions, with high-level constructs like objects, protocols, closures, and generics. Its many features make it a language that is powerful, yet fun to use. It’s no wonder that Swift has quickly become one of the fastest growing languages in history. -
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MCP Toolbox for Databases
Open source MCP server that exposes database tools for AI agents
...By defining tools and data sources through configuration files, developers can standardize how AI systems access and operate on database resources. GenAI Toolbox is designed to integrate with agent frameworks and development environments so that AI assistants can execute database-related tasks with proper context and security. It also supports observability through built-in metrics and tracing capabilities, allowing developers to monitor how tools are used and debug interactions. -
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E2B Cookbook
Examples of using E2B
...E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. The cookbook organizes examples across multiple frameworks and model providers, allowing developers to experiment with integrations involving models from OpenAI, Anthropic, and other ecosystems. -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. ... -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
...The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques. Rather than relying on high-level machine learning frameworks, the codebase uses mostly low-level array and matrix manipulation APIs so that developers can understand exactly how model inference works internally. The project demonstrates how to load and run models such as Qwen-style architectures while progressively implementing performance improvements like KV caching, request batching, and optimized attention mechanisms. ... -
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Awesome LLM Apps
Collection of awesome LLM apps with AI Agents and RAG using OpenAI
Awesome LLM Apps is a community-curated directory of interesting, practical, and innovative applications built on or around large language models, serving as a discovery hub for developers, researchers, and enthusiasts. The list spans a wide range of categories including productivity tools, creative assistants, utilities, education platforms, research frameworks, and niche vertical apps, showcasing how generative models are being used across domains. Each entry includes a brief description, language model dependencies, technology stack notes, and sometimes links to demos or source code, making it easy to explore ideas and reuse concepts for your own projects. Because the landscape of LLM-powered applications changes quickly, the repository is designed to be updated regularly through community contributions, ensuring it stays current with new tools and releases. -
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OpenFL
Open source library for creative expression on the web, desktop, etc.
OpenFL is a free and open-source, cross-platform software framework that empowers developers to create rich interactive applications and games using a single codebase that can run on web browsers, mobile devices, desktops, and even some consoles. It builds on the Haxe programming language and offers a familiar display list and event-driven API inspired by classic Adobe Flash and AIR, allowing developers to leverage well-known paradigms while targeting modern platforms. OpenFL supports 2D and... -
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Universal Commerce Protocol (UCP)
The common language for platforms, agents and businesses.
Universal Commerce Protocol (UCP) is an open standard designed to unify how platforms, businesses, and payment providers interact across the modern commerce ecosystem. It provides a common language that eliminates fragmented, custom integrations and enables seamless interoperability between diverse commerce systems. Built for an increasingly agentic web, UCP supports AI-driven platforms that can discover products, manage carts, and complete transactions securely on a user’s behalf. Its... -
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rLLM
Democratizing Reinforcement Learning for LLMs
rLLM is an open-source framework for building and training post-training language agents via reinforcement learning — that is, using reinforcement signals to fine-tune or adapt language models (LLMs) into customizable agents for real-world tasks. With rLLM, developers can define custom “agents” and “environments,” and then train those agents via reinforcement learning workflows, possibly surpassing what vanilla fine-tuning or supervised learning might provide. The project is designed to... -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
...Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. 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. ... -
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Positron
Positron, a next-generation data science IDE
...Built on the open-source Code-OSS foundation, Positron provides a familiar coding experience along with specialized panes and tooling for variable inspection, data-frame viewing, plotting previews, and interactive consoles designed for analytical work. The IDE supports notebook and script workflows, integration of data-app frameworks (such as Shiny, Streamlit, Dash), database and cloud connections, and built-in AI-assisted capabilities to help write code, explore data, and build models. -
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GenAI Agents
Implementations for various Generative AI Agent techniques
...It spans a spectrum from simple conversational bots and basic question-answering agents to complex multi-agent systems that coordinate on research, education, business workflows, and creative tasks. The implementations leverage modern frameworks such as LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, and more, showing how each can be wired into realistic agent workflows. The repo is structured by categories like beginner agents, framework tutorials, educational agents, business agents, creative agents, analysis agents, news bots, shopping assistants, task management agents, QA bots, and advanced systems such as controllable RAG agents. ... -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
EasyR1 is a streamlined training framework for building “R1-style” reasoning models from open-source LLMs with minimal boilerplate. It focuses on the full reasoning stack—data preparation, supervised fine-tuning, preference or outcome-based optimization, and lightweight evaluation—so you can iterate quickly on chain-of-thought–heavy tasks. The project’s philosophy is practicality: sensible defaults, one-command recipes, and compatibility with popular base models let you stand up experiments...