Search Results for "modules" - Page 2
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Showing 230 open source projects for "modules"
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AI Agents Masterclass
Follow along with my AI Agents Masterclass videos
...It breaks down how autonomous agents interact with external systems, handle iterative reasoning, and integrate with third-party services or APIs to perform real tasks — for example, web search, browsing, scheduling, or coding assistance. Students of the masterclass can follow written modules or Jupyter notebooks that illustrate concepts step by step and progressively build more capable agents. The content is suitable for both beginners and intermediate developers because it starts with basic principles and escalates to advanced architectures like multi-agent coordination. -
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
...The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time. -
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xFormers
Hackable and optimized Transformers building blocks
xformers is a modular, performance-oriented library of transformer building blocks, designed to allow researchers and engineers to compose, experiment, and optimize transformer architectures more flexibly than monolithic frameworks. It abstracts components like attention layers, feedforward modules, normalization, and positional encoding, so you can mix and match or swap optimized kernels easily. One of its key goals is efficient attention: it supports dense, sparse, low-rank, and approximate attention mechanisms (e.g. FlashAttention, Linformer, Performer) via interchangeable modules. The library includes memory-efficient operator implementations in both Python and optimized C++/CUDA, ensuring that performance isn’t sacrificed for modularity. ... -
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DreamCraft3D
Official implementation of DreamCraft3D
...The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. It may integrate rendering or post-processing modules (e.g. mesh smoothing, texturing) to make the outputs more output-ready. Because 3D generation is hardware‐intensive, the repository likely also includes optimizations like quantization, pruning, or inference accelerations (e.g. using FlashMLA or DeepEP) to make the generation pipeline faster or more efficient. DreamCraft3D may also support style or attribute control (e.g. ... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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Kheish
Kheish: A multi-role LLM agent for tasks like code auditing
Kheish is a framework designed for cybersecurity professionals to automate penetration testing tasks, providing tools to streamline security assessments. -
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GraphRAG
A modular graph-based Retrieval-Augmented Generation (RAG) system
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs. -
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Mlxtend
A library of extension and helper modules for Python's data analysis
Mlxtend (machine learning extensions) is a Python library of useful tools for day-to-day data science tasks. -
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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. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses: BinaryFocalLoss, Focal, ReducedFocal, Lovasz, Jaccard and Dice losses, Wing Loss and more. ... -
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HunyuanVideo
HunyuanVideo: A Systematic Framework For Large Video Generation Model
HunyuanVideo is a cutting-edge framework designed for large-scale video generation, leveraging advanced AI techniques to synthesize videos from various inputs. It is implemented in PyTorch, providing pre-trained model weights and inference code for efficient deployment. The framework aims to push the boundaries of video generation quality, incorporating multiple innovative approaches to improve the realism and coherence of the generated content. Release of FP8 model weights to reduce GPU... -
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Discord4J
Reactive library to enable quick and easy development of bots
...Automatic rate-limiting, automatic reconnection strategies, and consistent naming conventions are among the many features Discord4J offers to ensure your Discord bots run-up to Discord's specifications and to provide the least amount of surprises when interacting with our library. Discord4J breaks itself into modules to allow advanced users to interact with our API at lower levels to build minimal and fast runtimes or even add their own abstractions. Discord4J can be used to develop any bot, big or small. We offer many tools for developing large-scale bots from custom distribution frameworks, off-heap caching, and its interaction with Reactor allows complete integration. -
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Atmosphere
Real-time transport layer for Java AI agents
...It lets developers declare agent behavior with an @Agent annotation while the framework handles transport, streaming, tool calls, memory, reconnect behavior, authorization, and observability. A single agent can be exposed over WebSocket, Server-Sent Events, long polling, gRPC, and WebTransport over HTTP/3 depending on the modules included. It also supports agent-facing protocols such as MCP, A2A, and AG-UI, along with external messaging channels such as Slack, Telegram, Discord, WhatsApp, and Messenger. The project is built for teams that need AI agents to behave like production services instead of simple chat demos. It is useful for JVM developers who want portable, observable, real-time AI agent endpoints across multiple clients and protocols. -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external... -
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OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
OpenClaw-Medical-Skills is an open-source library that provides a large collection of specialized medical capabilities designed for the OpenClaw AI agent ecosystem. The project organizes domain-specific “skills” that enable autonomous agents to perform tasks related to biomedical research, healthcare analysis, and clinical data interpretation. Each skill is packaged as a modular component that can be integrated into an OpenClaw-based AI assistant, allowing the agent to perform expert-level... -
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MemoryOS
MemoryOS is designed to provide a memory operating system
MemoryOS is an open-source framework designed to provide a structured memory management system for AI agents and large language model applications. The project addresses one of the major limitations of modern language models: their inability to maintain long-term context beyond the limits of their prompt window. MemoryOS introduces a hierarchical memory architecture inspired by operating system memory management principles, allowing agents to store, update, retrieve, and generate information... -
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Letta Code
The memory-first coding agent
Letta Code is a memory-first CLI coding agent built on the Letta platform that offers developers a persistent AI assistant capable of learning and improving over time rather than resetting state each session, giving agents a sense of continuity and context across coding tasks. Unlike traditional session-based coding tools, Letta Code attaches a long-lived agent to a working directory so that the agent accumulates memory about a project’s structure, preferences, and history, effectively... -
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Office Agents
Agent plugins for Microsoft Office but BYOK for any model and provider
...It supports a bring-your-own-key model, allowing users to connect to a wide range of AI providers, including OpenAI, Anthropic, and other compatible APIs. The framework also includes advanced capabilities such as a sandboxed execution environment, virtual file systems, and extensible skill modules that expand agent functionality. -
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Fara-7B
An Efficient Agentic Model for Computer Use
...Rather than relying on ad-hoc or manual review processes, FARA enables organizations to profile AI behavior using standardized tests, metrics, and reporting templates, making evaluations reproducible and comparable over time. The framework supports plugin-based modules that can be tailored to industry-specific concerns or regulatory requirements, helping compliance teams, auditors, and engineers collaborate on shared assessment goals. -
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VIPER
AI-powered red team platform for adversary simulation toolkit
...Viper emphasizes ease of use through a graphical interface, allowing users to manage complex operations without relying solely on command-line tools. It includes a large collection of built-in modules that cover multiple stages of the MITRE ATT&CK framework, enabling realistic and structured attack simulations. Viper also incorporates automation features and workflow orchestration, helping teams streamline repetitive tasks and maintain continuous monitoring of target environments. A notable aspect of the project is its integration of a large language model agent, which assists with decision-making, parameter handling, and analysis during operations. -
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DeepTutor
AI-Powered Personalized Learning Assistant
...It goes beyond simple Q&A by constructing multi-stage educational narratives, breaking down complex topics into sequenced “lesson steps,” and offering prompts, examples, and exercises that build on each other in a logical curriculum. The core architecture combines LLM-based reasoning with structured pedagogy modules so that explanations accommodate different learning styles and address misconceptions in follow-up responses. DeepTutor supports retrieval of external references, definitions, and diagrams so responses are grounded in authoritative content and not just generative text, and it includes internal checks to ensure accuracy and conceptual consistency. -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
...MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. The repository includes tools and kernels to support the new sparse architecture—for instance, CUDA kernels, logit indexers, and open-source modules like FlashMLA and DeepGEMM are invoked for performance. -
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Zero to Mastery Machine Learning
All course materials for the Zero to Mastery Machine Learning
Zero to Mastery Machine Learning is an open-source repository that contains the complete course materials for the Zero to Mastery Machine Learning and Data Science bootcamp. The project provides a structured curriculum designed to teach machine learning and data science using Python through hands-on projects and interactive notebooks. The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from... -
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ViMax
Director, Screenwriter, Producer, and Video Generator All-in-One
ViMax is an open-source framework for performing large-scale multi-modal vision-language modeling and reasoning by combining powerful image encoders with advanced language models to solve complex visual tasks. It integrates components like visual encoders, cross-modal fusion techniques, and reasoning modules so that users can go beyond simple captioning or classification to perform tasks such as visual question answering, multi-image inference, and structured scene understanding. ViMax’s design accommodates large image sets and supports retrieval augmentation, enabling it to work with external image databases, supplementary metadata, and semantic search to enhance context awareness. ... -
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
...Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate into the JIT runtime seamlessly. After compilation using the optimized graph should feel no different than running a TorchScript module. You also have access to TensorRT’s suite of configurations at compile time, so you are able to specify operating precision (FP32/FP16/INT8) and other settings for your module. -
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JimuReport
Open source drag-and-drop reporting and dashboard builder platform
...It can connect to multiple data sources and retrieve data through SQL queries, APIs, or other structured formats. It can be embedded into Java applications using Spring Boot integration modules. -
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Antigravity Kit
AI Agent templates with Skills, Agents, and Workflows
Antigravity Kit is an AI agent capability expansion toolkit that provides structured templates, skills, and workflows designed to boost the productivity of AI assistants and autonomous agents in coding environments. It comes with an extensive library of predefined agent personas and domain-specific skills that help in performing targeted tasks such as frontend development, backend engineering, quality assurance, and more. With this kit, developers can rapidly initialize a project scaffold...
