Search Results for "mac framework" - Page 4
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Showing 1369 open source projects for "mac framework"
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference... -
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Hephaestus
Semi-Structured Agentic Framework. Workflows build themselves
Hephaestus is an open-source semi-structured agentic framework designed to orchestrate multiple AI agents working together on complex tasks. Instead of relying entirely on predefined workflows, the framework allows agents to dynamically create tasks as they explore a problem space. Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression,... -
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Django-CRM
Open Source CRM based on Django
Django CRM is opensource CRM developed on django framework. It has all the basic features of CRM to start with. We welcome code contributions and feature requests via github. Create and activate a virtual environment. Install the project's dependency after activating env. -
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Seldon Core
An MLOps framework to package, deploy, monitor and manage models
The de facto standard open-source platform for rapidly deploying machine learning models on Kubernetes. Seldon Core, our open-source framework, makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. Seldon Core serves models built in any open-source or commercial model building framework. You can make use of powerful Kubernetes features like custom resource definitions to manage model graphs. And then connect your continuous integration and... -
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QwenPaw
A personal AI assistant, easy to install
QwenPaw is an AI agent framework developed by the AgentScope ecosystem to provide a desktop-style intelligent assistant powered by Qwen language models and modular agent orchestration. The project combines conversational AI, memory systems, tool usage, workflow automation, and multimodal interaction into a unified assistant environment designed for daily productivity and experimentation. It supports structured reasoning, autonomous task execution, and integration with external tools and... -
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TypeAgent Python
Structured RAG: ingest, index, query
TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language... -
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BrowserGym
A Gym environment for web task automation
BrowserGym is an open framework for web task automation research that exposes browser interaction as a Gym-style environment for training and evaluating agents. It is intended for researchers building web agents rather than for end users looking for a consumer automation product. The project provides a common environment where agents can interact with websites, execute tasks, and be evaluated against standardized benchmarks. One of its main strengths is that it bundles several important... -
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AG2
Framework for building and orchestrating multi-agent AI systems
AG2 is an open source framework designed to support the creation and coordination of multiple AI agents working together to solve complex tasks. It provides abstractions that allow developers to define agents with distinct roles, responsibilities, and communication patterns, enabling collaborative problem-solving workflows. AG2 focuses on making multi-agent systems more accessible by simplifying how agents are configured, connected, and executed. It includes mechanisms for agent-to-agent... -
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web.py
Web framework for python that is as simple as it is powerful
web.py is a web framework for Python that is as simple as it is powerful. web.py is in the public domain, you can use it for whatever purpose with absolutely no restrictions. web.py was originally published while Aaron Swartz worked at reddit.com, where the site used it as it grew to become one of the top 1000 sites according to Alexa and served millions of daily page views. “It’s the anti-framework framework. web.py doesn’t get in your way,” explained founder Steve Huffman. (The site was... -
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Cog
Package and deploy machine learning models using Docker containers
Cog is an open source tool designed to package machine learning models into standardized, production-ready containers. It simplifies the process of deploying models by automatically generating Docker images based on a simple configuration file, eliminating the need to manually write complex Dockerfiles. Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best... -
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RAG Anything
RAG-Anything: All-in-One RAG Framework
RAG-Anything is an open-source unified framework that extends the Retrieval-Augmented Generation (RAG) paradigm to fully multimodal document and knowledge retrieval, enabling systems to ingest, parse, represent, and query rich content that includes text, images, tables, formulas, and other structured or visual elements. Traditional RAG systems are typically limited to text and cannot effectively work across heterogeneous document layouts, but RAG-Anything addresses this by modeling... -
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NVIDIA NeMo Agent Toolkit
Library for efficiently connecting and optimizing teams of AI agents
NVIDIA NeMo Agent Toolkit is an open-source framework designed to build, optimize, and manage AI agents across different development ecosystems. It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze... -
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Pixeltable
Data Infrastructure providing an approach to multimodal AI workloads
Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a... -
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caveman
Why use many token when few token do trick
Caveman is a lightweight and experimental project focused on simplifying backend or full-stack development workflows through minimalistic abstractions and rapid prototyping principles. It is designed to reduce the complexity of modern frameworks by offering a stripped-down approach that prioritizes speed, clarity, and ease of use. The project often serves as a foundation for developers who want to build applications quickly without being constrained by heavy conventions or extensive... -
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SGLang
SGLang is a fast serving framework for large language models
SGLang is a fast serving framework for large language models and vision language models. It makes your interaction with models faster and more controllable by co-designing the backend runtime and frontend language. -
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Mobly
E2E test framework for tests with complex environment requirements
Mobly is a Python-based test framework that specializes in supporting test cases that require multiple devices, complex environments, or custom hardware setups. P2P data transfer between two devices. Conference calls across three phones. Wearable device interacting with a phone. Internet-Of-Things devices interacting with each other. Testing RF characteristics of devices with special equipment. Testing LTE network by controlling phones, base stations, and eNBs. Mobly can support many... -
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Halo
Framework built by White Circle for training large language
Halo is an open-source training framework for large language and multimodal models, designed to scale from a single GPU to multi-node clusters. It supports pretraining, supervised fine-tuning, preference optimization, distillation, and fully asynchronous multi-turn reinforcement learning. The framework trains Hugging Face models directly, so checkpoints remain compatible with standard from_pretrained workflows. Distributed execution supports expert, context, tensor, and expert-tensor... -
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FuzzyAI Fuzzer
A powerful tool for automated LLM fuzzing
FuzzyAI is an open-source fuzzing framework designed to test the security and reliability of large language model applications. The tool automates the process of generating adversarial prompts and input variations to identify vulnerabilities such as jailbreaks, prompt injections, or unsafe model responses. It allows developers and security researchers to systematically evaluate the robustness of LLM-based systems by simulating a wide range of malicious or unexpected inputs. The framework can... -
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Hunyuan3D-1
A Unified Framework for Text-to-3D and Image-to-3D Generation
Hunyuan3D-1 is an earlier version in the same 3D generation line (the unified framework for text-to-3D and image-to-3D tasks) by Tencent Hunyuan. It provides a framework combining shape generation and texture synthesis, enabling users to create 3D assets from images or text conditions. While less advanced than version 2.1, it laid the foundations for the later PBR, higher resolution, and open-source enhancements. (Note: less detailed public documentation was found for Hunyuan3D-1 compared to... -
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Make It heavy
A Python framework that emulates Grok Heavy functionality
Make It heavy is a Python framework for producing deeper AI analysis through multi-agent orchestration. It is designed to emulate the style of Grok Heavy by splitting a user query into several specialized research angles. The system runs four agents in parallel so each one can explore the problem from a different perspective. It then combines their outputs into one unified answer through an intelligent synthesis step. The framework uses OpenRouter for model access and can also run in... -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence.... -
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TNT
A lightweight library for PyTorch training tools and utilities
TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps... -
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CrewAI
Framework for orchestrating role-playing, autonomous AI agents
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI... -
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Responder
A familiar HTTP Service Framework for Python
Responder is a web service framework, written for human beings. This gets you a ASGI app, with a production static files server (WhiteNoise) pre-installed, jinja2 templating (without additional imports), and a production web server based on uvloop, serving up requests with gzip compression automatically. A pleasant API, with a single import statement. Class-based views without inheritance. ASGI framework, the future of Python web services. WebSocket support! The ability to mount any ASGI /... -
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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. “planner,” “searcher,” “coder,” “report generator”)...
