Search Results for "frameworks" - Page 4
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Showing 1053 open source projects for "frameworks"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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PilottAI
Python framework for building scalable multi-agent systems
pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers. -
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BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely... -
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Katib
Automated Machine Learning on Kubernetes
Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is a project that is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom Resources with out-of-the-box support for Kubeflow Training Operator, Argo Workflows, Tekton Pipelines, and many more. -
Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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LangChain for Java
LangChain4j is an open-source Java library
...LangChain4j also implements common design patterns used in generative AI systems, such as retrieval-augmented generation pipelines, tool calling, and intelligent agent frameworks. These abstractions allow developers to orchestrate interactions between language models, external tools, and knowledge bases in a structured and scalable way. -
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AgentScope
Build and run agents you can see, understand and trust
...With built-in support for ReAct agents, memory, planning, human-in-the-loop control, and real-time voice interaction, developers can create powerful agents in minutes. AgentScope integrates seamlessly with tools, long-term memory systems, MCP, A2A (Agent-to-Agent) protocols, and observability frameworks. It also supports reinforcement learning workflows for tuning agents and improving performance across complex tasks. Deployable locally, serverless in the cloud, or on Kubernetes with OpenTelemetry support, AgentScope is built for both experimentation and production environments. -
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Agent Stack
Deploy and share agents with open infrastructure
...It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. The platform supports agents built in frameworks like LangChain, CrewAI, etc., enabling them to be hosted, managed and shared through a unified interface. It also offers multi-model, multi-provider support (OpenAI, Anthropic, Gemini, IBM WatsonX, Ollama etc.), letting users compare performance and cost across models. For developers and organizations building AI-agent products or automations, Agent Stack gives a scaffold that handles the “plumbing”, so they can focus on logic and domain. -
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Botonic
Build chatbots and conversational experiences using React
Botonic is a full-stack Javascript framework to create chatbots and modern conversational apps that work on multiple platforms, web, mobile and messaging apps (Messenger, Whatsapp, Telegram, etc). Building modern applications on top of messaging apps like Whatsapp or Messenger is much more than creating simple text-based chatbots. Botonic is a full-stack serverless framework that combines the power of React and Tensorflow.js to create amazing experiences at the intersection of text and... -
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VectorizedMultiAgentSimulator (VMAS)
VMAS is a vectorized differentiable simulator
VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Open Autonomy
A framework for the creation of autonomous agent services
Open Autonomy is a framework that enables the development of autonomous economic agents (AEAs) capable of operating independently in various economic contexts. -
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Agent S
Agent S: an open agentic framework that uses computers like a human
Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines... -
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AWS Neuron
Powering Amazon custom machine learning chips
...Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can continue to use the same ML frameworks you use today and migrate your software onto Inf1 instances with minimal code changes and without tie-in to vendor-specific solutions. Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization. -
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Bolna
Conversational voice AI agents
Bolna is an end-to-end open-source platform for building conversational voice AI agents, enabling developers to create voice-first conversational assistants efficiently. -
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FlashInfer
FlashInfer: Kernel Library for LLM Serving
FlashInfer is a kernel library designed to enhance the serving of Large Language Models (LLMs) by optimizing inference performance. It provides a high-performance framework that integrates seamlessly with existing systems, aiming to reduce latency and improve efficiency in LLM deployments. FlashInfer supports various hardware architectures and is built to scale with the demands of production environments. -
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Academic Research Skills for Claude Code
Academic Research Skills for Claude Code
Academic Research Skills is a structured learning repository aimed at improving users’ ability to conduct rigorous academic research, particularly in technical and scientific domains. It compiles methodologies, frameworks, and best practices for literature review, critical analysis, and research writing. The project is designed as a self-guided resource, helping learners understand how to evaluate sources, synthesize information, and develop strong arguments. It likely integrates examples, templates, and conceptual explanations to bridge the gap between theory and practical research execution. ... -
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TEN Framework
TEN, a voice agent framework to create conversational AI.
TEN (Transformative Extensions Network) is a voice agent framework for creating conversational AI applications, focusing on high performance and modularity. -
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Godot RL Agents
An Open Source package that allows video game creators
godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot. -
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SwarmZero
SwarmZero's SDK for building AI agents, swarms of agents and much more
SwarmZero is an open-source platform designed for deploying and managing autonomous robot swarms. It enables collective coordination, decentralized decision-making, and real-time collaboration among large groups of autonomous agents, focusing on multi-robot systems and research in swarm robotics. -
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uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
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Petastorm
Petastorm library enables single machine or distributed training
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular Python-based machine learning (ML) frameworks such as Tensorflow, PyTorch, and PySpark. ... -
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Grounded Docs
Open-Source Alternative to Context7, Nia, and Ref.Tools
...The architecture follows the MCP specification, which allows AI assistants and agent frameworks to connect to external tools through standardized protocols. -
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Node.js Telegram Bot API
Telegram Bot API for NodeJS
TelegramBot is an EventEmitter that emits several events. Message, received a new incoming Message of any kind. Depending on the properties of the Message, one of these events may ALSO be emitted, text, audio, document, photo, sticker, video, voice, contact, location, new_chat_members, left_chat_member, new_chat_title, new_chat_photo, delete_chat_photo, group_chat_created, game, pinned_message, poll, dice, migrate_from_chat_id, migrate_to_chat_id, channel_chat_created,... -
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highway-env
A minimalist environment for decision-making in autonomous driving
HighwayEnv is an OpenAI Gym-compatible environment focused on autonomous driving scenarios. It provides flexible simulations for testing decision-making algorithms in highway, intersection, and merging traffic situations. -
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Unity ML-Agents Toolkit
Unity machine learning agents toolkit
Train and embed intelligent agents by leveraging state-of-the-art deep learning technology. Creating responsive and intelligent virtual players and non-playable game characters is hard. Especially when the game is complex. To create intelligent behaviors, developers have had to resort to writing tons of code or using highly specialized tools. With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn”... -
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PettingZoo
An API standard for multi-agent reinforcement learning environments
PettingZoo is a standardized API and library for multi-agent reinforcement learning (MARL) environments. It provides a broad set of environments and tools to facilitate the development and evaluation of multi-agent algorithms.
