Search Results for "ai framework" - Page 4
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Showing 718 open source projects for "ai framework"
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super-agent-party
All-in-one AI companion! Desktop girlfriend + virtual streamer
Super Agent Party is an open-source experimental framework designed to demonstrate collaborative multi-agent AI systems interacting within a shared environment. The project explores how multiple specialized AI agents can coordinate to solve complex tasks by communicating with each other and sharing information. Instead of relying on a single monolithic model, the framework organizes agents with different roles or capabilities that cooperate to achieve goals. ... -
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npcpy
The AI toolkit for the AI developer
npcpy is a Python-based agent framework and command-line toolkit (the NPC Shell) for developers to build, test, and integrate AI agents into their workflows, including both command-line and GUI interfaces via NPC Studio. Welcome to npcpy, the core library of the NPC Toolkit that supercharges natural language processing pipelines and agent tooling. npcpy is a flexible framework for building state-of-the-art applications and conducting novel research with LLMs. ... -
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Griptape
Python framework for AI workflows and pipelines with chain of thought
The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. -
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HybridClaw
The enterprise operating layer for open agents
HybridClaw is an emerging open-source framework focused on enabling hybrid AI agent systems that combine local execution, tool integration, and multi-agent orchestration into a cohesive development environment. It is designed to work alongside modern agent ecosystems such as OpenClaw, Claude Code, and similar agentic coding tools, providing a flexible infrastructure for managing agent behaviors, workflows, and capabilities. -
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Dynamiq
An orchestration framework for agentic AI and LLM applications
Dynamiq is an open-source orchestration framework designed to streamline the development of generative AI applications that rely on large language models and autonomous agents. The framework focuses on simplifying the creation of complex AI workflows that involve multiple agents, retrieval systems, and reasoning steps. Instead of building each component manually, developers can use Dynamiq’s structured APIs and modular architecture to connect language models, vector databases, and external tools into cohesive pipelines. ... -
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OpenClaw CN
The Chinese version of OpenClaw
OpenClaw-CN is a Chinese language community adaptation and localization of the OpenClaw project, focused on making a powerful open-source agent framework usable and understandable for Chinese-speaking developers. It includes translated documentation, localized examples, and language-specific nuances so that developers in the Chinese ecosystem can adopt and contribute without a language barrier. The repository mirrors the structure of the upstream project but adds Chinese translations of core workflows, prompts, guidelines, and best practices for building multi-agent systems or AI applications. ... -
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agency-agents-zh
193 plug-and-play AI expert roles
agency-agents-zh is a framework focused on building and coordinating multiple AI agents, likely with a particular emphasis on Chinese-language environments or documentation. The project appears to explore the concept of agent collaboration, where different agents handle specialized tasks and communicate to achieve broader objectives. It is designed to simulate organizational workflows, enabling complex problem-solving through distributed intelligence rather than a single monolithic model. ... -
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omp (Oh My Pi)
AI Coding agent for the terminal
omp (Oh-My-Pi) is an open-source AI agent toolkit focused on creating intelligent coding assistants that operate directly from the terminal environment. The project provides a command-line coding agent capable of analyzing repositories, generating commits, editing code, and interacting with development tools through an integrated tool system. Instead of functioning as a simple prompt-based assistant, the system includes an agent architecture that can inspect Git repositories, analyze... -
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GitAgent
A framework-agnostic, git-native standard for defining AI agents
GitAgent is an open standard and toolkit for defining portable AI agents using Git repositories as their foundational structure. The core idea behind the project is that an AI agent can be fully described by a set of files stored in a repository, allowing developers to clone the repository and instantly obtain a runnable agent. Unlike many frameworks that tightly couple agents to specific ecosystems, GitAgent is designed to be framework-agnostic so that the same agent definition can operate across multiple platforms and AI tooling environments. ... -
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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. -
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BioNeMo
BioNeMo Framework: For building and adapting AI models
BioNeMo is an AI-powered framework developed by NVIDIA for protein and molecular generation using deep learning models. It provides researchers and developers with tools to design, analyze, and optimize biological molecules, aiding in drug discovery and synthetic biology applications. -
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Harmonist
Portable AI agent orchestration with mechanical protocol enforcement
Harmonist is a portable multi-agent orchestration framework for AI coding assistants such as Cursor, Claude Code, Copilot, Windsurf, and Aider. It is designed to make agent workflows more reliable by enforcing protocol rules mechanically instead of trusting prompts alone. The framework includes a catalog of specialized agents, validated memory behavior, supply-chain checks, and hooks that gate code-changing turns. -
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BMad Method
Breakthrough Method for Agile Ai Driven Development
BMad Method is a comprehensive AI-driven software development framework that structures the entire lifecycle of building applications through coordinated agent workflows and agile methodologies. It transforms AI from a reactive assistant into a structured team of specialized roles such as product manager, architect, developer, and QA, each operating within predefined workflows. -
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Bytebot
Bytebot is an AI desktop agent that automates computer tasks
Bytebot is an open-source AI assistant and automation framework built to help developers and teams automate repetitive software development tasks, accelerate coding workflows, and integrate intelligent assistance into everyday tooling. It typically includes capabilities for code generation, refactoring suggestions, automated testing assistance, and integration with source control systems to make commits or generate pull requests guided by natural language prompts. -
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Olares
Olares: An Open-Source Sovereign Cloud OS for Local AI
Olares is an AI-powered chatbot framework designed to support real-time natural language understanding and response generation. -
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AgentUniverse
agentUniverse is a LLM multi-agent framework
AgentUniverse is a multi-agent AI framework that enables coordination between multiple intelligent agents for complex task execution and automation. -
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kagent
Kubernetes native framework for building AI agents
Kagent is a Kubernetes-native framework for building, deploying, and operating AI agents as first-class cloud-native workloads. It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. ... -
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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. -
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Mastra
The TypeScript AI agent framework
Mastra is a TypeScript-first framework for building AI-powered applications and agents, designed to take projects from prototype to production on a modern JavaScript/TypeScript stack. It integrates cleanly with React, Next.js, and Node-based backends, but can also run as a standalone server, giving teams flexibility in how they deploy their AI logic. At its core, Mastra provides abstractions for agents, workflows, tools, memory, retrieval, and model routing, so developers can focus on specifying behavior rather than wiring infrastructure from scratch. ... -
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LiveKit Agents
Framework for building realtime multimodal voice AI agents apps
LiveKit Agents is an open source framework designed for building realtime AI agents that can participate as programmable entities within communication sessions. It enables developers to create conversational and multimodal agents capable of processing voice, audio, and other inputs in realtime environments. These agents can join LiveKit rooms as participants and interact with users or systems through speech, text, and other modalities. -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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Multi-Agent Orchestrator
Flexible and powerful framework for managing multiple AI agents
Multi-Agent Orchestrator is an AI coordination framework that enables multiple intelligent agents to work together to complete complex, multi-step workflows. -
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LiteRT
LiteRT, successor to TensorFlow Lite
...The framework simplifies on-device AI development through automated accelerator selection, asynchronous execution, and optimized memory handling. It also includes specialized support for large language models and generative AI workloads through LiteRT-LM and related tooling. With broad hardware compatibility and advanced performance optimizations, LiteRT enables developers to build fast, scalable, and efficient AI applications that run directly on user devices. -
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Notte
Opensource browser using agents
Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications. -
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SuperPrompt
Experimental prompt framework exploring reasoning structures in AI
SuperPrompt is an experimental open source project focused on designing complex prompts intended to help researchers and developers better understand how AI agents reason and respond. It explores structured prompt engineering techniques that combine symbolic expressions, logical constructs, and conceptual frameworks to guide large language models toward deeper reasoning processes. Its main concept revolves around a highly structured prompt format that includes tagged sections for reasoning,...
