Search Results for "multi-system" - Page 3
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Showing 2678 open source projects for "multi-system"
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OmniRoute
OmniRoute is an AI gateway for multi-provider LLM
OmniRoute is a routing and orchestration framework designed to simplify the handling of requests, workflows, or data flows across multiple services or endpoints in a unified manner. It focuses on providing a flexible abstraction layer where developers can define routing logic that dynamically directs traffic based on conditions, context, or predefined rules. The project emphasizes modularity and extensibility, allowing users to plug in different services or handlers without tightly coupling... -
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Oh My OpenCode Slim
Slimmed, cleaned and fine-tuned oh-my-opencode fork
Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents, each with a defined role such as orchestration, exploration, and execution, allowing tasks to be automatically delegated and completed through coordinated workflows. ... -
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Build Your Own OpenClaw
A step-by-step guide to build your own AI agent
Build Your Own OpenClaw is a step-by-step educational framework that teaches developers how to construct a fully functional AI agent system from scratch, gradually evolving from a simple chat loop into a multi-agent, production-ready architecture. The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable code. ... -
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AgentField
Build and run AI agents like microservices
AgentField is an open-source control plane designed to run AI agents as production-grade backend services, applying cloud-native principles similar to Kubernetes to the world of autonomous software. Instead of treating agents as isolated scripts or prototypes, the system elevates them to first-class infrastructure components that can be deployed, orchestrated, and managed at scale across distributed environments. Developers define agents as typed functions, and the platform automatically handles orchestration, communication, identity, and execution, allowing agents to behave like APIs within a broader system architecture. ... -
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OpenFang
Open-source Agent Operating System
OpenFang is an open-source agent operating system designed to orchestrate autonomous AI agents and workflows in a structured, production-oriented environment. Written primarily in Rust, the project focuses on building a high-performance runtime where multiple specialized agents can collaborate to complete complex computational or development tasks. It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable execution. ... -
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MindSearch
An LLM-based Multi-agent Framework of Web Search Engine
MindSearch is an AI-powered search engine based on large language models (LLMs) designed for deep semantic search and retrieval. It leverages InternLM's language model to understand complex queries and retrieve highly relevant answers from large datasets. -
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METATRON
AI-powered penetration testing assistant using local LLM on linux
METATRON is a multi-agent AI orchestration framework designed to coordinate complex workflows across multiple intelligent agents. It provides a structured system for task delegation, communication, and collaboration between agents. The framework emphasizes scalability, allowing multiple agents to work together on large or complex problems. It includes mechanisms for managing context, memory, and execution flow across tasks. -
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Claude Cognitive
Persistent context and multi-instance coordination
Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. ... -
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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. -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
...It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external cloud models. The system includes a multi-agent architecture that supports planning, action execution, reflection, and memory, allowing the agent to reason through tasks and refine results iteratively. A key component of the framework is a virtual machine sandbox environment that safely executes code generated by the agent without affecting the host system. -
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AG2
Framework for building and orchestrating multi-agent AI systems
...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 interaction, task delegation, and iterative reasoning, which are essential for building advanced AI-driven applications. AG2 is intended for developers experimenting with autonomous systems, research prototypes, or production-grade agent pipelines. ... -
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reverse-SynthID
Reverse engineering Gemini's SynthID detection
Reverse-SynthID is a research-focused project that analyzes and reverse-engineers Google’s SynthID watermarking system used in AI-generated images. It leverages signal processing and spectral analysis techniques to identify hidden watermark patterns without access to proprietary encoding methods. The project introduces a multi-resolution “SpectralCodebook” that maps watermark characteristics across different image sizes. Using this approach, it can detect SynthID watermarks with high accuracy and selectively reduce or remove them through frequency-domain manipulation. ... -
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Vedana
Open source multi-agent RAG over a knowledge graph
Vedana is an open-source multi-agent RAG system built around a typed knowledge graph. It is designed for questions that require structure, completeness, and traceability instead of simple text similarity. The system lets agents navigate data step by step through Cypher queries, vector search, document lookup, and source verification. Its architecture combines a knowledge graph, pgvector-based embeddings, incremental ETL, and a backoffice interface for chat, metrics, prompt tuning, and data loading. ... -
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ASSERT
Requirement-driven evaluation harness for AI agents and LLM
...It turns natural-language specifications, policies, product requirements, and launch criteria into structured tests that can be reviewed, executed, scored, and improved. The pipeline derives behavior categories, generates single-turn and multi-turn test cases, runs them against a target system, and uses an LLM judge to score conversations against the stated policies. It can evaluate hosted models, custom agents, multi-agent systems, REST clients, and frameworks such as LangGraph, CrewAI, AutoGen, DSPy, LlamaIndex, and OpenAI Agents SDK. ASSERT is designed to close the gap between what a system is supposed to do and what evaluation actually measures. ... -
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CoStrict
Strict AI coder for enterprises, quality first
...Unlike typical AI coding tools that prioritize speed over rigor, CoStrict introduces a “strict mode” methodology that enforces disciplined processes such as requirements analysis, architecture planning, task decomposition, and test generation before producing code. This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. It also incorporates multi-agent or multi-expert verification strategies, ensuring that generated code is validated from multiple perspectives before being accepted. -
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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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Langflow
Low-code app builder for RAG and multi-agent AI applications
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database. -
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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. -
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RAG Web UI
RAG Web UI is an intelligent dialogue system based on RAG
...It features a multi-turn conversational interface that maintains context across interactions, allowing users to engage in more natural and continuous dialogues with their data. The system is designed with a scalable architecture that separates frontend and backend components, enabling distributed deployment and efficient handling of large datasets. -
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Council of High Intelligence
18 AI personas deliberate your hardest decisions
...Instead of relying on one model response, it creates structured disagreement between different intellectual roles such as Socrates, Feynman, Kahneman, Torvalds, Aristotle, and others. The project supports multi-round reasoning, cross-examination, dissent quotas, novelty checks, and model diversity across different providers. It is designed for decisions where hidden assumptions, groupthink, vague framing, or overconfident conclusions can cause poor outcomes. Users can run a full council, a quick analysis, a two-person dialectic, or domain-specific triads for areas like architecture, strategy, ethics, debugging, product, risk, and AI safety. ... -
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Claude Code Bridge
Real-time multi-AI collaboration: Claude, Codex & Gemini
Claude Code Bridge is an open-source command-line tool designed to enable real-time collaboration between multiple AI coding assistants within a unified development environment. The system allows developers to coordinate interactions between models such as Claude, Codex, and Gemini so that they can work together on programming tasks. By maintaining persistent shared context between these models, the tool reduces redundant prompts and minimizes token usage while allowing each AI system to contribute specialized capabilities. ... -
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Image Fusion
Deep Learning-based Image Fusion: A Survey
...Survey style description of method taxonomy, architectures, loss types. Compilation of many state-of-the-art image fusion methods (infrared + visible, multi-focus, multi-exposure). Survey style description of method taxonomy, architectures, loss types. -
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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. -
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OpenMed
Open source healthcare AI
...OpenMed can be used in three main ways: as a simple Python API for scripts and notebooks, as a Docker-friendly FastAPI service for backend integration, and as a batch-processing system for multi-document workflows. -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. ...
