Projects sharing features with XianyuAutoAgent

This project is an AI assistant integration that connects OpenAI models to the Feishu team communication platform. It functions as a multi-model gateway that routes requests to GPT-4, GPT-4V, DALL-E-3, and Whisper models, enabling voice conversations, image generation, and multi-topic dialogues within team chats. The assistant operates through a bridge layer that translates Feishu chat events into internal commands, supporting plugin-based persona switching to alter response behavior and tone for different use cases. It distributes API requests across multiple authentication tokens for load b

CrewAI is a multi-agent orchestration framework and autonomous agent workflow engine. It provides a system for coordinating autonomous AI agents with specific roles and goals to solve complex tasks through collaborative intelligence. The framework distinguishes itself through a collaborative AI agent system that enables multiple language model instances to share intelligence and execute multi-step objectives via role-playing. It incorporates human-in-the-loop mechanisms, allowing for manual review checkpoints to validate decisions and refine outcomes within autonomous execution paths. The pl

Agency Swarm is a multi-agent orchestration framework and development kit designed to coordinate specialized AI agents through defined communication patterns and handoffs. It functions as a system for managing agent swarms, providing an API gateway to expose these coordinated collectives as production-ready HTTP endpoints. The project distinguishes itself through its Model Context Protocol integration layer, which connects agents to external data sources and capabilities. It implements specialized orchestration patterns, such as the orchestrator-worker model and role-based delegation, to tran

Nexent is an enterprise AI control plane and LLM agent orchestration platform. It provides a zero-code environment for designing, deploying, and managing production AI agents through a multi-agent collaboration framework that coordinates specialized autonomous agents using standardized messaging protocols. The platform integrates the Model Context Protocol to connect agents with external tools, plugins, and services via a universal communication interface. It further distinguishes itself with a dedicated RAG knowledge base manager that imports unstructured documents and utilizes hybrid search

Miroflow is an agent orchestration framework designed to coordinate multiple large language models and autonomous agents to perform complex research and reasoning tasks. It functions as a hierarchical workflow manager that distributes workloads across specialized agents using intent recognition and structured planning to gather deep information and solve challenging queries. The system distinguishes itself through a multi-model integration gateway and a provider-agnostic interface, allowing it to unify various language model providers. It extends these models via a tool-augmented framework th

This project is an autonomous software engineering platform and orchestration framework designed to manage specialized artificial intelligence agents. It provides a suite of tools for coordinating autonomous entities to execute complex development tasks, ranging from architectural planning and code reviews to performance optimization. The platform distinguishes itself through its multi-agent orchestration layer, which dynamically assigns roles based on an analysis of a project's technology stack. By utilizing a modular agent registry, the system scales capabilities across different software m

mi-gpt is a voice assistant bridge and agent orchestrator that connects smart speakers to large language models. It functions as an integration layer that routes audio requests from hardware speakers to AI providers and converts generated text back into speech via a customizable synthesis system. The project features a retrieval-augmented generation knowledge base that uses embeddings and external documents to provide context-aware responses. It includes a persona definition system for configuring behavioral rules, system prompts, and roleplay characteristics, alongside a plugin architecture

This project is a multi-agent development framework and orchestrator designed to coordinate autonomous AI agents for software engineering tasks. It functions as an engine that plans, implements, and reviews complex code changes across multiple files and isolated worktrees from a command line interface. The system distinguishes itself through a multi-agent coordination layer that decomposes tasks into sequential phases and applies changes across isolated worktrees to validate solutions. It maintains project-specific knowledge and constraints across sessions via context persistence using dedica

vibe-vibe is an LLM agent engineering framework and toolchain optimizer designed for orchestrating multi-agent systems. It serves as a comprehensive guide and methodology for transforming conceptual ideas into deployed applications through agentic software engineering. The project focuses on the orchestration of specialized AI agent roles with defined collaboration boundaries and iterative feedback loops. It provides frameworks for toolchain optimization, including the selection and evaluation of protocols that extend model capabilities and the design of standardized tool interfaces. The sys

Swarms is a multi-agent orchestration framework and autonomous agent toolkit designed to coordinate large language model agents. It serves as a workflow engine for managing agent relationships, providing the infrastructure to build autonomous agents with integrated memory, tool-calling capabilities, and reasoning loops. The framework is distinguished by its multi-agent consensus systems, which utilize voting, adversarial debates, and judge agents to synthesize high-quality responses. It supports a variety of collaboration patterns, including director-worker hierarchies, expert synthesis, and

This project is a comprehensive framework for building, evaluating, and connecting autonomous agent systems. It provides a library of standardized architectural patterns for implementing complex agent workflows, including multi-agent orchestration, iterative reasoning, and memory management. By offering a unified interface for model providers, the framework allows for consistent agent execution across different artificial intelligence services. The framework distinguishes itself through a focus on rigorous benchmarking and deterministic control. It includes a suite of tools for evaluating age

PromptX is an LLM agent orchestration framework designed to execute multi-step workflows using autonomous agents. It features a sandboxed tool execution environment for secure filesystem operations and external API integrations, alongside a persona management system that defines professional roles and domain expertise to control agent behavior. The system implements a semantic memory network for persistent knowledge storage, utilizing graph-based memory and engrams to retain information across sessions. This cognitive memory includes specialized tools for knowledge graph visualization, allowi

Operit is a private, voice-enabled AI agent designed to run quantized large language models offline within mobile Linux environments. It functions as a plugin-based agent that combines local inference with a hands-free interaction pipeline. The system distinguishes itself through the use of role cards to manage distinct AI personas and conversation histories. It integrates a voice-driven interface utilizing speech-to-text and text-to-speech modules, and it enables device automation by dispatching shell commands and accessibility services to navigate user interfaces. The project further cover

This is a curated gallery of real-world workflows demonstrating how to use Claude Code for AI-driven coding, debugging, and development automation. The showcase includes executable scripts that reproduce each AI interaction locally, allowing you to see exactly how the assistant generates, explains, and modifies code within a development environment. The project shows how to build custom AI agents with targeted prompts and multi-step slash commands, define project-wide memory that persists across sessions, and inject domain-specific knowledge through markdown files. It also demonstrates integr

Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives. The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys

Generative Agents is a computational platform for simulating autonomous agents that exhibit human-like social behaviors and decision-making processes. The system functions as a multi-agent simulator where individual participants operate within a virtual environment, driven by large language models to process observations and generate natural language actions. The framework distinguishes itself through a hierarchical memory system that allows agents to store, retrieve, and synthesize past experiences into higher-level insights. This architecture supports the development of complex social dynam

xianyu-auto-reply is a Python and FastAPI automation framework designed for the Xianyu marketplace. It serves as a comprehensive system for automating customer service, product listings, and order fulfillment. The project integrates large language models to generate context-aware responses to buyer inquiries and utilizes a cookie-based session management system to handle multiple concurrent user accounts. It also functions as a digital goods delivery system that automatically sends coupons and virtual items to customers after a purchase is completed. The framework covers a wide range of e-co

This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist

This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

Qwen-code is an AI-powered development framework designed for orchestrating intelligent coding agents within terminal and IDE environments. It provides a comprehensive infrastructure for automating software maintenance, code generation, and complex refactoring tasks by managing multi-agent workflows and persistent session states. The system is built to handle both interactive development and automated background processes, ensuring that agents can execute shell commands and file operations safely within isolated, sandboxed environments. What distinguishes this project is its focus on granular

This project functions as a Model Context Protocol server and a multi-agent orchestration framework designed to bridge large language models with external data sources and specialized engineering tools. It provides a structured environment for automating software development workflows, enabling models to interact directly with codebases and remote services to perform complex tasks. The system distinguishes itself through a multi-agent orchestration layer that coordinates autonomous assistants to manage shared objectives and multi-step workflows. By utilizing structured task decomposition and

This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into structured dialogue sequences between specialized agents. The system distinguishes itself through its message-passing orchestration, which manages state transitions and task delegation between independent participants. It supports dynamic conversation state management to provid

MetaGPT is an agentic workflow engine and multi-agent orchestration framework designed to automate complex software engineering and data analysis tasks. It functions as an automated software factory that transforms high-level natural language requirements into functional web applications, technical documentation, and production-ready code. By utilizing a runtime environment that manages the lifecycle of specialized agents, the platform bridges the gap between user intent and finished software components. The system distinguishes itself through role-based agent orchestration and dynamic task d

ChatGPT-wechat-bot is a chatbot automation system that integrates a large language model into WeChat to automatically generate and send replies in both private and group conversations. The project employs an event-driven pipeline that uses keyword-based trigger filtering and mention patterns to control when the bot responds. It manages multi-turn dialogues through stateful context management, which stores conversation history in memory and allows for session-based history clearing via designated commands. The system connects to remote models via API requests to handle automated messaging wor

Casibase is an open-source platform that orchestrates multi-turn conversations with large language models and manages retrieval-augmented knowledge bases from a single interface. It provides a unified system for connecting to over 30 AI model providers, ingesting documents into vector embeddings for semantic search, and running autonomous agent loops that can drive a browser, search the web, execute commands, and integrate with external tools. The platform distinguishes itself by combining AI conversation management with infrastructure and application orchestration capabilities. It includes a

AG2 is a multi-agent large language model orchestration framework, agentic workflow automation tool, and RAG-enabled agent platform. It functions as a communication protocol and framework for coordinating multiple AI agents to solve complex tasks through shared state and standardized messaging. The project distinguishes itself through flexible coordination strategies, including hierarchical agent organization, hub-and-spoke models, and dynamic routing that analyzes conversation context to distribute work. It implements multi-stage feedback loops for iterative refinement and uses schema-constr