Projects sharing features with Astron Agent

Multica is an autonomous coding agent manager and LLM agent orchestration platform. It coordinates teams of autonomous agents to execute coding tasks and manage their lifecycles through a centralized dashboard. The system provides multi-tenant agent workspaces that isolate agents, settings, and project issues into distinct organizational boundaries. The platform distinguishes itself through an agent skill library that captures successful task solutions as reusable, versioned skills. These skills are shared across the agent team and pinned using content hashes to ensure consistent behavior acr

AgentScope is a multi-agent framework and orchestration platform designed for building and coordinating teams of language model agents. It provides a system for managing multiple agents that collaborate to solve complex tasks through structured communication and state sharing. The project distinguishes itself with a focus on production-ready deployment and security, featuring a multi-tenant hosting service that ensures session isolation between different users. It includes a sandboxed tool execution environment and fine-grained permission controls to manage how agents access system resources

Agent Squad is a multi-agent system orchestrator and language model agent orchestration framework. It serves as an AI workflow automation engine and tool integration layer designed to coordinate teams of specialized agents to solve complex tasks through routing, parallel execution, and state management. The project is distinguished by its ability to dynamically compose purpose-specific agents on-demand and route requests based on intent, language, or domain expertise. It supports advanced coordination patterns, including parallel subtask distribution, sequential task pipelines, and the abilit

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

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

Paperclip is an LLM agent orchestration platform and governance suite designed to coordinate teams of autonomous AI agents. It provides a management plane for defining organizational hierarchies, assigning roles, and aligning individual agent tasks with a structured mission tree to ensure work maps to business objectives. The project distinguishes itself through a specialized agent skill registry and workspace manager. It allows for the discovery and injection of reusable workflows into agent runtimes without retraining and provides isolated, sandboxed execution environments with persistent s

PydanticAI is a Python framework designed for building production-grade autonomous agents. It provides a unified interface for interacting with diverse language models, enabling developers to construct agents that perform complex tasks through structured data validation, tool execution, and multi-turn conversation management. The library centers on type-safe schema enforcement, ensuring that model inputs and outputs remain consistent and reliable throughout the agent's lifecycle. The framework distinguishes itself through a robust architecture that emphasizes modularity and testability. It ut

53AIHub is a centralized orchestration platform for deploying and managing AI agents and prompts across multiple large language model providers. It functions as a multi-model AI gateway and an operation portal for AI services, providing a unified interface to coordinate agents and prompts from various external platforms. The project distinguishes itself as a white-label AI portal designed for self-hosted infrastructure, allowing for full control over operational data on private servers or containers. It includes a comprehensive AI SaaS administration layer with a multi-tenant subscription eng

Agentverse is a multi-agent framework and orchestrator designed for deploying and managing multiple large language model agents. It provides a simulation environment where agents interact based on custom personas and defined interaction rules to solve tasks or simulate social dynamics. The system features a tool integration layer that connects agents to external functional plugins and specialized tools, extending their capabilities beyond text generation. It uses a combination of persona-based prompt injection and state-managed memory to maintain agent consistency and specialized skill sets d

This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a decentralized network. It serves as a collection of patterns and examples for developing intelligent software entities capable of performing complex tasks, making decisions, and interacting with other agents to achieve shared goals. The framework distinguishes itself through its focus on multi-agent orchestration and decentralized communication. It enables the coordination of specialized agent teams that collaborate on workflows through structured messaging protocols, allowing

LibreTranslate is an open-source, self-hosted machine translation engine that provides a private alternative to proprietary cloud-based translation services. It functions as a portable translation server, allowing users to process text and document translations locally or within their own infrastructure without relying on external providers. The platform distinguishes itself through its focus on privacy and flexible deployment, supporting anonymous network routing to bypass restrictive firewalls and protect user data. It is designed for integration into broader software ecosystems, offering a

Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

Julep is an LLM agent orchestration platform and multi-tenant AI backend designed for building autonomous agents with persistent memory, tool integration, and complex multi-step workflows. It serves as a framework for configuring agent identities and behavioral settings to automate specialized professional roles. The platform distinguishes itself through its stateful session management and RAG infrastructure engine, which allow agents to maintain long-term interaction history and ground responses in indexed private documents. It provides enterprise-grade infrastructure features, including a s

GLaDOS is a multimodal AI agent framework designed to create autonomous systems that process text, speech, and visual data to interact with users and their environment. It centers on an AI personality framework that emulates complex character personas using a multi-agent architecture and configurable behavioral profiles. The project distinguishes itself through an integrated tool layer that connects language models to external hardware, smart home devices, and system APIs via a standardized protocol. It features a character text-to-speech engine with low-latency playback and interruption hand

Deepagents is an LLM agent orchestration platform and stateful application server designed for deploying and managing AI agents built with computational graphs. It provides a containerized runtime environment that handles agent execution, state persistence, and the versioning of AI assistants. The platform distinguishes itself through deep integration with the Model Context Protocol, allowing agents to function as servers that expose tools and capabilities to external clients. It features a sophisticated observability suite for capturing execution traces, performing LLM-based evaluations agai

Cipher is an AI agent orchestration framework and LLM context memory layer. It provides a collaborative AI knowledge base and a context synchronization service that allows AI agents and CLI tools to maintain a persistent, structured memory of project decisions and codebase patterns across different sessions and machines. The system distinguishes itself through a version-controlled context model, using branches and commits to track how project knowledge evolves. It features a hierarchical knowledge store where information is organized as markdown files and can be synchronized between local env

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

Phidata is an LLM agent framework and agentic workflow orchestrator used to build autonomous agents that integrate custom data, tools, and memory. It provides a production environment for serving these agents as services via APIs, utilizing server-sent events and websockets for real-time communication. The system distinguishes itself through a human-in-the-loop control layer that requires manual approval and administrative sign-off for specific tool executions. It also implements a multi-tenant AI infrastructure that uses token-based roles to ensure data isolation between different tenants.

Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag

This project is an agentic retrieval-augmented generation platform and orchestration framework designed to connect large language models to private enterprise data. It serves as a self-hosted AI gateway that integrates vector databases and external tools to automate complex information retrieval and generation tasks. The system differentiates itself through an AI agent workflow builder that orchestrates multiple specialized agents with distinct roles to solve multi-step problems. It includes a dedicated vector database integration interface for indexing private documents and a secure sandbox

AutoAgent is a multi-agent orchestrator and natural language workflow builder designed to connect multiple large language models with external API tools. It provides a framework for designing multi-step agent interactions and reasoning processes using plain text instead of manual code. The platform functions as a tool integration gateway, linking agents to third-party platforms and authenticated browser sessions. It enables the execution of complex analytical tasks and deep research by distributing work across collaborative agent frameworks and importing browser cookies to access restricted w

This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu

adk-go is an agent orchestration engine and multi-agent framework for building, coordinating, and scaling systems of large language model agents. It provides a tool integration kit to connect agents with external APIs, custom functions, and diverse data sources. The project utilizes graph-based workflow orchestration to blend deterministic logic with adaptive reasoning. It supports modular multi-agent composition, allowing specialized agents to be organized into hierarchical structures to manage complex tasks through coordinated workflows. The framework includes tools for performance evaluat

Open-Assistant is a conversational assistant and a system for creating large language model training datasets. It utilizes a client-server architecture that separates the conversational user interface from language model processing through an API. The project features a retrieval-augmented generation system that fetches external data from search engines to provide real-time knowledge. It also includes a standardized plugin interface for connecting language models to third-party systems and external software tools. The system provides a pipeline for collecting and labeling human-annotated pro

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

ClaraVerse is a self-hosted orchestration platform for deploying and managing local language models, autonomous agents, and automated workflows on private infrastructure. It functions as a containerized backend manager that orchestrates services, databases, and model providers within local containers to maintain data sovereignty. The platform features a visual workflow builder with a drag-and-drop interface for designing complex parallel task sequences. It utilizes a multi-model abstraction layer to normalize interactions across diverse local and remote AI endpoints and includes a retrieval a

This project is a comprehensive suite of AI tools and frameworks, featuring an LLM multi-agent orchestrator, an autonomous agent runtime, and a stateful application framework. It provides the infrastructure to build and manage specialized AI agents capable of coordinating complex tasks through graph-based workflows and shared state. The system is distinguished by its implementation of the Model Context Protocol, allowing for standardized resource discovery and communication between AI clients and servers. It further includes an AI-powered documentation generator designed to analyze source cod