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AI agent framework for building autonomous systems that solve real-world tasks effectively.","maintainers":[{"name":"pzzaworks","email":"berke@pzza.works"}],"readme":"![Astreus](assets/intro.webp)\n\nOpen-source AI agent framework for building autonomous systems that solve real-world tasks effectively.\n\n[![npm version](https://badge.fury.io/js/@astreus-ai%2Fastreus.svg)](https://badge.fury.io/js/@astreus-ai%2Fastreus)\n[![Node.js Version](https://img.shields.io/badge/node-%3E%3D22.0.0-brightgreen)](https://nodejs.org/)\n[![code style: prettier](https://img.shields.io/badge/code_style-prettier-ff69b4.svg)](https://github.com/prettier/prettier)\n[![TypeScript](https://img.shields.io/badge/TypeScript-007ACC?logo=typescript&logoColor=white)](https://www.typescriptlang.org/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n## Installation\n\n```bash\nnpm install @astreus-ai/astreus\n```\n\n## Basic Usage\n\n```javascript\nimport { Agent } from '@astreus-ai/astreus';\n\nconst agent = await Agent.create({\n  name: 'Assistant',\n  model: 'gpt-4o',\n  memory: true\n});\n\nconst response = await agent.ask('How can you help me?');\n```\n\n## Core Features\n\n- **Sub-Agents**: Intelligent task delegation with specialized agent coordination, hierarchical workflows, and LLM-powered assignment\n- **Advanced Memory System**: Per-agent persistent memory with automatic context integration and vector search capabilities\n- **Task Orchestration**: Structured task execution with status tracking, dependency management, and streaming support\n- **Graph Workflows**: Complex workflow orchestration with conditional execution, parallel processing, and sub-agent integration\n- **MCP Integration**: Model Context Protocol support for seamless external tool and service connections\n- **Plugin System**: Extensible tool integration with JSON schema validation and automatic LLM function calling\n- **Vision Processing**: Built-in image analysis and document processing capabilities for multimodal interactions\n- **Knowledge Base**: RAG integration with document chunking, vector embeddings, and similarity search\n- **Multi-LLM Integration**: Unified interface for OpenAI, Claude, Gemini, and Ollama with automatic model routing\n\n## 📖 Documentation\n\nFor detailed documentation and advanced features, visit:\n- [Official Documentation](https://astreus.org/docs)\n- [Examples](https://astreus.org/docs/examples)\n\n## 🤝 Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n1. Fork the repository\n2. Create your feature branch (`git checkout -b feature/amazing-feature`)\n3. Commit your changes (`git commit -m 'Add some amazing feature'`)\n4. Push to the branch (`git push origin feature/amazing-feature`)\n5. Open a Pull Request\n\n## 📄 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## 📬 Contact\n\nAstreus Team - [https://astreus.org](https://astreus.org)\n\nProject Link: [https://github.com/astreus-ai/astreus](https://github.com/astreus-ai/astreus)","readmeFilename":"README.md"}