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| # Hello World Agent | ||
| # Hello World Agent 🌟 | ||
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| A simple demonstration agent using the ReACT methodology for analyzing and executing tasks. | ||
| A powerful, extensible agent framework leveraging ReACT methodology for autonomous task execution and human-in-the-loop collaboration. | ||
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| ## Quick Install | ||
| ## 🚀 Quick Start | ||
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| ```bash | ||
| pip install hello_agent | ||
| ``` | ||
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| ## Prerequisites | ||
| ## 🎯 Key Features | ||
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| | Feature | Description | | ||
| |---------|-------------| | ||
| | ReACT Methodology | Structured reasoning and action framework for intelligent task execution | | ||
| | Multi-Modal Tasks | Research, execution, and analysis capabilities | | ||
| | Streaming Responses | Real-time output with progress tracking | | ||
| | Human (HITL) Integration | Optional human validation at key decision points | | ||
| | Extensible Tools | Modular architecture for custom tool integration | | ||
| | Advanced LLM Support | Powered by OpenRouter API for state-of-the-art language models | | ||
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| ## 🔧 Core Capabilities | ||
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| | Capability | Details | | ||
| |------------|---------| | ||
| | Research | Information gathering, analysis, and synthesis | | ||
| | Execution | Task implementation with validation and quality checks | | ||
| | Analysis | Performance metrics, optimization, and recommendations | | ||
| | HITL | Human validation for critical decisions | | ||
| | Progress Tracking | Real-time status updates and metrics | | ||
| | Error Recovery | Robust error handling and state preservation | | ||
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| ## 🎮 Control Modes | ||
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| | Mode | Description | | ||
| |------|-------------| | ||
| | Autonomous | Self-directed task execution with ReACT methodology | | ||
| | HITL | Interactive mode with human validation points | | ||
| | Streaming | Real-time response processing and updates | | ||
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| ## 🛠️ Technical Stack | ||
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| | Component | Technology | | ||
| |-----------|------------| | ||
| | Core Framework | Python 3.8+ | | ||
| | LLM Integration | OpenRouter API | | ||
| | Task Management | CrewAI | | ||
| | Configuration | YAML-based | | ||
| | API | REST with OpenAPI spec | | ||
| | Documentation | Markdown + Examples | | ||
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| ## 📊 Performance Metrics | ||
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| | Metric | Target | | ||
| |--------|--------| | ||
| | Response Time | < 2s for standard operations | | ||
| | Streaming Latency | < 100ms | | ||
| | Task Success Rate | > 95% | | ||
| | HITL Integration | < 5s response time | | ||
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| ## 🔐 Security Features | ||
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| | Feature | Implementation | | ||
| |---------|----------------| | ||
| | Authentication | OpenRouter API key | | ||
| | Configuration | Environment variables | | ||
| | Rate Limiting | 100 requests/hour | | ||
| | Access Control | Role-based permissions | | ||
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| ## 📚 Documentation | ||
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| Comprehensive guides available for all aspects: | ||
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| | Guide | Content | | ||
| |-------|----------| | ||
| | [User Guide](agent/docs/readme.md) | Getting started and basic usage | | ||
| | [Templates](agent/docs/templates.md) | Customizing agent responses | | ||
| | [Tools](agent/docs/tools.md) | Extending agent capabilities | | ||
| | [Configuration](agent/docs/configuration.md) | System setup and options | | ||
| | [Advanced](agent/docs/advanced_implementations.md) | Complex implementations | | ||
| | [Memory/Storage](agent/docs/memory_and_storage.md) | Data management | | ||
| | [HITL](agent/docs/human_in_the_loop.md) | Human integration guide | | ||
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| ## 🎯 Use Cases | ||
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| | Industry | Applications | | ||
| |----------|--------------| | ||
| | Research | Literature review, data analysis | | ||
| | Development | Code generation, testing | | ||
| | Operations | System monitoring, optimization | | ||
| | Support | Customer service, documentation | | ||
| | Analysis | Performance metrics, reporting | | ||
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| ## 🔄 Integration Options | ||
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| | Method | Description | | ||
| |--------|-------------| | ||
| | CLI | Command-line interface | | ||
| | Python API | Direct library integration | | ||
| | REST API | HTTP endpoints | | ||
| | AI Plugin | OpenAI plugin compatibility | | ||
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| ## 🌐 Ecosystem Support | ||
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| | Component | Status | | ||
| |-----------|---------| | ||
| | PyPI Package | ✅ Available | | ||
| | Documentation | ✅ Comprehensive | | ||
| | Examples | ✅ Included | | ||
| | Community | 🚀 Growing | | ||
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| ## 📈 Future Roadmap | ||
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| | Feature | Status | | ||
| |---------|---------| | ||
| | Multi-Agent Support | 🚧 In Development | | ||
| | Advanced Analytics | 🎯 Planned | | ||
| | GUI Interface | 💡 Proposed | | ||
| | Cloud Deployment | 🎯 Planned | | ||
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| ## 🤝 Contributing | ||
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| Join our community! We welcome contributions of all kinds: | ||
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| - 🐛 Bug Reports | ||
| - 💡 Feature Suggestions | ||
| - 🔧 Code Contributions | ||
| - 📚 Documentation Improvements | ||
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| - Python 3.8 or higher | ||
| - OpenRouter API key (for LLM access) | ||
| ## 📄 License | ||
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| ## Installation | ||
| MIT License - See [LICENSE](LICENSE) for details. | ||
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| 1. Install the package: | ||
| ```bash | ||
| pip install hello_agent | ||
| ``` | ||
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| 2. Add your OpenRouter API key to the `.env` file: | ||
| ```bash | ||
| OPENROUTER_API_KEY=your_api_key_here | ||
| ``` | ||
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| ## Usage | ||
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| The agent can be run in two ways: | ||
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| 1. Using the command-line tool: | ||
| ```bash | ||
| agent --prompt "What is quantum computing?" --task research | ||
| ``` | ||
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| 2. Using Python code: | ||
| ```python | ||
| from agent.crew import HelloWorldCrew | ||
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| crew = HelloWorldCrew() | ||
| result = crew.run(prompt="What is quantum computing?", task_type="research") | ||
| ``` | ||
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| ### Command Line Arguments | ||
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| - `--prompt`: Specify the input prompt (default: "Tell me about yourself") | ||
| - `--task`: Specify the task type: research, execute, analyze, or both (default: both) | ||
| - `--hitl`: Enable human-in-the-loop mode (optional) | ||
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| Example: | ||
| ```bash | ||
| agent --prompt "What is quantum computing?" --task research --hitl | ||
| ``` | ||
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| ## Features | ||
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| - ReACT Methodology Implementation | ||
| - Research Analysis | ||
| - Task Execution | ||
| - Performance Analysis | ||
| - Progress Tracking | ||
| - Streaming Responses | ||
| - Optional Human-in-the-Loop Mode | ||
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| ## Documentation | ||
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| For detailed documentation and user guides, refer to: | ||
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| - [User Guide](agent/docs/readme.md) | ||
| - [Templates Guide](agent/docs/templates.md) | ||
| - [Tools Guide](agent/docs/tools.md) | ||
| - [Configuration Guide](agent/docs/configuration.md) | ||
| - [Advanced Implementations Guide](agent/docs/advanced_implementations.md) | ||
| - [Memory and Storage Guide](agent/docs/memory_and_storage.md) | ||
| - [Human-in-the-Loop Guide](agent/docs/human_in_the_loop.md) | ||
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| ## Examples | ||
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| Explore the [Examples](agent/examples/README.md) directory for sample usage scenarios and human-in-the-loop implementations. | ||
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| ## Project Structure | ||
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| ``` | ||
| hello_world/ | ||
| ├── config/ # Configuration files | ||
| │ ├── agents.yaml # Agent definitions | ||
| │ ├── tasks.yaml # Task definitions | ||
| │ └── analysis.yaml # Analysis rules | ||
| ├── tools/ # Custom tools | ||
| ├── docs/ # Documentation | ||
| └── examples/ # Example implementations | ||
| ``` | ||
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| ## Contributing | ||
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| 1. Fork the repository | ||
| 2. Create your feature branch (`git checkout -b feature/amazing-feature`) | ||
| 3. Commit your changes (`git commit -m 'Add amazing feature'`) | ||
| 4. Push to the branch (`git push origin feature/amazing-feature`) | ||
| 5. Open a Pull Request | ||
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| ## License | ||
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| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | ||
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| ## Acknowledgments | ||
| ## 🙏 Acknowledgments | ||
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| - Built with [CrewAI](https://github.com/joaomdmoura/crewAI) | ||
| - Powered by [OpenRouter](https://openrouter.ai/) | ||
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| --- | ||
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| <p align="center"> | ||
| Made by rUv with 💫 for the AI community | ||
| </p> |