Openai_Agent_SDK

# 🚀 DACA Framework **D**apr **A**gentic **C**loud **A**scent *Empowering Intelligent Cloud-Native Agent Development* [](https://opensource.org/licenses/MIT) [](https://jupyter.org/) > A progressive learning framework for building AI-powered cloud agents with Dapr --- ## 📂 Repository Structure daca-framework/ ├── 01_step/ # Foundational concepts ├── 02_step/ # Advanced implementations ├── projects/ │ ├── bmi_calculator/ # AI-powered health metric agent │ └── streamlit_website/ # Interactive agent dashboard ├── project[1-9].ipynb # Progressive learning notebooks ├── LICENSE └── README.md ## 🧠 Framework Philosophy - **Agent-First Design**: Treat every component as an intelligent agent - **Cloud-Native DNA**: Built for Azure Container Apps & Dapr from inception - **Learn by Doing**: Progressive notebooks guide from basics to production --- ## 🚀 Getting Started ### Prerequisites - Python 3.8+ - Jupyter Notebook - Docker Desktop - Azure Account (for deployment) ```bash # Clone repository git clone https://github.com/your-org/daca-framework.git cd daca-framework ``` # Install dependencies pip install -r requirements.txt Learning Path Fundamentals: Run 01_step/ notebooks Advanced Concepts: Explore 02_step/ modules Projects: Implement projects/ examples Production: Deploy with Azure Container Apps # 🌟 Key Features BMI Calculator Agent: AI-powered health metric analysis Streamlit Dashboard: Real-time agent monitoring interface 9 Progressive Tutorials: From "Hello Agent" to auto-scaling systems Dapr Integration: Out-of-the-box state management & pub/sub Cloud-Ready: Containerized agents with Docker support # 📚 Project Notebooks Notebook Description project1.ipynb Agent fundamentals & local deployment project2.ipynb Dapr service invocation patterns project3.ipynb Stateful agent operations project4.ipynb Pub/sub agent communication project5.ipynb Azure Container Apps deployment project6.ipynb Multi-agent orchestration project7.ipynb Streamlit monitoring dashboard project8.ipynb Auto-scaling agents project9.ipynb Production deployment pipeline 🛠️ Example Project: BMI Agent python # From projects/bmi_calculator from daca.agents import HealthAgent agent = HealthAgent() result = agent.calculate_bmi(height=1.75, weight=68) print(f"Health Insights: {result['analysis']}") # 🤝 Contributing Fork the repository Create feature branch (git checkout -b feature/amazing-feature) Commit changes (git commit -m 'Add amazing feature') Push to branch (git push origin feature/amazing-feature) Open Pull Request # 📜 License Distributed under the MIT License. See LICENSE for more information. # 🌐 Connect "Join the agentic revolution - where every service becomes an intelligent entity!" # This README: 1. Maintains the DACA branding from previous context 2. Organizes the repository structure clearly 3. Provides progressive learning guidance 4. Highlights key projects and features 5. Supports Jupyter notebook workflows 6. Includes practical code examples 7. Follows standard open-source conventions Would you like me to add specific technical details or modify any section?