https://github.com/LondheShubham153/strands-agents-workshop
This is a One Shot Course on Strands Agents with Notebooks, Scripts, resources and Projects to take you from Zero To Hero in Strands Agents SDK usage in your Agentic AI Journey
https://github.com/LondheShubham153/strands-agents-workshop
agentic-ai aws bedrock strands-agents
Last synced: 5 months ago
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This is a One Shot Course on Strands Agents with Notebooks, Scripts, resources and Projects to take you from Zero To Hero in Strands Agents SDK usage in your Agentic AI Journey
- Host: GitHub
- URL: https://github.com/LondheShubham153/strands-agents-workshop
- Owner: LondheShubham153
- Created: 2025-08-17T08:49:38.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-10-30T09:49:59.000Z (8 months ago)
- Last Synced: 2025-10-30T11:43:37.868Z (8 months ago)
- Topics: agentic-ai, aws, bedrock, strands-agents
- Language: Jupyter Notebook
- Homepage: https://strandsagents.com/
- Size: 138 KB
- Stars: 18
- Watchers: 0
- Forks: 19
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
Awesome Lists containing this project
- awesome-strands-agents - Strands Agents Workshop - shot course on Strands Agents with notebooks, scripts, resources and projects to take you from Zero to Hero in Strands Agents SDK usage for your Agentic AI journey | [LondheShubham153/strands-agents-workshop](https://github.com/LondheShubham153/strands-agents-workshop) | Learning Resources | (Community Projects / For PyPI Packages)
README
# Strands Agents Workshop
A comprehensive workshop for building AI agents with the Strands framework on AWS Cloud. This workshop provides both Jupyter notebook and Python script formats for flexible delivery.
## 🎯 Workshop Overview
This 2-3 hour workshop takes participants from basic agent creation to advanced multi-agent systems, covering:
- Basic agent creation and configuration
- Tool integration and custom capabilities
- Multi-model support (AWS Bedrock + Ollama)
- Memory-enabled agents with persistence
- Advanced real-world applications
- Multi-agent system orchestration
- MCP (Model Context Protocol) integration
## 📁 Repository Structure
```
strands-agents-workshop/
├── README.md # This file
├── requirements.txt # Python dependencies
├── SETUP.md # Detailed setup instructions
├── CONTRIBUTING.md # Contribution guidelines
├── notebooks/ # Jupyter notebook format
│ ├── 01-basic-agent-creation.ipynb
│ ├── 02-working-with-tools.ipynb
│ ├── 03-custom-models.ipynb
│ ├── 04-memory-enabled-agents.ipynb
│ ├── 05-advanced-examples.ipynb
│ ├── 06-multi-agent-systems.ipynb
│ ├── 07-mcp-integration.ipynb
│ └── README.md
├── scripts/ # Python script format
│ ├── 01_basic_agents.py
│ ├── 02_agent_tools.py
│ ├── 03_custom_models.py
│ ├── 04_memory_agents.py
│ ├── 05_advanced_examples.py
│ ├── 06_multi_agent_systems.py
│ ├── 07_mcp_integration.py
│ ├── mcp.json
│ └── README.md
├── .env.example # Environment variables template
└── venv/ # Virtual environment
```
## 🚀 Quick Start
### Prerequisites
- Python 3.8+
- AWS Account with Bedrock access
- (Optional) Ollama for local models
### Setup
```bash
# Clone and navigate
cd strands-agents-workshop
# Create virtual environment (if not exists)
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Configure environment variables
cp .env.example .env
# Edit .env with your AWS credentials and API keys
# Alternative: Configure AWS (choose one method)
aws configure # Interactive setup
# OR
export AWS_PROFILE=your-profile
export AWS_REGION=us-west-2
```
### Choose Your Format
#### Option 1: Jupyter Notebooks (Recommended for Interactive Learning)
```bash
jupyter notebook notebooks/
```
#### Option 2: Python Scripts (IDE Development)
```bash
cd scripts
python 01_basic_agents.py
```
## 🎓 Learning Path
### Module 1: Foundation (30 minutes)
- **01-basic-agent-creation**: Create your first agents
- **02-working-with-tools**: Add capabilities with tools
### Module 2: Models & Memory (45 minutes)
- **03-custom-models**: AWS Bedrock and Ollama integration
- **04-memory-enabled-agents**: Persistent conversations
### Module 3: Advanced Applications (60 minutes)
- **05-advanced-examples**: Real-world use cases
- **06-multi-agent-systems**: Agent orchestration
### Module 4: Integration (30 minutes)
- **07-mcp-integration**: Model Context Protocol
### Configuration
Copy the example environment file and configure your settings:
```bash
cp .env.example .env
# Edit .env with your AWS credentials and preferences
```
### AWS Bedrock Setup
```bash
# Ensure your AWS credentials have Bedrock access
aws bedrock list-foundation-models --region us-west-2
```
### Ollama Setup (Optional)
```bash
# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh
# Pull recommended models
ollama pull llama3.2:1b
ollama pull llama3.2:3b
```
### Memory Configuration (Optional)
```bash
# For Mem0 integration
export MEM0_API_KEY=your-api-key
```
## 📚 Documentation
- [Official Strands Agents Docs](https://strandsagents.com/latest/documentation/docs/) - Official documentation
- [Setup Instructions](SETUP.md) - Detailed environment setup
- [Troubleshooting](docs/TROUBLESHOOTING.md) - Common issues and solutions
- [API Reference](docs/API_REFERENCE.md) - Strands Agents API guide
- [Contributing](CONTRIBUTING.md) - How to contribute
## 🆘 Support
For issues and questions:
1. Check [TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)
2. Review notebook comments and documentation
3. Verify your environment setup
## 📄 License
This workshop content is provided for educational purposes.
---
**Ready to build intelligent agents? Start with `notebooks/01-basic-agent-creation.ipynb` or `scripts/01_basic_agents.py`!**