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3.2.1. Framework Selection
- Concept: Frameworks provide scaffolding for multi-agent systems
- Purpose: Simplify orchestration of multiple AI components
- Benefit: Proven patterns for complex AI systems
For AI orchestration and multi-agent workflows: Use Semantic Kernel framework
Comparative Table: Framework Selection
| Framework | Best For | Multi-Agent Support |
|---|---|---|
| Semantic Kernel | AI orchestration, plugins | ✅ Full support |
| Azure Bot Framework | Conversational bots | ❌ Limited |
| Azure ML Studio | ML model development | ❌ Not designed for |
| Cognitive Services API | Pre-built AI functions | ❌ No orchestration |
# Semantic Kernel setup
import semantic_kernel as sk
kernel = sk.Kernel()
# Add plugins (tools)
kernel.add_plugin(CalendarPlugin(), plugin_name="calendar")
kernel.add_plugin(EmailPlugin(), plugin_name="email")
kernel.add_plugin(SearchPlugin(), plugin_name="search")
# Create agent with orchestration
agent = kernel.create_agent(
model="gpt-4",
plugins=["calendar", "email", "search"]
)