⚡ Concurrent Agent Workflows with Azure OpenAI (Responses API) (.NET)
📋 High-Performance Parallel Processing Tutorial
This notebook demonstrates concurrent workflow patterns using the Microsoft Agent Framework for .NET and Azure OpenAI (Responses API). You'll learn how to build high-performance, parallel processing workflows that maximize throughput by executing multiple AI agents simultaneously while maintaining coordination and data consistency.
🎯 Learning Objectives
🚀 Concurrent Processing Fundamentals
- Parallel Agent Execution: Run multiple AI agents simultaneously for maximum performance
- Async/Await Patterns: Leverage .NET's async programming model for efficient concurrency
- Azure OpenAI (Responses API): Coordinate multiple concurrent calls to the Azure OpenAI Responses API
- Resource Management: Efficiently manage AI model resources across concurrent operations
🏗️ Advanced Concurrency Architecture
- Task-Based Parallelism: Use .NET Task Parallel Library for optimal concurrent execution
- Synchronization Patterns: Coordinate concurrent agents while avoiding race conditions
- Load Balancing: Distribute work efficiently across available concurrent processing capacity
- Fault Tolerance: Handle individual agent failures without stopping the entire workflow
🏢 Enterprise Concurrent Applications
- High-Volume Document Processing: Process multiple documents simultaneously
- Real-Time Content Analysis: Concurrent analysis of incoming data streams
- Batch Processing Optimization: Maximize throughput for large-scale data processing operations
- Multi-Modal Analysis: Parallel processing of different content types and formats
⚙️ Prerequisites & Setup
📦 Required NuGet Packages
Essential packages for high-performance concurrent workflows:
xml
🔑 Azure OpenAI Configuration
Environment Setup (.env file):
env