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# Magentic Orchestration Sample
This sample showcases the Magentic Orchestration Pattern in .NET, setting up a team with three roles:
- **ResearcherAgent** gathers factual background information.
- **CoderAgent** uses `HostedCodeInterpreterTool` for quantitative analysis.
- **MagenticManager** plans the work, tracks progress, and decides who should act next.
## What This Sample Demonstrates
- Building a Magentic workflow with `MagenticWorkflowBuilder`
- Combining standard responses-based agents with a code interpreter-enabled participant
- Streaming orchestration events such as the initial plan, replans, and progress-ledger updates
- Printing the final multi-agent conversation transcript
## Prerequisites
- `FOUNDRY_PROJECT_ENDPOINT` set to your Azure AI Foundry project endpoint
- `FOUNDRY_MODEL` set to your model deployment name (defaults to `gpt-5.4-mini`)
- `az login` completed before running the sample
## Running the Sample
```bash
dotnet run
```
## Expected Output
The sample prints:
1. The original task prompt
2. Streamed updates from the participating agents
3. Magentic plan and progress-ledger events as the workflow coordinates the team
4. The final conversation transcript returned by the workflow
## Related Samples
- [Handoff Orchestration](../Handoff) - another multi-agent orchestration pattern in .NET workflows
- [Python Magentic workflow sample](../../../../../python/samples/03-workflows/orchestrations/magentic.py) - the source scenario that this sample ports