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