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articles/ai-studio/how-to/develop/langchain.md

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@@ -385,25 +385,25 @@ You can use the tracing capabilities in Azure AI Foundry by creating a tracer. L
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1. Using the connection string directly:
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```python
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import os
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application_insights_connection_string = "instrumentation...."
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```
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```python
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import os
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application_insights_connection_string = "instrumentation...."
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```
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2. Using the Azure AI Foundry SDK and the project connection string (in the landing page of your project).
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```python
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from azure.ai.projects import AIProjectClient
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from azure.identity import DefaultAzureCredential
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project_client = AIProjectClient.from_connection_string(
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credential=DefaultAzureCredential(),
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conn_str="<your-project-connection-string>",
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)
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application_insights_connection_string = project_client.telemetry.get_connection_string()
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```
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```python
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from azure.ai.projects import AIProjectClient
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from azure.identity import DefaultAzureCredential
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project_client = AIProjectClient.from_connection_string(
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credential=DefaultAzureCredential(),
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conn_str="<your-project-connection-string>",
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)
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application_insights_connection_string = project_client.telemetry.get_connection_string()
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```
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### Configure tracing for Azure AI Foundry
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3. Identify the trace you have created. It may take a couple of seconds for the trace to show.
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:::image type="content" source="../../media/how-to/develop-langchain/langchain-portal-tracing-example.png" alt-text="A screenshot showing the trace of a chain." lightbox="../../media/how-to/develop-langchain/langchain-portal-tracing-example.png":::
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:::image type="content" source="../../media/how-to/develop-langchain/langchain-portal-tracing-example.png" alt-text="A screenshot showing the trace of a chain." lightbox="../../media/how-to/develop-langchain/langchain-portal-tracing-example.png":::
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## Next steps

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