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Python: docs(observability): add Langfuse example #1544
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@@ -254,6 +254,44 @@ ENABLE_OTEL=true OTLP_ENDPOINT=http://localhost:4317 python 01-zero_code.py | |
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| Once your sample finishes running, navigate to <http://localhost:18888> in a web browser to see the telemetry data. Follow the [Aspire Dashboard exploration guide](https://learn.microsoft.com/en-us/dotnet/aspire/fundamentals/dashboard/explore) to authenticate to the dashboard and start exploring your traces, logs, and metrics! | ||
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| ## Langfuse Dashboard | ||
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| [Langfuse](https://langfuse.com/) is an open-source LLM and AI agent observability tool. The Microsoft Agent Framework can export OpenTelemetry spans to Langfuse for evaluation and debugging. | ||
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| ### Configure Langfuse | ||
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| ```bash | ||
| pip install agent-framework langfuse | ||
| ``` | ||
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| Next, set your Langfuse credentials as environment variables. You can retrieve your Langfuse API keys by [self-hosting Langfuse](https://langfuse.com/self-hosting) or using [Langfuse Cloud](https://cloud.langfuse.com/). | ||
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| ```bash | ||
| LANGFUSE_PUBLIC_KEY=pk-lf-... | ||
| LANGFUSE_SECRET_KEY=sk-lf-... | ||
| LANGFUSE_HOST=https://cloud.langfuse.com | ||
| ``` | ||
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| Next, initialize the Langfuse client and enable observability in the Agent Framework: | ||
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| ```python | ||
| from agent_framework.observability import setup_observability | ||
| from langfuse import get_client | ||
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| langfuse = get_client() | ||
| setup_observability(enable_sensitive_data=True) | ||
| ``` | ||
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| For a complete integration guide, please take a look at the [Langfuse documentation](https://langfuse.com/integrations/frameworks/microsoft-agent-framework). | ||
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| ### See traces in Langfuse | ||
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| Now, all agent executions can be viewed in the Langfuse UI: | ||
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|  | ||
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Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. this link no longer works @jannikmaierhoefer |
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| [Example Trace in Langfuse](https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/232de211-7fcf-45c8-b415-6af0e8cd6eaa) | ||
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| ## Console output | ||
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| You won't have to deploy an Application Insights resource or install Docker to run Aspire Dashboard if you choose to inspect telemetry data in a console. However, it is difficult to navigate through all the spans and logs produced, so **this method is only recommended when you are just getting started**. | ||
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Some explanation on how agent framework connects to langfuse will be helpful.