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Python: docs(observability): add Langfuse example #1544

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38 changes: 38 additions & 0 deletions python/samples/getting_started/observability/README.md
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Expand Up @@ -240,6 +240,44 @@ ENABLE_OTEL=true OTLP_ENDPOINT=http://localhost:4317 python 01-zero_code.py

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!

## Langfuse Dashboard

[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.

### Configure Langfuse

```bash
pip install agent-framework langfuse
```

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/).

```bash
LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
LANGFUSE_HOST=https://cloud.langfuse.com
```

Next, initialize the Langfuse client and enable observability in the Agent Framework:

```python
from agent_framework.observability import setup_observability
from langfuse import get_client

langfuse = get_client()
setup_observability(enable_sensitive_data=True)
```

For a complete integration guide, please take a look at the [Langfuse documentation](https://langfuse.com/integrations/frameworks/microsoft-agent-framework).

### See traces in Langfuse

Now, all agent executions can be viewed in the Langfuse UI:

![Example trace in Langfuse](https://langfuse.com/images/cookbook/integration_microsoft-agent-framework/microsoft-agent-framework-example-race.png)

[Example Trace in Langfuse](https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/232de211-7fcf-45c8-b415-6af0e8cd6eaa)

## Console output

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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