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Update Graphsignal ecosystem page (#2662)

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Added/updated information due to new automatic data recording feature.
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Dmitri Melikyan 2023-04-10 17:00:26 +02:00 committed by GitHub
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docs/ecosystem/graphsignal.md
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# Graphsignal
This page covers how to use the Graphsignal ecosystem to trace and monitor LangChain.
This page covers how to use [Graphsignal](https://app.graphsignal.com) to trace and monitor LangChain. Graphsignal enables full visibility into your application. It provides latency breakdowns by chains and tools, exceptions with full context, data monitoring, compute/GPU utilization, OpenAI cost analytics, and more.
## Installation and Setup
@ -10,7 +10,7 @@ This page covers how to use the Graphsignal ecosystem to trace and monitor LangC
## Tracing and Monitoring
Graphsignal automatically instruments and starts tracing and monitoring chains. Traces, metrics and errors are then available in your [Graphsignal dashboard](https://app.graphsignal.com/). No prompts or other sensitive data are sent to Graphsignal cloud, only statistics and metadata.
Graphsignal automatically instruments and starts tracing and monitoring chains. Traces and metrics are then available in your [Graphsignal dashboards](https://app.graphsignal.com).
Initialize the tracer by providing a deployment name:
@ -20,7 +20,13 @@ import graphsignal
graphsignal.configure(deployment='my-langchain-app-prod')
```
In order to trace full runs and see a breakdown by chains and tools, you can wrap the calling routine or use a decorator:
To additionally trace any function or code, you can use a decorator or a context manager:
```python
@graphsignal.trace_function
def handle_request():
chain.run("some initial text")
```
```python
with graphsignal.start_trace('my-chain'):