mirror of
https://github.com/hwchase17/langchain
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45 lines
1.5 KiB
Markdown
45 lines
1.5 KiB
Markdown
# Graphsignal
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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.
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## Installation and Setup
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- Install the Python library with `pip install graphsignal`
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- Create free Graphsignal account [here](https://graphsignal.com)
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- Get an API key and set it as an environment variable (`GRAPHSIGNAL_API_KEY`)
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## Tracing and Monitoring
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Graphsignal automatically instruments and starts tracing and monitoring chains. Traces and metrics are then available in your [Graphsignal dashboards](https://app.graphsignal.com).
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Initialize the tracer by providing a deployment name:
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```python
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import graphsignal
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graphsignal.configure(deployment='my-langchain-app-prod')
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```
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To additionally trace any function or code, you can use a decorator or a context manager:
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```python
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@graphsignal.trace_function
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def handle_request():
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chain.run("some initial text")
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```
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```python
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with graphsignal.start_trace('my-chain'):
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chain.run("some initial text")
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```
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Optionally, enable profiling to record function-level statistics for each trace.
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```python
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with graphsignal.start_trace(
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'my-chain', options=graphsignal.TraceOptions(enable_profiling=True)):
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chain.run("some initial text")
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```
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See the [Quick Start](https://graphsignal.com/docs/guides/quick-start/) guide for complete setup instructions.
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