forked from phoenix/litellm-mirror
36 lines
1.7 KiB
Markdown
36 lines
1.7 KiB
Markdown
import Image from '@theme/IdealImage';
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# Traceloop (OpenLLMetry) - Tracing LLMs with OpenTelemetry
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[Traceloop](https://traceloop.com) is a platform for monitoring and debugging the quality of your LLM outputs.
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It provides you with a way to track the performance of your LLM application; rollout changes with confidence; and debug issues in production.
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It is based on [OpenTelemetry](https://opentelemetry.io), so it can provide full visibility to your LLM requests, as well vector DB usage, and other infra in your stack.
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<Image img={require('../../img/traceloop_dash.png')} />
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## Getting Started
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Install the Traceloop SDK:
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```
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pip install traceloop-sdk
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```
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Use just 2 lines of code, to instantly log your LLM responses with OpenTelemetry:
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```python
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Traceloop.init(app_name=<YOUR APP NAME>, disable_batch=True)
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litellm.success_callback = ["traceloop"]
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```
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Make sure to properly set a destination to your traces. See [OpenLLMetry docs](https://www.traceloop.com/docs/openllmetry/integrations/introduction) for options.
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To get better visualizations on how your code behaves, you may want to annotate specific parts of your LLM chain. See [Traceloop docs on decorators](https://traceloop.com/docs/python-sdk/decorators) for more information.
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## Exporting traces to other systems (e.g. Datadog, New Relic, and others)
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Since OpenLLMetry uses OpenTelemetry to send data, you can easily export your traces to other systems, such as Datadog, New Relic, and others. See [OpenLLMetry docs on exporters](https://www.traceloop.com/docs/openllmetry/integrations/introduction) for more information.
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## Support
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For any question or issue with integration you can reach out to the Traceloop team on [Slack](https://traceloop.com/slack) or via [email](mailto:dev@traceloop.com).
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