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59 lines
2.3 KiB
Markdown
59 lines
2.3 KiB
Markdown
---
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sidebar_position: 6
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title: "Monitoring with Langfuse"
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---
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:::warning
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Bundled LiteLLM support has been deprecated from 0.2.0
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:::
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# Monitoring with Langfuse
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Integrating [Langfuse](https://cloud.langfuse.com) with LiteLLM allows for detailed observation and recording of API calls.
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This guide walks you through setting up Langfuse callbacks with LiteLLM.
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The local deployment of Langfuse is an option available through their open-source alternative. However, for the convenience of this tutorial, we will utilize the free limited version of their Cloud service. If data privacy is a concern for you, it is recommended to install the local version instead.
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## Getting Started with Langfuse
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Begin by setting up your Langfuse account and acquiring necessary keys:
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1. Create an account at [Langfuse](https://cloud.langfuse.com/auth/sign-up).
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2. Generate and copy your public and private keys.
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## Configuring OpenWebUI LiteLLM Proxy for Langfuse
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To integrate Langfuse with LiteLLM, you'll need to modify the LiteLLM `config.yaml` file and set environment variables for your Docker container.
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### Editing the LiteLLM Configuration File
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Edit the LiteLLM `config.yaml` file, located in your host Docker mount point at `/data/litellm/config.yaml`.
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Add the following under the general settings as shown in the [LiteLLM official documentation](https://litellm.vercel.app/docs/observability/langfuse_integration):
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```yaml
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general_settings: {}
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litellm_settings:
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success_callback: ["langfuse"]
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failure_callback: ["langfuse"]
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```
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### Setting Environment Variables in Docker
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When launching the Docker container, pass the Langfuse API keys as environment variables:
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```bash
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LANGFUSE_PUBLIC_KEY: Replace "xxxxx" with your actual public key.
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LANGFUSE_SECRET_KEY: Replace "xxxxx" with your actual secret key.
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These variables can be set directly in the docker run command or through a Docker Compose YAML file.
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```
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## Testing the Integration
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Once setup is complete, your Langfuse dashboard should start recording every API call made through the LiteLLM integration. This allows for efficient monitoring and troubleshooting of API interactions.
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## Note
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Ensure that all configurations are correctly set, and environment variables are properly passed to avoid integration issues.
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