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83 lines
4.0 KiB
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83 lines
4.0 KiB
Markdown
---
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title: "Monitor your LLM requests with Helicone"
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sidebar_position: 19
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---
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:::warning
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This tutorial is a community contribution and is not supported by the Open WebUI team. It serves only as a demonstration on how to customize Open WebUI for your specific use case. Want to contribute? Check out the contributing tutorial.
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:::
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# Helicone Integration with Open WebUI
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Helicone is an open-source LLM observability platform for developers to monitor, debug, and improve **production-ready** applications, including your Open WebUI deployment.
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By enabling Helicone, you can log LLM requests, evaluate and experiment with prompts, and get instant insights that helps you push changes to production with confidence.
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- **Real-time monitoring with consolidated view across model types**: Monitor both local Ollama models and cloud APIs through a single interface
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- **Request visualization and replay**: See exactly what prompts were sent to each model in Open WebUI and the outputs generated by the LLMs for evaluation
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- **Local LLM performance tracking**: Measure response times and throughput of your self-hosted models
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- **Usage analytics by model**: Compare usage patterns between different models in your Open WebUI setup
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- **User analytics** to understand interaction patterns
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- **Debug capabilities** to troubleshoot issues with model responses
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- **Cost tracking** for your LLM usage across providers
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## How to integrate Helicone with OpenWebUI
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<iframe
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width="560"
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height="315"
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src="https://www.youtube-nocookie.com/embed/8iVHOkUrpSA?si=Jt1GVqA0wY4UI7sF"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</iframe>
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### Step 1: Create a Helicone account and generate your API key
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Create a [Helicone account](https://www.helicone.ai/) and log in to generate an [API key](https://us.helicone.ai/settings/api-keys).
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*— Make sure to generate a [write only API key](https://docs.helicone.ai/helicone-headers/helicone-auth). This ensures you only allow logging data to Helicone without read access to your private data.*
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### Step 2: Create an OpenAI account and generate your API key
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Create an OpenAI account and log into [OpenAI's Developer Portal](https://platform.openai.com/account/api-keys) to generate an API key.
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### Step 3: Run your Open WebUI application using Helicone's base URL
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To launch your first Open WebUI application, use the command from [Open WebUI docs](https://docs.openwebui.com/) and include Helicone's API BASE URL so you can query and monitor automatically.
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```bash
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# Set your environment variables
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export HELICONE_API_KEY=<YOUR_API_KEY>
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export OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
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# Run Open WebUI with Helicone integration
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docker run -d -p 3000:8080 \
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-e OPENAI_API_BASE_URL="https://oai.helicone.ai/v1/$HELICONE_API_KEY" \
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-e OPENAI_API_KEY="$OPENAI_API_KEY" \
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--name open-webui \
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ghcr.io/open-webui/open-webui
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```
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If you already have a Open WebUI application deployed, go to the `Admin Panel` > `Settings` > `Connections` and click on the `+` sign for "Managing OpenAI API Connections". Update the following properties:
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- Your `API Base URL` would be ``https://oai.helicone.ai/v1/<YOUR_HELICONE_API_KEY>``
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- The `API KEY` would be your OpenAI API key.
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### Step 4: Make sure monitoring is working
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To make sure your integration is working, log into Helicone's dashboard and review the "Requests" tab.
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You should see the requests you have made through your Open WebUI interface already being logged into Helicone.
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## Learn more
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For a comprehensive guide on Helicone, you can check out [Helicone's documentation](https://docs.helicone.ai/getting-started/quick-start).
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