---
title: Observability and Tracing for LobeChat
description: "Monitor and trace your LobeChat conversations with Langfuse. Capture detailed traces, costs, and usage patterns for your open-source LLM chat platform."
sidebarTitle: LobeChat
logo: /images/integrations/lobechat_icon.png
---

# Langfuse Integration with LobeChat

## What is LobeChat?

[LobeChat](https://lobehub.com/) is an **[open-source](https://github.com/lobehub/lobe-chat) LLM chat platform** that seamlessly integrates with various AI models and tools, providing users with an intuitive interface to interact with advanced language technologies.

## What is Langfuse?

[Langfuse](https://langfuse.com/) is one of the most used **open-source LLM Observability platforms**. By enabling the Langfuse integration, you can trace your application data with Langfuse to develop, monitor, and improve the use of LobeChat, including:

- Application [traces](/docs/observability/overview)
- Usage patterns
- Cost data by user and model
- [Evaluations](/docs/evaluation/overview)

## Get Started

<Steps>

### Set up Langfuse

Get your Langfuse API key by signing up for [Langfuse Cloud](https://cloud.langfuse.com) or [self-hosting](/self-hosting) Langfuse.

### Set up LobeChat

There are multiple ways to [self-host LobeChat](https://lobehub.com/docs/self-hosting/start). For this example, we will use the Docker Desktop deployment.

<Tabs items={["Environment Variables", "Example in Docker Desktop"]}>
<Tab>

Before deploying LobeChat, set the following four environment variables with the Langfuse API keys you created in the previous step.

```sh
ENABLE_LANGFUSE = '1'
LANGFUSE_SECRET_KEY = 'sk-lf...'
LANGFUSE_PUBLIC_KEY = 'pk-lf...'
LANGFUSE_HOST = 'https://cloud.langfuse.com'
```

</Tab>

<Tab>

Before running the Docker container, set the environment variables in the Docker Desktop with the Langfuse API keys you created in the previous step.

![Environment Variables in Docker Desktop](/images/docs/lobechat-docker-desktop-env.png)

</Tab>

</Tabs>

### Activate Analytics in Settings

Once you have LobeChat running, navigate to the **About** tab in the **Settings** and activate analytics. This is necessary for traces to be sent to Langfuse.

  ![LobeChat Settings](/images/docs/lobechat-settings.png)

### See your traces in Langfuse

After setting your LLM model key, you can start interacting with your LobeChat application.

  ![LobeChat Conversation](/images/docs/lobechat-converstation.png)

All conversations in the chat are automatically traced and sent to Langfuse. You can view the traces in the [Traces section](/docs/observability/overview) of the Langfuse platform.

  ![LobeChat Example Trace](/images/docs/lobechat-example-trace.png)

_[Example trace in the Langfuse UI](https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/63e9246d-3f22-4e45-936d-b0c4ccf55a1e?timestamp=2024-11-26T17%3A00%3A02.028Z&observation=7ea75a0c-d9d1-425c-9b88-27561c63b413)_

</Steps>

## Feedback

If you have any feedback or requests, please create a GitHub [Issue](/issue) or share your work with the community on [Discord](https://discord.langfuse.com/).

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/integrations/no-code/lobechat.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.