---
title: Observability and Tracing for Ragflow
sidebarTitle: Ragflow
logo: /images/integrations/ragflow_icon.svg
description: Open source observability for Ragflow applications. Automatically capture detailed traces and metrics for every request built with Ragflow.
category: integrations
---

# Ragflow Observability & Tracing

**[Ragflow](https://ragflow.io/)** ([GitHub](https://github.com/infiniflow/ragflow)) is a no-code / low-code framework to design and run Retrieval-Augmented-Generation (RAG) pipelines.

With the native Langfuse integration you can build complex RAG pipelines in Ragflow and then use Langfuse to monitor, debug and improve them.

The integration works for all execution modes of Ragflow: interactive runs in the UI, scheduled jobs and API calls.

## Integration

<Steps>

### Get Langfuse API keys

<Tabs items={["Langfuse cloud", "local or self-hosted"]}>
<Tab>

1. Create an account and project on [cloud.langfuse.com](https://cloud.langfuse.com/auth/sign-up)
2. Copy the **public** and **secret** API keys for your project

</Tab>
<Tab>

1. Follow the [self-hosting guide](/docs/get-started/) to run Langfuse locally or on-prem
2. Copy the **public** and **secret** API keys for your project

</Tab>
</Tabs>

### Configure Ragflow

You can configure Langfuse in the Ragflow API settings (scroll to bottom). Please note that you first have to configure an LLM in the Ragflow settings.

### Run your pipeline and inspect traces

Execute a pipeline from the Ragflow UI or trigger it via the API. Ragflow will automatically send structured trace data to Langfuse.

  ![Example Ragflow trace in
  Langfuse](/images/docs/ragflow/ragflow-example-trace.png)

([Example trace in Langfuse](https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/0bde9629-4251-4386-b583-26101b8e7561?timestamp=2025-05-09T19%3A15%3A37.797Z&display=details&observation=823997d8-ac40-40f3-8e7b-8aa6753b499e))

</Steps>

## Version requirements

| Library | Minimum version |
| ------- | --------------- |
| Ragflow | `>= 0.3.0`      |

If you are on an older Ragflow version please upgrade to benefit from the Langfuse integration.

<!-- 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/ragflow.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>.