docs: add langfuse documentation (#7568)

### What problem does this PR solve?

As RAGFlow has an integration with Langfuse, this docs page shows how to
configure Langfuse tracing.

### Type of change

- [ ] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):

docs/guides/tracing.mdx

+---
+sidebar_position: 9
+slug: /tracing
+---
+
+# Observability & Tracing with Langfuse
+
+RAGFlow ships with a built-in [Langfuse](https://langfuse.com) integration so that you can **inspect and debug every retrieval and generation step** of your RAG pipelines in near real-time.
+
+Langfuse stores traces, spans and prompt payloads in a purpose-built observability backend and offers filtering and visualisations on top.  
+
+:::info NOTE
+• RAGFlow **≥ 0.18.0** (contains the Langfuse connector)  
+• A Langfuse workspace (cloud or self-hosted) with a _Project Public Key_ and _Secret Key_
+:::
+
+---
+
+## 1. Collect your Langfuse credentials
+
+1. Sign in to your Langfuse dashboard.  
+2. Open **Settings ▸ Projects** and either create a new project or select an existing one.  
+3. Copy the **Public Key** and **Secret Key**.  
+4. Note the Langfuse **host** (e.g. `https://cloud.langfuse.com`). Use the base URL of your own installation if you self-host.
+
+> The keys are _project-scoped_: one pair of keys is enough for all environments that should write into the same project.
+
+---
+
+## 2. Add the keys to RAGFlow
+
+RAGFlow stores the credentials _per tenant_. You can configure them either via the web UI or the HTTP API.
+
+1. Log in to RAGFlow and click your avatar in the top-right corner.  
+2. Select **API ▸ Scroll down to the bottom ▸ Langfuse Configuration**.  
+3. Fill in you Langfuse **Host**, **Public Key** and **Secret Key**.  
+4. Click **Save**. 
+
+![Example Ragflow trace in Langfuse](https://langfuse.com/images/docs/ragflow/ragflow-configuration.gif)
+
+Once saved, RAGFlow starts emitting traces automatically – no code change required.
+
+---
+
+## 3. Run a pipeline and watch the traces
+
+1. Execute any chat or retrieval pipeline in RAGFlow (e.g. the Quickstart demo).  
+2. Open your Langfuse project ▸ **Traces**.  
+3. Filter by **name ~ `ragflow-*`** (RAGFlow prefixes each trace with `ragflow-`).
+
+For every user request you will see:
+
+• a **trace** representing the overall request  
+• **spans** for retrieval, ranking and generation steps  
+• the complete **prompts**, **retrieved documents** and **LLM responses** as metadata
+
+![Example Ragflow trace in Langfuse](https://langfuse.com/images/docs/ragflow/ragflow-trace-frame.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))
+
+:::tip NOTE
+Use Langfuse's diff view to compare prompt versions or drill down into long-running retrievals to identify bottlenecks.
+:::
+