> For the complete documentation index, see [llms.txt](https://docs.apica.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.apica.io/observe/ai-evaluation-forwarders/langfuse-ai-evaluation-engine.md).

# Langfuse - AI Evaluation Engine

To use Langfuse as a downstream AI Evaluation Engine for data processed by Apica Flow, you leverage Langfuse's native OpenTelemetry (OTLP) ingestion capabilities.

Apica Flow acts as the "Observability Pipeline"—scrubbing PII, calculating costs, and normalizing data—before "forking" a high-fidelity copy of the AI traces to Langfuse for evaluation (LLM-as-a-judge, scoring, and versioning).

#### 1. Prerequisites in Langfuse

Before configuring the forwarder in Apica, generate your credentials in the Langfuse dashboard:

1. Navigate to Settings > API Keys.
2. Create a new set of keys and copy the Public Key, Secret Key, and Host URL.
3. Generate the Auth String: Langfuse uses Basic Authentication. You must encode your keys as a Base64 string in the format `pk-lf-xxx:sk-lf-xxx`.

   > Command: `echo -n "your-public-key:your-secret-key" | base64`

#### 2. Configuration Strategy: The Forwarder

In the Apica Flow (Ascent) UI, you will create a new Export Destination using the OTLP/HTTP protocol.

| **Configuration Field** | **Required Value**                                              |
| ----------------------- | --------------------------------------------------------------- |
| Destination Name        | `Langfuse_Evaluation_Engine`                                    |
| Endpoint                | `https://cloud.langfuse.com/api/public/otel/v1/traces`          |
| Protocol                | `http/protobuf` (Note: Langfuse does not support gRPC for OTel) |
| Auth Header Key         | `Authorization`                                                 |
| Auth Header Value       | `Basic <Your-Base64-Encoded-Auth-String>`                       |

#### 3. Detailed Reference: Metadata Mapping (OTTL)

Langfuse maps standard OTel GenAI attributes automatically. However, to unlock advanced Langfuse features (like grouping by User ID or Session), you should map these specific attributes in your Apica Flow pipeline:

SQL

```
# 1. Map Langfuse-specific attributes
set(attributes["langfuse.user.id"], attributes["enduser.id"])
set(attributes["langfuse.session.id"], attributes["session.id"])
set(attributes["langfuse.tags"], ["production", "apica-forwarded"])

# 2. Ensure GenAI Semantic Conventions are intact
# Langfuse requires these to identify "Generations" (LLM calls)
set(attributes["gen_ai.request.model"], attributes["model_name"])
set(attributes["gen_ai.usage.total_tokens"], attributes["total_tokens"])
```

#### 4. Implementation: The Dual-Sink Flow

The power of this setup is that Apica Flow allows you to send data to multiple "Sinks" simultaneously.

* Sink 1 (Security/SIEM): Receives redacted, low-volume security events.
* Sink 2 (Langfuse): Receives 100% of the raw (or semi-scrubbed) AI traces for evaluation and quality monitoring.

#### 5. Key Implementation Notes

* Batching: Langfuse is optimized for batch ingestion. Ensure the `batch` processor in Apica Flow is enabled with a `timeout` of at least `5s` to minimize the number of HTTP requests to the Langfuse API.
* Region-Specific Endpoints: \* EU: `https://cloud.langfuse.com/api/public/otel/v1/traces`
  * US: `https://us.cloud.langfuse.com/api/public/otel/v1/traces`
* Trace Visibility: Data forwarded via OTLP may take 1–3 minutes to appear in the Langfuse UI as it passes through their internal processing queues.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.apica.io/observe/ai-evaluation-forwarders/langfuse-ai-evaluation-engine.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.