docs: Add Arize integration documentation to Langflow (#6876)

* docs: Add Arize integration documentation to Langflow

* Apply suggestions from code review

Co-authored-by: KimberlyFields <46325568+KimberlyFields@users.noreply.github.com>

---------

Co-authored-by: KimberlyFields <46325568+KimberlyFields@users.noreply.github.com>

docs/docs/Integrations/Arize/integrations-arize.md

@@ -0,0 +1,54 @@
+---
+title: Integrate Arize with Langflow
+slug: /integrations-arize
+---
+
+Arize is a tool built on [OpenTelemetry](https://opentelemetry.io/) and [OpenInference](https://docs.arize.com/phoenix/reference/open-inference) for monitoring and optimizing LLM applications.
+
+To add tracing to your Langflow application, add the `ARIZE_SPACE_ID` and `ARIZE_API_KEY` environment variables to your Langflow application.
+
+## Prerequisites
+
+* If you are using the [standard Arize platform](https://docs.arize.com/arize), you need an **Arize Space ID** and **API API Key**.
+* If you are using the open-source [Arize Phoenix platform](https://docs.arize.com/phoenix), you need an Arize Phoenix API key and a project name.
+
+## Connect Arize to Langflow
+
+1. To retrieve your **Arize Space ID** and **API API Key**, navigate to the [Arize dashboard](https://app.arize.com/).
+2. Click **Settings**, and then click **Space Settings and Keys**.
+3. Copy the **SpaceID** and **API Key (Ingestion Service Account Key)** values.
+4. Create a `.env` file in the root of your Langflow application.
+5. Add the `ARIZE_SPACE_ID` and `ARIZE_API_KEY` environment variables to your Langflow application.
+You do not need to specify the **Arize Project** name if you're using the standard Arize platform. The **Project** name in Arize is the same as the Langflow **Flow** name.
+
+```bash
+export ARIZE_SPACE_ID=<your-arize-space-id>
+export ARIZE_API_KEY=<your-arize-api-key>
+```
+
+6. Start your Langflow application with the values from the `.env` file.
+
+```bash
+uv run langflow run --env-file .env
+```
+
+## Run a flow and view metrics in Arize
+
+1. In Langflow, select the [Simple agent](/starter-projects-simple-agent) starter project.
+2. In the **Agent** component's **OpenAI API Key** field, paste your **OpenAI API key**.
+3. Click **Playground**.
+Ask your Agent some questions to generate traffic.
+4. Navigate to the [Arize dashboard](https://app.arize.com/), and then open your project.
+You may have to wait a few minutes for Arize to process the data.
+5. The **LLM Tracing** tab shows metrics for your flow.
+Each Langflow execution generates two traces in Arize.
+The `AgentExecutor` trace is the Arize trace of Langchain's `AgentExecutor`. The UUID trace is the trace of the Langflow components.
+6. To view traces, click the **Traces** tab.
+A **trace** is the complete journey of a request, made of multiple **spans**.
+7. To view **Spans**, select the **Spans** tab.
+A **span** is a single operation within a trace. For example, a **span** could be a single API call to OpenAI or a single function call to a custom tool.
+For more on traces, spans, and other metrics in Arize, see the [Arize documentation](https://docs.arize.com/arize/llm-tracing/tracing).
+8. All metrics in the **LLM Tracing** tab can be added to **Datasets**.
+To add a span to a **Dataset**, click the **Add to Dataset** button.
+9. To view a **Dataset**, click the **Datasets** tab, and then select your **Dataset**.
+For more on **Datasets**, see the [Arize documentation](https://docs.arize.com/arize/llm-datasets-and-experiments/datasets-and-experiments).

docs/sidebars.js

@@ -141,6 +141,7 @@ module.exports = {
       label: "Integrations",
       items: [
         "Integrations/Apify/integrations-apify",
+        "Integrations/Arize/integrations-arize",
         "Integrations/integrations-assemblyai",
         "Integrations/Composio/integrations-composio",
         "Integrations/integrations-langfuse",