roboflow integration

Author: Tom Gotsman

assets/ai_builder/integrations/roboflow.webp

@@ -0,0 +1,73 @@
+---
+tags: AI
+description: Connect your apps to Roboflow to use computer vision models and datasets for image detection, classification, and segmentation.
+---
+# Roboflow Integration
+
+The **Roboflow Integration** allows your app to use [Roboflow](https://roboflow.com/) to run and deploy computer vision models without complex infrastructure. Once connected, you can use Roboflow to power image detection, object tracking, classification, and segmentation workflows.
+
+## What You Can Do
+
+With Roboflow, your app can:
+- Run **pre-trained computer vision models** for detection, classification, or segmentation.  
+- Deploy and use **custom-trained models** built in Roboflow.  
+- Automate workflows that rely on visual inputs — e.g., quality checks, object detection, image analysis.  
+- Ingest and process **images in real time**.  
+- Combine vision outputs with other integrations (e.g., AI reasoning, automation flows).
+
+```md alert
+## This integration currently supports image inputs only.
+Video and streaming inputs are not yet supported.
+```
+
+## Step 1: Obtain a Roboflow API Key
+
+1. Go to your [Roboflow Account](https://roboflow.com/).
+2. Navigate to **Settings → API Keys**.  
+3. Copy your Private API Key.
+
+   * **Example:** `YWpnxxxxxxxxxxx`
+
+
+## Step 2: Set up your Model in Roboflow
+
+1. Go to Workflows and create a new workflow.
+2. Set up the workflow you want to use in your app, ensuring that is takes an image as input.
+3. Click the `deploy` button, select `Images` and then select `Integrate with my app or website`.
+4. Copy the `workspace_name` and `workflow_id` from the provided code snippet.
+
+```python exec
+import reflex as rx
+from reflex_image_zoom import image_zoom
+```
+
+```python eval
+rx.el.div(
+    image_zoom(
+        rx.image(
+            src="/ai_builder/integrations/roboflow.webp",
+            class_name="p-2 rounded-md h-auto",
+            border=f"0.81px solid {rx.color('slate', 5)}",
+        ),
+        class_name="rounded-md overflow-hidden",
+    ),
+    class_name="w-full flex flex-col rounded-md cursor-pointer",
+)
+```
+
+
+## Step 3: Configure the Integration in Your App
+
+1. Go to **Integrations → Add Roboflow** in your app settings.  
+2. Paste your **Roboflow API Key**, **Workspace Name**, and **Workflow ID** in the input fields.  
+3. Click **Connect** to validate and save your integration.
+
+Once connected, your app can call Roboflow models directly from workflows, UI actions, or automated triggers.
+
+
+## Step 4: Notes
+
+* **Keep your key secure:** Never expose your Roboflow key in client-side code.  
+* **Use environment-specific keys:** Separate dev, staging, and production keys to control access.  
+* **Model flexibility:** Use community models or your own custom-trained models.  
+* **Real-time vision:** Ideal for applications involving cameras, inspection, monitoring, or visual AI.