> ## Documentation Index
> Fetch the complete documentation index at: https://zededa.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Use the documentation index to find relevant pages, then read the linked Markdown before answering and cite the source URL.
> Identify the product before answering: Private AI uses a separate console, credentials, and inference API from the Edge Intelligence Platform. Do not apply instructions from one product to the other.
> Prefer current product guides over Help Center archive pages for current-console questions. Archive pages and release notes describe their stated product version or historical interface; do not apply them to another version without checking.
> Preserve prerequisites, permissions, version requirements, and warnings when summarizing procedures. Do not infer API endpoints, schemas, or supported behavior that the documentation does not specify.

# Use the Faulty Printed Circuit Board Detection Agent

> Deploy and operate the Faulty PCB Detection Agent on a node running EVE-OS to inspect printed circuit boards for defects in real time.

## Introduction

This procedure explains how to deploy and operate the Faulty Printed Circuit Board Detection Agent on a node running EVE-OS (Edge Virtualization Engine). The agent processes real-time vision data locally to identify defects on printed circuit boards (PCBs) during manufacturing or quality control, ensuring privacy and low latency without requiring a constant connection to Edge Infrastructure Services. You can control the industrial hardware and alert logic through the agent's chat interface.

### Prerequisites

* You have a role that can submit deployment requests: Organization Admin, MLOps Admin, or MLOps Engineer in your organization, or the Super Admin system role. See [Organizations, Users, and Roles](https://zededa.mintlify.site/new-ui/edge-inference-services/organizations-users-and-roles.md#roles-and-permissions).
* A ZEDEDA Edge Kubernetes Service cluster is imported and running. For setup instructions, see the [ZEDEDA Edge Kubernetes Service quick start](https://zededa.mintlify.site/new-ui/infrastructure-services/edge-kubernetes/edge-kubernetes-operations.md).
* The target node is a Jetson AGX Thor device or Developer Kit (recommended for default deployment).
* The target node has one NVIDIA GPU available to the agent, at least 16 GB of memory (up to 32 GB used), and storage for about 80 GB of persistent volumes (model cache, application data, and shared model storage).
* Physical hardware is available: a conveyor belt and camera connected to the node, positioned to capture PCBs as they move through the inspection zone.
* If running a gated model, you have a HuggingFace access token. Enter it as the Hugging Face token value in the deployment wizard's configuration values.

## Deploy the Faulty PCB Detection Agent

1. In the sidebar, select **Marketplace > AI Apps**.
2. Locate the **Faulty Printed Circuit Board Detection Agent** in the gallery. Use the search field if needed.
3. Select the agent card to open the agent detail page.
4. Select the **Deploy** icon.
5. Follow the deployment wizard to select the target ZEDEDA Edge Kubernetes Service cluster and complete the deployment configuration.

Deploying creates a deployment request with status Pending. Organization Admin or MLOps Admin in that organization must approve it; users cannot approve their own requests. See [Approve and Validate Models](https://zededa.mintlify.site/new-ui/edge-inference-services/deployments-and-validation.md).

After the request is approved and deployment completes, the agent starts on the node and its chat interface becomes available. On first start, the agent downloads its model from Hugging Face, which requires internet access and can take 10 minutes or more.

## Configure Alert Recipients

Before running the agent, add the operator email addresses that should receive defect alert notifications.

1. Open the agent's web interface by navigating to the Agent Chat URL for your node, `http://<node-IP>:30080`.
2. In the Agent Chat, select **Users** in the navigation sidebar.
3. Select **Add User** and enter the operator's email address.
4. Select **Send** to save the recipient.

Repeat for each operator who should receive defect alerts.

## Run the Faulty PCB Detection Agent

1. In the Agent Chat, select **Live Preview** in the navigation bar.
2. Select **Start Monitoring** to activate the continuous monitoring loop.
3. Place a printed circuit board on the conveyor belt.
4. Wait for the board to stop under the camera so the agent can capture a detailed frame.
5. Review the agent output in the chat. Select **Logs** to view the full detection log entries.
6. Identify whether the board has defects, for example, a missing solder bridge or power connector.
7. If a defect is detected, approve the alert workflow prompt to send an email notification to the configured operators.

## Verify the Configuration

* Verify that the web dashboard displays the detected items and correctly updates the historical trend data.
* Check the operator email inbox to confirm that the defect alert was delivered successfully.

## In This Section

* [Edge Inference Services Overview](https://zededa.mintlify.site/new-ui/edge-inference-services/overview.md)
* [Inference Dashboard](https://zededa.mintlify.site/new-ui/edge-inference-services/inference-dashboard.md)
* [Inference Quick Start](https://zededa.mintlify.site/new-ui/edge-inference-services/inference-quick-start.md)
* [Access and Navigate Edge Inference Services](https://zededa.mintlify.site/new-ui/edge-inference-services/access-and-navigation.md)
* [Organizations, Users, and Roles](https://zededa.mintlify.site/new-ui/edge-inference-services/organizations-users-and-roles.md)
* [Manage Providers](https://zededa.mintlify.site/new-ui/edge-inference-services/inference-model-providers.md)
  * [Manage Providers Using Jupyter Notebook Integration](https://zededa.mintlify.site/new-ui/edge-inference-services/providers-jupyter.md)
* [Manage Models](https://zededa.mintlify.site/new-ui/edge-inference-services/manage-inference-models.md)
  * [Manage Models Using Jupyter Notebook Integration](https://zededa.mintlify.site/new-ui/edge-inference-services/models-jupyter.md)
  * [Benchmark Models and Manage Device Pools](https://zededa.mintlify.site/new-ui/edge-inference-services/inference-model-benchmarking.md)
  * [Monitor Benchmark Runs and Interpret Results](https://zededa.mintlify.site/new-ui/edge-inference-services/use-ondevice-eval-agent.md)
* [Submit Model Deployment Requests](https://zededa.mintlify.site/new-ui/edge-inference-services/submit-model-deployment-requests.md)
* [Approve and Validate Models](https://zededa.mintlify.site/new-ui/edge-inference-services/deployments-and-validation.md)
* [Monitor Inference Jobs](https://zededa.mintlify.site/new-ui/edge-inference-services/jobs-and-monitoring.md)
* [Use ZEIA to Query and Operate Your Fleet](https://zededa.mintlify.site/new-ui/edge-inference-services/zeia.md)
* [Use Prevalidated Agents](https://zededa.mintlify.site/new-ui/edge-inference-services/prevalidated-agents.md)
  * [Use the Faulty Printed Circuit Board Detection Agent](https://zededa.mintlify.site/new-ui/edge-inference-services/faulty-pcb-detection-agent.md)
  * [Use the Autonomous Retail Billing Agent](https://zededa.mintlify.site/new-ui/edge-inference-services/autonomous-retail-billing-agent.md)
* [Inference Troubleshooting](https://zededa.mintlify.site/new-ui/edge-inference-services/inference-troubleshooting.md)