# Deploy - [Deploy a Model or Workflow](https://docs.roboflow.com/deploy/deployment-overview.md): Learn how to deploy workflows and models trained on or uploaded to Roboflow. - [Supported Models](https://docs.roboflow.com/deploy/supported-models.md): All models you can deploy with Roboflow. - [SAM3](https://docs.roboflow.com/deploy/supported-models/sam3.md): Use Meta's SAM3 model through our Serverless Hosted API - [Serverless Hosted API](https://docs.roboflow.com/deploy/serverless-hosted-api-v2.md): Run Workflows and Model Inference on GPU-accelerated auto-scaling infrastructure in the Roboflow cloud. - [Use in a Workflow](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/use-in-a-workflow.md): You can use Serverless Hosted API with Roboflow Workflows. - [Use with the REST API](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/use-with-the-rest-api.md) - [Use with Python SDK](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/use-with-python-sdk.md): Use Roboflow's Serverless Hosted API with Python SDK - [Pricing](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/pricing.md): Serverless Hosted API Pricing page - [Serverless Video Streaming API](https://docs.roboflow.com/deploy/serverless-video-streaming-api.md): Run Roboflow Workflows on live video in the Roboflow Cloud. Stream input from webcams, RTSP cameras, or video files via WebRTC and receive inference results back in your application. - [Batch Processing](https://docs.roboflow.com/deploy/batch-processing.md) - [API Reference](https://docs.roboflow.com/deploy/batch-processing/api-reference.md): REST API reference for Batch Processing endpoints. - [CLI Usage](https://docs.roboflow.com/deploy/batch-processing/cli-usage.md): Use the Roboflow CLI to create and manage Batch Processing jobs. - [Troubleshooting](https://docs.roboflow.com/deploy/batch-processing/troubleshooting.md): Troubleshoot common Batch Processing issues including timeouts, SAHI performance, and OOM errors. - [Dedicated Deployments](https://docs.roboflow.com/deploy/dedicated-deployments.md): Run Your Vision Models on Dedicated Servers with Roboflow - [Create a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/create-a-dedicated-deployment.md): You can create a Dedicated Deployment in the Roboflow web interface, or in the CLI. - [Pause and Resume a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/pause-and-resume-a-dedicated-deployment.md) - [Delete a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/delete-a-dedicated-deployment.md) - [Make Requests to a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/make-requests-to-a-dedicated-deployment.md): You can make requests to a Dedicated Deployment directly with the Python SDK, using a HTTP API, or using the Workflows web interface. - [Manage Dedicated Deployments with an API](https://docs.roboflow.com/deploy/dedicated-deployments/manage-dedicated-deployments-with-an-api.md): Manage your dedicated deployment using our HTTP APIs. - [Self-Hosted Deployment](https://docs.roboflow.com/deploy/self-hosted-deployment.md): You can run Roboflow models and Workflows on your own hardware. - [Other SDKs](https://docs.roboflow.com/deploy/sdks.md) - [Python inference-sdk](https://docs.roboflow.com/deploy/sdks/python-inference-sdk.md): Information about inference-sk - [Web Browser](https://docs.roboflow.com/deploy/sdks/web-browser.md) - [Web inference.js](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference.js.md): Run realtime predictions at the edge, on the browser, with inference.js - [inferencejs Reference](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference.js/inferencejs-reference.md): Reference for \`inferencejs\`, an edge library for deploying computer vision applications built with Roboflow to web/JavaScript environments - [inferencejs Requirements](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference.js/inferencejs-requirements.md): Requirements for running \`inferencejs\` - [Web inference-sdk](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference-sdk.md): Run realtime video inference from your browser, running on the Roboflow cloud, with inference-sdk - [Lens Studio](https://docs.roboflow.com/deploy/sdks/lens-studio.md): Deploy a model to Lens Studio for use in building a Snap Lens. - [Changelog - Lens Studio](https://docs.roboflow.com/deploy/sdks/lens-studio/changelog-lens-studio.md): A list of public facing changes for the Lens Studio integration - [Luxonis OAK](https://docs.roboflow.com/deploy/sdks/luxonis-oak.md): Deploy your Roboflow Train model to your OpenCV AI Kit with Myriad X VPU acceleration. - [OpenMV](https://docs.roboflow.com/deploy/sdks/openmv.md): Deploy computer vision models to extremely low power edge cameras. - [iOS SDK](https://docs.roboflow.com/deploy/sdks/ios-sdk.md): Deploy your trained Roboflow model in your iOS app - [Upload Custom Model Weights](https://docs.roboflow.com/deploy/upload-custom-weights.md): Roboflow offers the ability to upload model weights for your custom-trained models to your Roboflow projects for model deployment. - [Download Model Weights](https://docs.roboflow.com/deploy/download-roboflow-model-weights.md): To run your Roboflow models on your own hardware, you can either use Roboflow Inference (the recommended, automatic method) or manually download Model Weights (for specific edge cases). - [Enterprise Deployment](https://docs.roboflow.com/deploy/enterprise-deployment.md) - [License Server](https://docs.roboflow.com/deploy/enterprise-deployment/license-server.md): You can use the Roboflow License server to proxy the necessary routes for Roboflow Deployment servers into your company's DMZ - [Offline Mode](https://docs.roboflow.com/deploy/enterprise-deployment/offline-mode.md): Roboflow Enterprise customers can deploy models offline. - [Kubernetes](https://docs.roboflow.com/deploy/enterprise-deployment/kubernetes.md): Getting started with Roboflow Inference on Kubernetes - [Docker Compose](https://docs.roboflow.com/deploy/enterprise-deployment/docker-compose.md): Run the Roboflow inference server alongside other docker containers to build your multi-container application via Docker Compose. - [Deployment Manager](https://docs.roboflow.com/deploy/device-manager.md): Manage and monitor computer vision models deployed on edge hardware. - [Setting Up](https://docs.roboflow.com/deploy/device-manager/setting-up.md) - [Hardware Requirements](https://docs.roboflow.com/deploy/device-manager/setting-up/hardware-requirements.md) - [Add a Device](https://docs.roboflow.com/deploy/device-manager/setting-up/add-a-device.md): Set up a device with everything you need to deploy a Workflow using Deployment Manager. - [Add a Stream](https://docs.roboflow.com/deploy/device-manager/setting-up/add-a-stream.md): Learn how to configure a stream that you can use to run a Workflow. - [Setup Maintenance Windows](https://docs.roboflow.com/deploy/device-manager/setting-up/setup-maintenance-windows.md) - [Set up Device Alerts](https://docs.roboflow.com/deploy/device-manager/setting-up/set-up-device-alerts.md) - [Monitoring](https://docs.roboflow.com/deploy/device-manager/monitoring.md) - [View a Stream](https://docs.roboflow.com/deploy/device-manager/monitoring/view-a-stream.md): Learn how to view a Stream configured with Deployment Manager. - [View Device Logs](https://docs.roboflow.com/deploy/device-manager/monitoring/view-device-logs.md) - [View the Resource Monitor](https://docs.roboflow.com/deploy/device-manager/monitoring/view-the-resource-monitor.md) - [Making Changes](https://docs.roboflow.com/deploy/device-manager/making-changes.md) - [Update Device Configuration](https://docs.roboflow.com/deploy/device-manager/making-changes/update-device-configuration.md) - [Redeploy Deployment Manager](https://docs.roboflow.com/deploy/device-manager/making-changes/redeploy-deployment-manager.md) - [API Keys for Device Manager](https://docs.roboflow.com/deploy/device-manager/making-changes/api-keys-for-device-manager.md) - [Terminate a Stream](https://docs.roboflow.com/deploy/device-manager/making-changes/delete-a-stream.md) - [Pause and Resume a Stream](https://docs.roboflow.com/deploy/device-manager/making-changes/stop-a-stream.md) - [Delete a Device](https://docs.roboflow.com/deploy/device-manager/making-changes/delete-a-device.md) - [Model Monitoring](https://docs.roboflow.com/deploy/model-monitoring.md): A guide to Model Monitoring with Roboflow. - [Alerting](https://docs.roboflow.com/deploy/model-monitoring/alerting.md) - [Vision Events](https://docs.roboflow.com/deploy/vision-events.md): Record, search, and analyze what your deployed computer vision models see in production. - [Use Cases](https://docs.roboflow.com/deploy/vision-events/use-cases.md): Group Vision Events by purpose using Use Cases. - [Send Events](https://docs.roboflow.com/deploy/vision-events/send-events.md): Three ways to send Vision Events from your deployed models. - [Query Events](https://docs.roboflow.com/deploy/vision-events/query-events.md): Search, filter, and browse Vision Events in the dashboard and via the API - [Delete Events](https://docs.roboflow.com/deploy/vision-events/delete-events.md): Remove Vision Events from a Use Case through the dashboard or the API. - [Operator Feedback](https://docs.roboflow.com/deploy/vision-events/operator-feedback.md): Let operators review Vision Events and mark them as correct, incorrect, or inconclusive. - [Add Images for Training](https://docs.roboflow.com/deploy/vision-events/add-images-for-training.md): Send images from Vision Events into a Roboflow project for training. --- # Agent Instructions: 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: ``` GET https://docs.roboflow.com/deploy.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.