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tutorials/ai-core-deploy/ai-core-deploy.md

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@@ -17,9 +17,9 @@ If you are an SAP Developer or SAP employee, please refer to the following links
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[How to create a BTP Account (internal)](https://me.sap.com/notes/3493139)
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[SAP AI Core](https://help.sap.com/docs/sap-ai-core?version=INTERNAL&locale=en-US&state=PRODUCTION)
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If you are an external developer or a customer or a partner kindly refer to this [tutorial](https://developers.sap.com/tutorials/btp-cockpit-entitlements.html)
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- You have connected code to the AI workflows of SAP AI Core using [this tutorial](ai-core-code).
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- You have trained a model using SAP AI Core, such as the house price predictor model in [this tutorial](ai-core-data), or your own model trained in your local system. If you trained your own local model, follow [this tutorial](ai-core-tensorflow-byod) to use it with SAP AI Core.
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- You know how to locate artifacts. This is explained in [this tutorial](ai-core-data).
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- You have connected code to the AI workflows of SAP AI Core using [this tutorial](ai-core-code).
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- You have trained a model using SAP AI Core, such as the house price predictor model in [this tutorial](ai-core-data), or your own model trained in your local system. If you trained your own local model, follow [this tutorial](ai-core-tensorflow-byod) to use it with SAP AI Core.
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- You know how to locate artifacts. This is explained in [this tutorial](ai-core-data).
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## You will learn
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- How to create deployment server an for AI model
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The deployment server demonstrated in this tutorial can only be used in the backend of your AI project. For security reasons, in your real set up you will not be able to directly make prediction calls from your front end application to the deployment server. Doing so will lead to an inevitable Cross-origin Resource Sharing (CORS) error. As a temporary resolution, please deploy another application between your front end application and this deployment server. This middle application should use the SAP AI Core SDK (python package) to make calls to the deployment server.
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Please find downloadable sample notebooks for the tutorials : . Note that these tutorials are for demonstration purposes only and should not be used in production environments. To execute them properly, you'll need to set up your own S3 bucket or provision services from BTP, including an AI Core with a standard plan for narrow AI and an extended plan for GenAI HUB. Ensure you input the service keys of these services into the relevant cells of the notebook.
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Please find downloadable sample notebooks for the tutorials : . Note that these tutorials are for demonstration purposes only and should not be used in production environments. To execute them properly, you'll need to set up your own S3 bucket or provision services from BTP, including an AI Core with a standard plan for narrow AI and an extended plan for Generative AI Hub. Ensure you input the service keys of these services into the relevant cells of the notebook.
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[Link to notebook](https://github.com/SAP-samples/ai-core-samples/blob/main/02_ai_core/tutorials/01_create_your_first_machine_learning_project_using_sap_ai_core/01_05_make_predictions_for_house_prices_with_sap_ai_core/make-prediction.ipynb)
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---
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```PYTHON
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response = ai_core_client.deployment.create(
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configuration_id="YOUR_CONFIGURATIO_ID",
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configuration_id="YOUR_CONFIGURATION_ID",
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resource_group='default'
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)
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### Check Running Resources (optional)
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You can check the Current running Pods Using in AI Lauchpad Choosing the Deployment and clicking on Scaling tab
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You can check the current running Pods Using in AI Launchpad, choosing the Deployment, and clicking on Scaling tab
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<!-- border -->![resource](img/ail/resource1.jpg)
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Similary if you want to check for resource plan just visit the resources tab
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Similarly if you want to check for resource plan just visit the resources tab
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<!-- border -->![resource](img/ail/resource2.jpg)

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