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commit dbe64e75163ae89bc0aa515fcaf1e012593a22af Author: REDACTED Date: Mon Feb 3 11:36:40 2025 +0000 Update from SAP DITA CMS 2025-02-03 11:36:40 Project: dita-all/bex1621329160251 Project map: d3e749bbac3d4f728c12228db6629c45.ditamap Output: loiodaa66b2ef49f48539fa2882d82d5b619 Language: en-US Builddable map: f17fa8568d0448c685f2a0301061a6ee.ditamap commit df167c6c8f99f75710ac98d2740f8dbca4129fbd Author: REDACTED Date: Mon Feb 3 11:25:24 2025 +0000 Update from SAP DITA CMS 2025-02-03 11:25:24 Project: dita-all/ayn1620809929290 Project map: 8a3894192639433b9ba1f87efe78bfd1.ditamap Output: loio62559d01add8414eb0c4d76d2d9f48bd Language: en-US Builddable map: 038a6194f65c4ef68885f6f16360dbc4.ditamap commit 0335c4827478852e2b218e01d9a26bcd890cc8bb Author: REDACTED Date: Mon Feb 3 10:24:55 2025 +0000 Update from SAP DITA CMS 2025-02-03 10:24:55 Project: dita-all/ayn1620809929290 Project map: 8a3894192639433b9ba1f87efe78bfd1.ditamap ################################################## [Remaining squash message was removed before commit...]
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docs/sap-ai-core/consume-generative-ai-models-bf0373b.md

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<a name="concept_ynz_mgh_tzb__section_gqg_fxc_z1c"/>
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## Aleph Alpha
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<a name="concept_ynz_mgh_tzb__section_p3k_fxc_z1c"/>
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## Vertex AI

docs/sap-ai-core/consume-models-with-the-harmonized-api-2392d9a.md

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}
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},
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"llm_module_config": {
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"model_name": " gpt-35-turbo-16k ",
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"model_name": "gpt-4o-mini",
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"model_params": {
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"max_tokens": 50,
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"temperature": 0.1,
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}'
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```
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This request configures the templating module with a single user message with two parameters: `text` and `language`. The `language` parameter is also configured with English as the default. The LLM module is configured to use gpt-35-turbo-16k in the latest available version and a set of model parameters. The `input_params` field contains the values for the parameters `text` and `language`. These values are used during this request in the prompt sent to the model.
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This request configures the templating module with a single user message with two parameters: `text` and `language`. The `language` parameter is also configured with English as the default. The LLM module is configured to use gpt-4o-mini in the latest available version and a set of model parameters. The `input_params` field contains the values for the parameters `text` and `language`. These values are used during this request in the prompt sent to the model.
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The response contains a `request_id`, the module results from each module that was executed, and the `orchestration_result`, which includes the response of the call to the model.
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> "id": "chatcmpl-9k8M3djXphXPWh2QkQm1YVtXK4Eki",
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> "object": "chat.completion",
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> "created": 1720782231,
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> "model": " gpt-35-turbo-16k ",
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> "model": "gpt-4o-mini",
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> "choices": [
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> {
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> "index": 0,

docs/sap-ai-core/create-a-collection-9cbfe27.md

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You have created a resource group for grounding purposes. For more information, see [Create a Resource Group for Grounding](create-a-resource-group-for-grounding-6712bfe.md)
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You have created a generic secret for grounding purposes. For more information, see [Create a Generic Secret for Grounding](create-a-generic-secret-for-grounding-bdea357.md)
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You have created a generic secret for grounding purposes. For more information, see [Grounding Generic Secrets for Microsoft SharePoint](grounding-generic-secrets-for-microsoft-sharepoint-bdea357.md)
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docs/sap-ai-core/create-a-generic-secret-1831845.md

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Generic secrets are different to system secrets \(such as object store, Docker registry, and so on\) and can be used to store sensitive information, either for the main tenant, for all of its resource groups, or for each resource group via an API. The latter can be attached to containers in executions or deployments as environment variables or volume mounts.
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Tenant-wide secrets are only automatically propagated to the appropriate resource group when a new execution or deployment is created. They are not propagated to running deployments.
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> ### Note:
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> In order to allow rotation of tenant-wide secrets for long-running deployments without restarting the deployment, the following guidelines must be followed:
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>
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> - > The deployment must mount the tenant-wide secret. For more information see [Consume Generic Secrets in Executions or Deployments](https://help.sap.com/docs/AI_CORE/52b4adb30e6744709d6226d2b0659dea/185a3245692542a78bfeff87220410c6.html).
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> - > The deployment must monitor the mounted secret for changes instead of relying on an in-memory copy of the secret read from the mount.
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> - > When a tenant-wide secret is updated, the tenant is responsible for observing the `resourceGroupSecretReplicationStatus` field of the `Get Secret` endpoint, to ensure that the replicator has successfully updated the secret in the required resource groups. For more information, see [Create a Generic Secret](https://help.sap.com/docs/AI_CORE/52b4adb30e6744709d6226d2b0659dea/1831845910364e97b3a7c6644a9e1f4b.html).
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> ### Note:
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> Each tenant can have a maximum of five tenant-wide secrets. If you reach this limit, you'll receive an error message. To free up space, you can delete some tenant-wide secrets as described at [Delete a Generic Secret](delete-a-generic-secret-d5d5187.md). Alternatively, you can submit a ticket to request an increase your quota.
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> Each tenant can have a maximum of five tenant-wide secrets. If you reach this limit, you'll receive an error message. To free up space, you can delete some tenant-wide secrets as described at [Delete a Generic Secret](delete-a-generic-secret-d5d5187.md). Alternatively, you can submit a ticket to request an increase in your quota.
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Generic secrets are different to system secrets \(such as object store, Docker registry, and so on\) and can be used to store sensitive information, either for the main tenant, for all of its resource groups, or for each resource group via an API. The latter can be attached to containers in executions or deployments as environment variables or volume mounts.
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Tenant-wide secrets are only automatically propagated to the appropriate resource group when a new execution or deployment is created. They are not propagated to running deployments.
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> ### Note:
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> In order to allow rotation of tenant-wide secrets for long-running deployments without restarting the deployment, the following guidelines must be followed:
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>
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> - > The deployment must mount the tenant-wide secret. For more information see [Consume Generic Secrets in Executions or Deployments](https://help.sap.com/docs/AI_CORE/52b4adb30e6744709d6226d2b0659dea/185a3245692542a78bfeff87220410c6.html).
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> - > The deployment must monitor the mounted secret for changes instead of relying on an in-memory copy of the secret read from the mount.
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> - > When a tenant-wide secret is updated, the tenant is responsible for observing the `resourceGroupSecretReplicationStatus` field of the `Get Secret` endpoint, to ensure that the replicator has successfully updated the secret in the required resource groups. For more information, see [Create a Generic Secret](https://help.sap.com/docs/AI_CORE/52b4adb30e6744709d6226d2b0659dea/1831845910364e97b3a7c6644a9e1f4b.html).
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> ### Note:
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> Each tenant can have a maximum of five tenant-wide secrets. If you reach this limit, you'll receive an error message. To free up space, you can delete some tenant-wide secrets as described at [Delete a Generic Secret](delete-a-generic-secret-d5d5187.md). Alternatively, you can submit a ticket to request an increase your quota.
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> Each tenant can have a maximum of five tenant-wide secrets. If you reach this limit, you'll receive an error message. To free up space, you can delete some tenant-wide secrets as described at [Delete a Generic Secret](delete-a-generic-secret-d5d5187.md). Alternatively, you can submit a ticket to request an increase in your quota.
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docs/sap-ai-core/data-masking-8b87002.md

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There are two ways in which you can mask data:
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- Anonmyization replaces personally identifiable information in chosen categories with a `MASKED_ENTITY` placeholder. Anonymized data can't be unmasked because the original data isn't retained.
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- Anonymization replaces personally identifiable information in chosen categories with a `MASKED_ENTITY` placeholder. Anonymized data can't be unmasked because the original data isn't retained.
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International phone numbers in the following format: +country code, any prefix and phone number
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International phone numbers in the following format: +country/region code, any prefix and phone number
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UserID: Sequence of characters that starts with either C, I, or D followed by 6-8 digits.
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User ID: Sequence of characters that starts with either C, I, or D followed by 6-8 digits.
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> Anonymization replaces personally identifiable information in an irreversible way. As a result, context can be lost, which can limit the model's ability to process the input. For instance, if tasked with writing a story about Michael and Donna, anonymization of profile-person results in a story about `MASKED_PERSON` and `MASKED_PERSON`, making it impossible to distinguish between the two.
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- **[Enhancing Model Consumption with Data Masking](enhancing-model-consumption-with-data-masking-592c570.md "")**
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docs/sap-ai-core/delete-a-generic-secret-d5d5187.md

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# Delete a Generic Secret
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To get a secret name, see [List All Generic Secrets](list-all-generic-secrets-05a3713.md).
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To get a secret name, see [Get Generic Secrets](get-generic-secrets-05a3713.md).
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<!-- loiofbf4daea78e9409eb13c4b413345a2c9 -->
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# Generic Secrets for Grounding
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- **[Grounding Generic Secrets for Microsoft SharePoint](grounding-generic-secrets-for-microsoft-sharepoint-bdea357.md "")**
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docs/sap-ai-core/get-a-repository-a64179d.md

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You have created a resource group for grounding purposes. For more information, see [Create a Resource Group for Grounding](create-a-resource-group-for-grounding-6712bfe.md)
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You have created a generic secret for grounding purposes. For more information, see [Create a Generic Secret for Grounding](create-a-generic-secret-for-grounding-bdea357.md)
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You have created a generic secret for grounding purposes. For more information, see [Grounding Generic Secrets for Microsoft SharePoint](grounding-generic-secrets-for-microsoft-sharepoint-bdea357.md)
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