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Increase embedding TPM capacity and add note in cloud ingestion guide (#2846)
* Increase embedding TPM capacity and add note in cloud ingestion guide * Update markdown lint * Better config format * Better config format * Fix the config * Ignore table style rule
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.github/workflows/lint-markdown.yml

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@@ -14,9 +14,11 @@ jobs:
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steps:
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- name: Checkout repo
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uses: actions/checkout@v6
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- name: Run markdownlint
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uses: articulate/actions-markdownlint@v1
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- name: Run markdownlint-cli2
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uses: DavidAnson/markdownlint-cli2-action@v21
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with:
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config: .github/workflows/markdownlint-config.json
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files: '**/*.md'
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ignore: data/
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config: .markdownlint-cli2.jsonc
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globs: |
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**/*.md
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!data/**
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!.github/**

.github/workflows/markdownlint-config.json

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.markdownlint-cli2.jsonc

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{
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"config": {
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"default": true,
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"line-length": false,
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"table-column-style": false,
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"MD033": { "allowed_elements": ["br", "details", "summary"] }
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}
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}

SECURITY.md

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<!-- BEGIN MICROSOFT SECURITY.MD V0.0.5 BLOCK -->
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## Security
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# Security
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Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), and [our GitHub organizations](https://opensource.microsoft.com/).
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docs/data_ingestion.md

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3. Open `azure.yaml` and un-comment the document-extractor, figure-processor, and text-processor sections. Those are the Azure Functions apps that will be deployed and serve as Azure AI Search skills.
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4. Provision the new Azure Functions resources, deploy the function apps, and update the search indexer with:
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4. (Recommended) Increase the capacity for the embedding model to the maximum quota allowed for your region/subscription, so that the Azure Functions can generate embeddings without hitting rate limits:
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```shell
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azd env set AZURE_OPENAI_EMB_DEPLOYMENT_CAPACITY 400
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```
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5. Provision the new Azure Functions resources, deploy the function apps, and update the search indexer with:
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```shell
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azd up
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```
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5. That will upload the documents in the `data/` folder to the Blob storage container, create the indexer and skillset, and run the indexer to ingest the data. You can monitor the indexer status from the portal.
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6. That will upload the documents in the `data/` folder to the Blob storage container, create the indexer and skillset, and run the indexer to ingest the data. You can monitor the indexer status from the portal.
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6. When you have new documents to ingest, you can upload documents to the Blob storage container and run the indexer from the Azure Portal to ingest new documents.
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7. When you have new documents to ingest, you can upload documents to the Blob storage container and run the indexer from the Azure Portal to ingest new documents.
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### Indexer architecture
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infra/main.bicep

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deploymentName: !empty(embeddingDeploymentName) ? embeddingDeploymentName : 'text-embedding-3-large'
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deploymentVersion: !empty(embeddingDeploymentVersion) ? embeddingDeploymentVersion : (embeddingModelName == 'text-embedding-ada-002' ? '2' : '1')
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deploymentSkuName: !empty(embeddingDeploymentSkuName) ? embeddingDeploymentSkuName : (embeddingModelName == 'text-embedding-ada-002' ? 'Standard' : 'GlobalStandard')
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deploymentCapacity: embeddingDeploymentCapacity != 0 ? embeddingDeploymentCapacity : 30
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deploymentCapacity: embeddingDeploymentCapacity != 0 ? embeddingDeploymentCapacity : 200
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dimensions: embeddingDimensions != 0 ? embeddingDimensions : 3072
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}
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