AWS sagemaker-unified-studio documentation change
Summary
Updated documentation title and added detailed step-by-step instructions for creating a Knowledge Base with local files, including parsing options, chunking strategies, and embedding model selection
Security assessment
The changes are procedural documentation improvements showing how to configure data sources and processing options. No security vulnerabilities, access controls, or encryption mechanisms are mentioned. The parsing/chunking configurations relate to data processing efficiency rather than security.
Diff
diff --git a/sagemaker-unified-studio/latest/userguide/data-source-document.md b/sagemaker-unified-studio/latest/userguide/data-source-document.md index 821eff377..0ab3f46d8 100644 --- a//sagemaker-unified-studio/latest/userguide/data-source-document.md +++ b//sagemaker-unified-studio/latest/userguide/data-source-document.md @@ -5 +5 @@ -# Document data source +# Use a Local file as a data source @@ -7 +7 @@ -A document is a local file that contains information that you want the model to use when generating a response. By using a document as a data source for a knowledge base, your app users can chat with a document. For example, they can use a document to answers questions, make an analysis, create a summary, itemize fields in a numbered list, or rewrite content. +You can add a local file (document) as a data source. A document contains information that you want the model to use when generating a response. By using a document as a data source for a knowledge base, your app users can chat with a document. For example, they can use a document to answers questions, make an analysis, create a summary, itemize fields in a numbered list, or rewrite content. @@ -13 +13,50 @@ The document file must be in PDF, MD, TXT, DOC, DOCX, HTML, CSV, XLS or XLSX for -To create a knowledge base with a document data source, see [Create an Amazon Bedrock Knowledge Base component](./creating-a-knowledge-base-component.html). +###### To create a Knowledge Base with a local file + + 1. Navigate to the Amazon SageMaker Unified Studio landing page by using the URL from your administrator. + + 2. Access Amazon SageMaker Unified Studio using your IAM or single sign-on (SSO) credentials. For more information, see [Access Amazon SageMaker Unified Studio](./getting-started-access-the-portal.html). + + 3. Choose the **Build** menu at the top of the page. + + 4. In the **MACHINE LEARNING & GENERATIVE AI** section, choose **My apps**. + + 5. In the **Select or create a new project to continue** dialog box, select the project that you want to use. + + 6. In the left pane, choose **Asset gallery**. + + 7. Choose **My components**. + + 8. In the **Components** section, choose **Create component** and then **Knowledge Base**. The **Create Knowledge Base** pane is shown. + + 9. For **Name** , enter a name for the Knowledge Base. + + 10. For **Description** , enter a description for the Knowledge Base. + + 11. In **Select data source type** , Select **Local file** : + + 12. Choose **Click to upload** and upload the document that you want the Knowledge Base to use. Alternatively, add your source documents by dragging and dropping the document from your computer. + + 13. For **parsing** Choose either **default** parsing or choose **parsing with foundation model**. + + 14. If you choose **parsing with foundation model** , do the following: + + 1. For **Choose a foundation model for parsing** select your preferred foundation model. You can only choose models that your administrator has enabled for parsing. If you don't see a suitable model, contact your administrator. + + 2. (Optional) Overwrite the **Instructions for the parser** to suit your specific needs. + +For more information, see [Chunking and parsing with knowledge bases](./kb-chunking-parsing.html). + + 15. (Optional) For **Chunking strategy** Choose a chunking strategy for your knowledge base. For more information, see [Chunking and parsing with knowledge bases](./kb-chunking-parsing.html). + + 16. (Optional) For **Embeddings model** , choose a model for converting your data into vector embeddings, or use the default model. + + 17. Choose **Create** to create the Knowledge Base. + + 18. Use the Knowledge Base in an app, by doing one of the following: + + * If your app is a chat agent app, do [Add an Amazon Bedrock Knowledge Base component to a chat agent app](./add-kb-component-chat-app.html). + + * If your app is a flow app, do [Add a Knowledge Base component to a flow app](./add-kb-component-prompt-flow-app.html). + + + @@ -21 +70 @@ To use the Amazon Web Services Documentation, Javascript must be enabled. Please -Add a Knowledge Base to your Amazon Bedrock app +Create a Knowledge Base component @@ -23 +72 @@ Add a Knowledge Base to your Amazon Bedrock app -Web crawler data source +Use a web crawler as a data source