Load data, vector search sections

Author: codingbandit

07_Create_First_Cosmos_DB_Project/README.md

@@ -4,19 +4,19 @@ This section will cover how to create your first Cosmos DB project. We'll use a
 
 ## Emulator support
 
-Azure Cosmos DB has an emulator that can be used to develop code locally. The emulator supports the API for NoSQL and the API for MongoDB. The use of the emulator does not require an Azure subscription, nor does it incur any costs, so it is ideal for local development and testing. The Azure Cosmos DB emulator can also be utilized with unit tests in a [GitHub Actions CI workflow](https://learn.microsoft.com/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-mongodb#use-the-emulator-in-a-github-actions-ci-workflow).
+Azure Cosmos DB has an emulator that can be used to develop code locally. The emulator supports the API for NoSQL and the API for MongoDB. The use of the emulator does not require an Azure subscription, nor does it incur any costs, so it is ideal for local development and testing. The Azure Cosmos DB emulator can also be utilized with unit tests in a [GitHub Actions CI workflow](https://learn.microsoft.com/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-nosql#use-the-emulator-in-a-github-actions-ci-workflow).
 
 There is not 100% feature parity between the emulator and the cloud service. Visit the [Azure Cosmos DB emulator](https://learn.microsoft.com/azure/cosmos-db/emulator) documentation for more details.
 
 For Windows machines, the emulator can be installed via an installer or by using a Docker container. A Docker image is also available for Linux-based machines.
 
-Learn more about the pre-requisites and installation of the emulator [here](https://learn.microsoft.com/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-mongodb).
+Learn more about the pre-requisites and installation of the emulator [here](https://learn.microsoft.com/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-nosql).
 
 **The Azure Cosmos DB emulator does not support vector search. To complete the vector search and AI-related labs, a Azure Cosmos DB for NoSQL account in Azure is required.**
 
 ## Authentication
 
-Authentication to Azure Cosmos DB API for Mongo DB uses a connection string. The connection string is a URL that contains the authentication information for the Azure Cosmos DB account or local emulator. The username and password used when provisioning the Azure Cosmos DB API for NoSQL service are used in the connection string when authenticating to Azure.
+Authentication to Azure Cosmos DB for NoSQL uses a connection string. The connection string is a URL that contains the authentication information for the Azure Cosmos DB account or local emulator.
 
 ### Retrieving the connection string from the Cosmos DB Emulator
 
@@ -28,7 +28,7 @@ The splash screen or **Quickstart** section of the Cosmos DB Emulator will displ
 
 Retrieve the connection string from the Azure portal by navigating to the Azure Cosmos DB account and expanding the **Settings** menu item on the left-hand side of the screen. Locate the **Primary Connection String**, and select the icon to make it visible. Copy the connection string and paste it in notepad for future reference.
 
-![The Azure Cosmos DB API for NoSQL Connection strings screen displays with the copy button next to the connection string highlighted.](media/azure_connection_string.png)
+![The Azure Cosmos DB for NoSQL Connection strings screen displays with the copy button next to the connection string highlighted.](media/azure_connection_string.png)
 
 ## Lab - Create your first Cosmos DB for the NoSQL application
 
@@ -42,7 +42,7 @@ The following concepts are covered in detail in this lab:
 
 ### Creating a database client
 
-The `azure-cosmos` library is used to create a Cosmos DB API for NoSQL database client. The client enables both DDL (data definition language) and DML (data manipulation language) operations.
+The `azure-cosmos` library is used to create a Cosmos DB for NoSQL database client. The client enables both DDL (data definition language) and DML (data manipulation language) operations.
 
 ```python
 # Initialize the Cosmos DB client

08_Load_Data/README.md

@@ -1,31 +1,11 @@
-# Load data into Azure Cosmos DB API for NoSQL
+# Load data into Azure Cosmos DB for NoSQL
 
-The previous lab demonstrated how to add data to a container individually. This lab will demonstrate how to load data using bulk operations into multiple containers. This data will be used in subsequent labs to explain further the capabilities of Azure Cosmos DB API about AI.
-
-When loading data, bulk operations are preferred over adding each document individually. Bulk operations involve performing multiple database operations as a batch rather than executing them simultaneously. This approach is more efficient and provides several benefits:
-
-1. Performance: By issuing load operations in bulk, the lab can significantly reduce the overhead of network round-trips and database operations. This results in faster data loading and improved overall performance.
-
-2. Scalability: Bulk operations allow the lab to handle large volumes of data efficiently. They can quickly process and load a substantial amount of customer, product, and sales data, enabling them to scale their operations as needed.
-
-3. Atomicity: Bulk operations ensure that all database changes within a batch are treated as a single transaction. The entire batch can be rolled back if any document fails to load, maintaining data integrity and consistency.
-
-4. Simplified code logic: By using bulk operations, the lab can simplify its code logic and reduce the number of database queries. This results in cleaner, more manageable code and reduces the likelihood of errors or inconsistencies.
+To support future labs and exercises, the Cosmic Works data must be loaded into Azure Cosmos DB for NoSQL containers. This lab will demonstrate how to load the Cosmic Works Customer, Product, and Sales data into Azure Cosmos DB for NoSQL containers.
 
 ## Lab - Load data into Azure Cosmos DB for NoSQL containers
 
-This lab will load the Cosmic Works Customer, Product, and Sales data into Azure Cosmos DB for NoSQL containers using bulk operations. Both the Azure Cosmos DB Emulator and Azure Cosmos DB account in Azure are supported for completion of this lab.
+This lab will load the Cosmic Works Customer, Product, and Sales data into Azure Cosmos DB for NoSQL containers using bulk operations.
 
 >**Note**: It is highly recommended to use a [virtual environment](https://python.land/virtual-environments/virtualenv) for all labs.
 
 Please visit the lab repository to complete [this lab](../Labs/lab_2_load_data.ipynb).
-
-This lab demonstrates the use of bulk operations to load product, customer, and sales data into Azure Cosmos DB for NoSQL containers. As an example, the following code snippet inserts product data using the `bulk_write` method allowing for upsert functionality using the `UpdateOne` method:
-
-```python
-# Add product data to database using bulkwrite and updateOne with upsert
-# Get cosmic works product data from github
-product_raw_data = "https://cosmosdbcosmicworks.blob.core.windows.net/cosmic-works-small/product.json"
-product_data = ProductList(items=[Product(**data) for data in requests.get(product_raw_data).json()])
-db.products.bulk_write([ UpdateOne({"_id": prod.id}, {"$set": prod.model_dump(by_alias=True)}, upsert=True) for prod in product_data.items])
-```