Correct Oracle Database 23ai mention (#384)

Author: ramonamagadan18

generative-ai-agent-23ai/sql/sql.md

@@ -20,9 +20,9 @@ This lab assumes you have:
 * All previous labs successfully completed
 * Must have an Administrator Account or Permissions to manage several OCI Services: Oracle ADB
 
-## Task 1: Oracle 23ai Prerequisites
+## Task 1: Oracle Database 23ai Prerequisites
 
-The user must have the Oracle 23ai Database with the following components:
+The user must have the Oracle Database 23ai with the following components:
 
 * Table: Used to store records with 'docid', 'body', and 'vector'.
 * Database Function: Provides vector search results against the provided query.

generative-ai-multi-agent-oda/provision-agent-23ai/provision-agent-23ai.md

@@ -155,9 +155,9 @@ This task involves creating a Database Tools Connection which will be used to qu
 
 ## Task 6: Load vector data in ADB using sql
 
-### Oracle 23ai Prerequisites
+### Oracle Database 23ai Prerequisites
 
-The user must have the Oracle 23ai Database with the following components:
+The user must have the Oracle Database 23ai with the following components:
 
 * Table: Used to store records with 'docid', 'body', and 'vector'.
 * Database Function: Provides vector search results against the provided query.

generative-ai-rag-llama-index/0-introduction/introduction.md

@@ -2,7 +2,7 @@
 
 ## About This Workshop
 
-The main purpose of this workshop is to get started with using Oracle 23ai Vector Similarity Search, OCI Generative AI Service and Llama-Index for putting together a Retrieval Augmented Generation application that can be utilized with unstructured data.
+The main purpose of this workshop is to get started with using Oracle Database 23ai Vector Similarity Search, OCI Generative AI Service and Llama-Index for putting together a Retrieval Augmented Generation application that can be utilized with unstructured data.
 
 Estimated time: 120 minutes
 

generative-ai-rag-llama-index/4-setup-gen-ai-frontend/setup-frontend.md

@@ -49,7 +49,7 @@ If you run into any issues in this portion of the lab, you can check error messa
 ## Task 5: Experimenting with RAG Frontend
 1. After completing the previous task, navigate to ```http://localhost:8501``` on your browser.
      ![Streamlit Frontend](images/frontend_splash_page.png)
-2. Upload a file for processing. This may take some time depending on the size of your file. Supported file types are .txt, .pdf, .csv and .tsv. You can use the example file used in this lab [Oracle 23ai Vector Search User Guide](https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/oracle-ai-vector-search-users-guide.pdf).
+2. Upload a file for processing. This may take some time depending on the size of your file. Supported file types are .txt, .pdf, .csv and .tsv. You can use the example file used in this lab [Oracle Database 23ai Vector Search User Guide](https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/oracle-ai-vector-search-users-guide.pdf).
      ![Upload File](images/browse_files.png)
 3. Once the data is preprocessed and vector generation is finished, your RAG Agent is ready to chat with. Make your first query.
      ![Chat with RAG Agent](images/RAG_text_generated.png)