Update the code

Author: BenConstable9

text_2_sql/README.md

@@ -6,6 +6,8 @@ The implementation is written for [Semantic Kernel](https://github.com/microsoft
 
 The sample provided works with Azure SQL Server, although it has been easily adapted to other SQL sources such as Snowflake.
 
+**Two approaches are provided for schema management. A prompt based approach and a vector database based approach. See Multi-Shot Approach for more details**
+
 ## High Level Workflow
 
 The following diagram shows a workflow for how the Text2SQL plugin would be incorporated into a RAG application. Using the plugins available, alongside the [Function Calling](https://platform.openai.com/docs/guides/function-calling) capabilities of LLMs, the LLM can do [Chain of Thought](https://learn.microsoft.com/en-us/dotnet/ai/conceptual/chain-of-thought-prompting) reasoning to determine the steps needed to answer the question. This allows the LLM to recognise intent and therefore pick appropriate data sources based on the intent of the question.