Merge branch 'main' of https://github.com/ahmedbham/azure-openai-api-…

…levelup

docs/modules/Module3/bookcreatorflow.md

@@ -0,0 +1,24 @@
+---
+title: Book Creator detailed flow
+parent:  Module 3 - Semantic Kernel
+has_children: false
+nav_order: 3
+---
+
+## Module 3: Book Creator application detailed flow
+
+The following sequence diagram illustrates the interactions of the Book creator Client app and the Semantic Kernel API exposed via the dotnet C# function.
+
+
+The function API exposes only 2 endpoints
+
+- /skills/{skillName}/invoke/{functionName}
+
+- /planner/execute/{maxSteps}
+
+
+  ![Semantic Kernel Use cases](../../assets/images/module3/book-creator-sequence.png)
+
+1. The childrensBookSkill is a predefined skill that with a templated prompt that can be found in the samples/skills folder, a skill may have one to many sub-skills or functions.
+2. The planner skill is also a specialized skill that can leverage additional skills, embeddings and connectors.
+3. The planner execute API used the templated values of the previous steps/instructions from the planner to fulfill the user's Ask.

docs/modules/Module3/intro.md

@@ -9,9 +9,9 @@ nav_order: 1
 
 ## What is Semantic Kernel?
 
-Semantic Kernel is an Open source, Lightweight SDK that allows you to easily integrate Large Language Models (LLMs) like ChatGPT into your applications.
+Semantic Kernel (SK) is an Open source, Lightweight SDK that allows you to easily integrate Large Language Models (LLMs) like ChatGPT into your application.
 
-SK provides the developer with controls over AI LLM constructs such as prompts, embeddings and allows you to provide rich context to your application specific use cases that you would not have by just using OpenAI/Azure OpenAI APIs.
+Semantic Kernel provides the developer with controls over AI LLM constructs such as prompts, embeddings and allows you to provide rich context to your application specific use cases that you would otherwise not have by just using OpenAI/Azure OpenAI APIs.
 
 ## Why is Semantic Kernel needed?
 
@@ -28,7 +28,7 @@ SK provides the developer with controls over AI LLM constructs such as prompts,
 
 ## Semantic Kernel - building blocks
 
-- Planner - The planner is responsible for fulfilling a specific ASK, the planner has access to a pre-defined library of pre-made skills and can also call upon memories to best situate the ASK's context and connectors to call APIs and to leverage other external capabilities if needed.
+- Planner - The planner is responsible for fulfilling a specific user ASK, the planner has access to a pre-defined library of pre-made skills and can also call upon memories to best situate the ASK's context and connectors to call APIs and to leverage other external capabilities if needed.
 
 - Memories – Also referred to as Embeddings and provides ability to provide specific context to an ASK or Prompt.
 

docs/modules/Module3/lab-module3.md

@@ -5,7 +5,7 @@ has_children: false
 nav_order: 2
 ---
 
-# Module 3: Lab - Book Creator application
+## Module 3: Lab - Book Creator application
 
  The Book creator sample application shows how `planner`, `skills` and `memories` are used to enrich content for a specific use case and allows you to enter in a children's book topic. Then the `Planner` creates a plan for the functions (skills) to run based on the Ask. You can see the execution plan along with the results. The `Writer` Skill functions are chained together based on the user ask.