Azd semantickernel cleanup

.gitignore

@@ -456,6 +456,5 @@ __pycache__/
 *.xsd.cs
 
 *.whl
-!autogen_core-0.3.dev0-py3-none-any.whl
 .azure
 .github/copilot-instructions.md

README.md

@@ -6,8 +6,6 @@ When dealing with complex organizational tasks, users often face significant cha
 
 The Multi-Agent Custom Automation Engine solution accelerator allows users to specify tasks and have them automatically processed by a group of AI agents, each specialized in different aspects of the business. This automation not only saves time but also ensures accuracy and consistency in task execution.
 
-### Technology Note
-This accelerator uses the AutoGen framework from Microsoft Research.  This is an open source project that is maintained by [Microsoft Research’s AI Frontiers Lab](https://www.microsoft.com/research/lab/ai-frontiers/). Please see this [blog post](https://devblogs.microsoft.com/autogen/microsofts-agentic-frameworks-autogen-and-semantic-kernel/) for the latest information on using the AutoGen framework in production solutions.
 <br/>
 
 <div align="center">
@@ -40,9 +38,9 @@ If you'd like to customize the solution accelerator, here are some common areas
 
 ### Additional resources
 
-[AutoGen Framework Documentation](https://microsoft.github.io/autogen/dev/user-guide/core-user-guide/index.html)
+[Semantic Kernel Documentation](https://learn.microsoft.com/en-us/semantic-kernel/)
 
-[Azure OpenAI Service Documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data)
+[Azure AI Foundry Documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/)
 
 [Azure Container App documentation](https://learn.microsoft.com/en-us/azure/azure-functions/functions-how-to-custom-container?tabs=core-tools%2Cacr%2Cazure-cli2%2Cazure-cli&pivots=container-apps)
 

TRANSPARENCY_FAQS.md

@@ -14,7 +14,6 @@ The evaluation process includes human review of the outputs, and tuned LLM promp
 
 ## What are the limitations of Multi Agent: Custom Automation Engine – Solution Accelerator? How can users minimize the impact Multi Agent: Custom Automation Engine – Solution Accelerator’s limitations when using the system? 
 The system allows users to review, reorder and approve steps generated in a plan, ensuring human oversight. The system uses function calling with LLMs to perform actions, users can approve or modify these actions. Users of the accelerator should review the system prompts provided and update as per their organizational guidance. Users should run their own evaluation flow either using the guidance provided in the GitHub repository or their choice of evaluation methods. 
-Note that the Multi Agent: Custom Automation Engine – Solution Accelerator relies on the AutoGen Multi Agent framework.  AutoGen has published their own [list of limitations and impacts](https://github.com/microsoft/autogen/blob/gaia_multiagent_v01_march_1st/TRANSPARENCY_FAQS.md#what-are-the-limitations-of-autogen-how-can-users-minimize-the-impact-of-autogens-limitations-when-using-the-system).
 
 ## What operational factors and settings allow for effective and responsible use of Multi Agent: Custom Automation Engine – Solution Accelerator? 
 Effective and responsible use of the Multi Agent: Custom Automation Engine – Solution Accelerator depends on several operational factors and settings. The system is designed to perform reliably and safely across a range of business tasks that it was evaluated for. Users can customize certain settings, such as the planning language model used by the system, the types of tasks that agents are assigned, and the specific actions that agents can take (e.g., sending emails or scheduling orientation sessions for new employees). However, it's important to note that these choices may impact the system's behavior in real-world scenarios.