Update README.md

OpenAIDemos/README.md

@@ -16,7 +16,7 @@ Below is a summary list of the official Azure OpenAI Accelerators and workshops:
 | Azure OpenAI Workshop |  In this workshop, you will learn how to use the Azure OpenAI service to create AI powered solutions. You will get hands-on experience with the latest AI technologies and will learn how to use Azure OpenAI API. | [Link](https://github.com/Azure/azure-openai-workshop)
 | Business Process Automation solution accelerator | Creates pipelines to analyze text and audio datasets, across multiple cognitive services, and the HuggingFace library. The accelerator deploys all of the resources, and transforms the input data at each step, allowing multiple Cognitive Services to be called and deployed within a single, end-to-end pipeline. Includes capabilities like Azure OpenAI (summarization or custom prompts) and integration with CosmosDb, Cognitive Search, and RediSearch for Vector Search  | [Link](https://github.com/Azure/business-process-automation)
 |ChatGPT + Enterprise data with Azure OpenAI and Cognitive Search | This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure Cognitive Search for data indexing and retrieval. **NOTE: sample created by Product Group**| [Link](https://github.com/Azure-Samples/azure-search-openai-demo/)
-|Knowledge Mining with Azure OpenAI| The purpose of this repo is to accelerate the deployment of a Python-based Knowledge Mining solution with OpenAI that will ingest a Knowledge Base, generate embeddings using the contents extracted, store them in a vector search engine (Redis), and use that engine to answer queries / questions specific to that Knowledge Base.| [Link](https://github.com/MSUSAzureAccelerators/Knowledge-Mining-with-OpenAI)
+|Knowledge Mining with Azure OpenAI| The purpose of this repo is to accelerate the deployment of a Python-based Knowledge Mining solution with OpenAI that will ingest a Knowledge Base, generate embeddings using the contents extracted, store them in a vector search engine (Redis), and use that engine to answer queries / questions specific to that Knowledge Base. The repo includes the use of MRKL/ReAct Prompts and the ability to ask questions of different stores (including mathematical operations). | [Link](https://github.com/MSUSAzureAccelerators/Knowledge-Mining-with-OpenAI)
 | OpenAI workshop | Workshop materials to build intelligent solutions on Open AI | [Link](https://github.com/microsoft/OpenAIWorkshop)
 |Semantic Kernel |Semantic Kernel (SK) is a lightweight SDK enabling integration of AI Large Language Models (LLMs) with conventional programming languages.| [Link](https://github.com/microsoft/semantic-kernel)
 |Visual ChatGPT |Visual ChatGPT connects ChatGPT and a series of Visual Foundation Models to enable sending and receiving images during chatting. | [Link](https://github.com/microsoft/visual-chatgpt)