Merge pull request #2144 from MicrosoftDocs/main

1/2/2025 AM Publish

Author: Albertyang0

articles/ai-studio/how-to/develop/ai-template-get-started.md

@@ -7,7 +7,7 @@ ms.service: azure-ai-studio
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 5/21/2024
+ms.date: 01/02/2025
 ms.reviewer: dantaylo
 ms.author: sgilley
 author: sdgilley
@@ -30,13 +30,16 @@ Start with our sample applications! Choose the right template for your needs, th
 
 | Template      | App host | Tech stack | Description |
 | ----------- | ----------| ----------- | ------------|
-| [Azure AI Basic Template with Python](https://github.com/azure-samples/azureai-basic-python) | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), Bicep | The app serves as a straightforward example of integrating Azure AI Services within a basic prompt-based application. This template walks you through building a simple chat app that utilizes models and prompts. It also covers setting up the necessary infrastructure for the app, including creating an Azure AI Foundry Hub, configuring projects, and provisioning essential resources such as Azure AI Service, Azure Container Apps, Cognitive Search, and more. <br>You can build, deploy, and test it with a single command.  |
+| [Azure AI Basic Template with Python](https://github.com/azure-samples/azureai-basic-python) | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), Bicep | The app serves as a straightforward example of integrating Azure AI Services within a basic prompt-based application. This template walks you through building a simple chat app that utilizes models and prompts. The template also covers setting up the necessary infrastructure for the app, including creating an Azure AI Foundry Hub, configuring projects, and provisioning essential resources such as Azure AI Service, Azure Container Apps, Cognitive Search, and more. <br>You can build, deploy, and test it with a single command.  |
 | [Contoso Chat Retail copilot with Azure AI Foundry](https://github.com/Azure-Samples/contoso-chat) | [Azure Container Apps](/azure/container-apps/overview) | [Azure Cosmos DB](/azure/cosmos-db/index-overview), [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [Azure AI Search](/azure/search/search-what-is-azure-search), Bicep  | A retailer conversation agent that can answer questions grounded in your product catalog and customer order history. This template uses a retrieval augmented generation architecture with cutting-edge models for chat completion, chat evaluation, and embeddings. Build, evaluate, and deploy, an end-to-end solution with a single command. | 
 | [Process Automation: speech to text and summarization with Azure AI Foundry](https://github.com/Azure-Samples/summarization-openai-python-prompflow) | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [Azure AI speech to text service](../../../ai-services/speech-service/index-speech-to-text.yml), Bicep  | An app for workers to report issues via text or speech, translating audio to text, summarizing it, and specify the relevant department. | 
 | [Multi-Modal Creative Writing copilot with Dalle](https://github.com/Azure-Samples/agent-openai-python-prompty) | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure AI Search](/azure/search/search-what-is-azure-search), [Azure OpenAI Service](../../../ai-services/openai/overview.md), Bicep | demonstrates how to create and work with AI agents. The app takes a topic and instruction input and then calls a research agent, writer agent, and editor agent. |  
 | [Assistant API Analytics Copilot with Python and Azure AI Foundry](https://github.com/Azure-Samples/assistant-data-openai-python-promptflow) | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) |  [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure AI Search](/azure/search/search-what-is-azure-search), [Azure OpenAI Service](../../../ai-services/openai/overview.md), Bicep| A data analytics chatbot based on the Assistants API. The chatbot can answer questions in natural language, and interpret them as queries on an example sales dataset. |
+<!-- remove for now
 | Function Calling with Prompty, LangChain, and Pinecone | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [LangChain](https://python.langchain.com/v0.1/docs/get_started/introduction), [Pinecone](https://www.pinecone.io/), Bicep  | Utilize the new Prompty tool, LangChain, and Pinecone to build a large language model (LLM) search agent. This agent with Retrieval-Augmented Generation (RAG) technology is capable of answering user questions based on the provided data by integrating real-time information retrieval with generative responses. | 
 | Function Calling with Prompty, LangChain, and Elastic Search | [Azure AI Foundry online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [Elastic Search](https://www.elastic.co/elasticsearch), [LangChain](https://python.langchain.com/v0.1/docs/get_started/introduction) , Bicep  | Utilize the new Prompty tool, LangChain, and Elasticsearch to build a large language model (LLM) search agent. This agent with Retrieval-Augmented Generation (RAG) technology is capable of answering user questions based on the provided data by integrating real-time information retrieval with generative responses |
+-->
+
 
 ### [C#](#tab/csharp)
 

articles/ai-studio/tutorials/copilot-sdk-evaluate.md

@@ -1,5 +1,5 @@
 ---
-title: "Part 3: Evaluate and deploy chat app with the Azure AI SDK"
+title: "Part 3: Evaluate a chat app with the Azure AI SDK"
 titleSuffix: Azure AI Foundry
 description: Evaluate and deploy a custom chat app with the prompt flow SDK. This tutorial is part 3 of a 3-part tutorial series.
 manager: scottpolly