Merge pull request #308089 from MaryanneNjeri/user/maryanne/agent_config_docs

AnnaMHuff · web-flow · commit bf5cc9785205 · 2026-01-14T13:37:55.000-07:00
[Azure App Configuration] AI Agent configuration docs
diff --git a/articles/azure-app-configuration/TOC.yml b/articles/azure-app-configuration/TOC.yml
@@ -194,6 +194,12 @@
       href: quickstart-chat-completion-dotnet.md
     - name: Go
       href: quickstart-chat-completion-go.md
+  - name: Agent framework
+    items:
+    - name: Get started
+      href: howto-ai-agent-config.md
+    - name: Python
+      href: howto-ai-agent-config-python.md
 - name: Feature management
   items:
   - name: Overview
diff --git a/articles/azure-app-configuration/concept-ai-configuration.md b/articles/azure-app-configuration/concept-ai-configuration.md
@@ -52,9 +52,16 @@ Chat completion is an AI capability that produces human-like dialogue responses
 Azure OpenAI Service supports a diverse set of models from OpenAI. For more information, see [Azure OpenAI Service models](/azure/ai-services/openai/concepts/models). To learn more about models from Anthropic, refer to the [Claude models documentation](https://docs.anthropic.com/docs/about-claude/models/overview).  
 For more details about models provided by Google, see the [Gemini models documentation](https://ai.google.dev/gemini-api/docs/models).
 
+## Agent framework 
+
+Agent framework is a comprehensive multi-language framework for building, orchestrating and deploying AI agents with support for both .NET and Python. This framework provides everything from simple chat agents to complex multi-agents workflows. For more information, refer to the [Microsoft Agent Framework documentation](/agent-framework/overview/agent-framework-overview). To see how App Configuration can help configure Agent Framework applications, visit the [getting started](./howto-ai-agent-config.md) guide.
+
 ## Next steps
 
 Continue to the following instructions to use AI configuration in your application:
 
 > [!div class="nextstepaction"]
-> [Chat completion configuration](./howto-chat-completion-config.md)
+> [Chat completion configuration](./howto-chat-completion-config.md)
+
+> [!div class="nextstepaction"]
+> [Agent framework](./howto-ai-agent-config.md)
diff --git a/articles/azure-app-configuration/howto-ai-agent-config-python.md b/articles/azure-app-configuration/howto-ai-agent-config-python.md
@@ -0,0 +1,174 @@
+---
+title: How to use Agent Framework in a Python app with Azure App Configuration
+titleSuffix: Azure App Configuration
+description: Learn how to use Agent Framework in a Python app with Azure App Configuration.
+ms.service: azure-app-configuration
+author: MaryanneNjeri
+ms.author: mgichohi
+ms.topic: how-to
+ms.date: 11/10/2025
+ms.update-cycle: 180-days
+ms.collection: ce-skilling-ai-copilot
+---
+
+# Use Agent Framework in a Python app with Azure App Configuration
+
+In this guide, you build an AI agent chat application using Azure App Configuration to load agent YAML specifications that define AI agent behavior, prompts and model configurations. 
+
+The full sample source code is available in the [Azure App Configuration GitHub repository](https://github.com/Azure/AppConfiguration/tree/main/examples/Python/ChatAgent).
+
+## Prerequisites
+
+- Create an _Azure AI project_ in Microsoft Foundry and configure the _example agent settings_ discussed in the [Get started](./howto-ai-agent-config.md#example-agent-settings) section.
+- Python 3.10 or later - for information on setting up Python on Windows, see the [Python on Windows documentation](/windows/python/).
+
+## Console application
+
+In this section, you create a console application and load the agent YAML specification from your App Configuration store.
+
+1. Create a new folder for your project. In the new folder, install the following packages by using the `pip install` command:
+
+    ```console
+    pip install azure-appconfiguration-provider
+    pip install agent-framework-declarative --pre
+    pip install azure-identity
+    ```
+
+1. Create a new file called _app.py_, and add the following import statements:
+
+    ```python
+    import asyncio
+    import os
+    from agent_framework.declarative import AgentFactory
+    from azure.identity import DefaultAzureCredential
+    from azure.appconfiguration.provider import load
+    ```
+
+1. You can connect to Azure App Configuration using either Microsoft Entra ID (recommended) or a connection string. In this example, you use Microsoft Entra ID with `DefaultAzureCredential` to authenticate to your App Configuration store. Follow these [instructions](./concept-enable-rbac.md#authentication-with-token-credentials) to assign the **App Configuration Data Reader** role to the identity represented by `DefaultAzureCredential`. Be sure to allow sufficient time for the permission to propagate before running your application.
+
+    ```python
+    async def main():
+        endpoint = os.environ["AZURE_APPCONFIGURATION_ENDPOINT"]
+
+        # Connect to Azure App Configuration using Microsoft Entra ID.
+        credential = DefaultAzureCredential()
+
+        config = load(endpoint=endpoint, credential=credential)
+    ```
+
+1. Update the code in _app.py_ to retrieve the agent specification from the configuration, create the agent from the YAML spec and handle user interaction:
+
+    ```python
+    async def main():
+        endpoint = os.environ["AZURE_APPCONFIGURATION_ENDPOINT"]
+
+        # Connect to Azure App Configuration using Microsoft Entra ID.
+        credential = DefaultAzureCredential()
+
+        config = load(endpoint=endpoint, credential=credential)
+
+        agent_spec = config["ChatAgent:Spec"]
+        
+        agent = AgentFactory(client_kwargs={"credential": credential, "project_endpoint": config["ChatAgent:ProjectEndpoint"]}).create_agent_from_yaml(agent_spec)
+
+        while True:
+            print("How can I help? (type 'quit' to exit)")
+
+            user_input = input("User: ")
+            
+            if user_input.lower() in ['quit', 'exit', 'bye']:
+                break
+        
+            response = await agent.run(user_input)
+            print("Agent response: ", response.text)
+            input("Press enter to continue...")
+            
+        print("Exiting... Goodbye...")
+
+    if __name__ == "__main__":
+        asyncio.run(main())
+    ```
+
+1. After completing the previous steps, your _app.py_ file should now contain the complete implementation as shown below:
+    ```python
+    import asyncio
+    import os
+    from agent_framework.declarative import AgentFactory
+    from azure.identity import DefaultAzureCredential
+    from azure.appconfiguration.provider import load
+
+    async def main():
+        endpoint = os.environ["AZURE_APPCONFIGURATION_ENDPOINT"]
+
+        # Connect to Azure App Configuration using Microsoft Entra ID.
+        credential = DefaultAzureCredential()
+
+        config = load(endpoint=endpoint, credential=credential)
+
+        agent_spec = config["ChatAgent:Spec"]
+        
+        agent = AgentFactory(client_kwargs={"credential": credential, "project_endpoint": config["ChatAgent:ProjectEndpoint"]}).create_agent_from_yaml(agent_spec)
+
+        while True:
+            print("How can I help? (type 'quit' to exit)")
+
+            user_input = input("User: ")
+            
+            if user_input.lower() in ['quit', 'exit', 'bye']:
+                break
+        
+            response = await agent.run(user_input)
+            print("Agent response: ", response.text)
+            input("Press enter to continue...")
+                
+        print("Exiting... Goodbye...")
+
+    if __name__ == "__main__":
+        asyncio.run(main())
+    ```
+
+## Build and run the app
+
+1. Set the environment variable named **AZURE_APPCONFIGURATION_ENDPOINT** to the endpoint of your App Configuration store found under the *Overview* of your store in the Azure portal.
+
+    If you use the Windows command prompt, run the following command and restart the command prompt to allow the change to take effect:
+
+    ```cmd
+    setx AZURE_APPCONFIGURATION_ENDPOINT "<endpoint-of-your-app-configuration-store>"
+    ```
+
+    If you use PowerShell, run the following command:
+    ```powershell
+    $Env:AZURE_APPCONFIGURATION_ENDPOINT="<endpoint-of-your-app-configuration-store>"
+    ```
+
+    If you use macOS or Linux, run the following command:
+    ```bash
+    export AZURE_APPCONFIGURATION_ENDPOINT='<endpoint-of-your-app-configuration-store>'
+    ```
+
+1. After the environment variable is properly set, run the following command to run the app locally:
+
+    ```console
+    python app.py
+    ```
+
+1. Type the message "What is the weather today in Seattle?" when prompted with "How can I help?" and then press the Enter key.
+
+    ```Output
+    How can I help? (type 'quit' to exit)
+    User: What is the weather today in Seattle?     
+    Agent response: Today in Seattle, expect steady rain throughout the day with patchy fog, and a high temperature around 57°F (14°C). 
+    Winds are from the south-southwest at 14 to 17 mph, with gusts as high as 29 mph.
+    Flood and wind advisories are in effect due to ongoing heavy rain and saturated conditions. 
+    Rain is likely to continue into the night, with a low near 49°F. 
+    Please stay aware of weather alerts if you are traveling or in low-lying areas [National Weather Service Seattle](https://forecast.weather.gov/zipcity.php?inputstring=Seattle%2CWA) [The Weather Channel Seattle Forecast](https://weather.com/weather/today/l/Seattle+Washington?canonicalCityId=1138ce33fd1be51ab7db675c0da0a27c).
+    Press enter to continue...
+    ```
+
+## Next steps
+
+To learn how to use Chat completion configuration in your application, continue to this tutorial.
+
+> [!div class="nextstepaction"]
+> [Chat completion configuration](./howto-chat-completion-config.md)
diff --git a/articles/azure-app-configuration/howto-ai-agent-config.md b/articles/azure-app-configuration/howto-ai-agent-config.md
@@ -0,0 +1,61 @@
+---
+title: Configuring agents in Agent framework with Azure App Configuration
+description: Learn how to configure agents in Agent framework with Azure App Configuration
+author: MaryanneNjeri
+ms.author: mgichohi
+ms.topic: how-to
+ms.service: azure-app-configuration
+ms.date: 11/25/2025
+ms.update-cycle: 180-days
+ms.collection: ce-skilling-ai-copilot
+---
+
+# Configuring agents in Agent framework with Azure App Configuration
+
+Agents are software systems that autonomously perform tasks using Large Language Models (LLMs) to process user input and execute actions on behalf of users. Agent framework provides tools and structures to build, orchestrate, and manage AI agents. Configuring agents within this framework involves defining their instructions and toolsets through either code-based or declarative methods. Azure App Configuration serves as a centralized store for these agent configurations, keeping them in one place where they can be easily managed and shared across multiple application instances.
+
+Here are some agent settings that can be stored on Azure App Configuration:
+
+ - Instructions
+ - Endpoint
+ - Agent name
+ - Model parameters - temperature, top_p, max_tokens, frequency_penalty, presence_penalty, response_format and stop sequences.
+ - Tools
+
+## Prerequisites
+
+- An Azure account with an active subscription. [Create one for free](https://azure.microsoft.com/free).
+- An App Configuration store, as shown in the [tutorial for creating a store](./quickstart-azure-app-configuration-create.md#create-an-app-configuration-store).
+
+
+## Example agent settings
+1. Follow the [Microsoft Foundry Quickstart](/azure/ai-foundry/quickstarts/get-started-code) to create a project in Foundry with a deployed gpt-4.1 model. Note down the Azure AI project endpoint for later use.
+
+1. Navigate to your App Configuration store and add the following key-values. Leave **Label** with its default value. For more information about how to add key-values to a store using the Azure portal or the CLI, go to [Create a key-value](./quickstart-azure-app-configuration-create.md#create-a-key-value).
+
+    | Key                            | Value                                                               | Content type                                 |
+    |--------------------------------|---------------------------------------------------------------------|----------------------------------------------|
+    | *ChatAgent:ProjectEndpoint*    | *Paste the Azure AI project endpoint*                               |                                              |
+    | *ChatAgent:Spec*               | *See YAML*                                                    |                                              |
+
+
+    **Value for ChatAgent:Spec**
+
+    ```yaml
+    kind: Prompt
+    name: ChatAgent
+    description: Agent example with web search
+    instructions: You are a helpful assistant with access to web search.
+    model:
+        id: gpt-4.1
+        connection:
+            kind: remote
+    tools:
+      - kind: web_search
+        name: WebSearchTool
+        description: Search the web for live information.
+    ```
+
+1. Continue to the following instructions to implement the AI agent configuration into your application for the language or platform you're using.
+
+    - [Python](./howto-ai-agent-config-python.md)
