ai-agents-for-beginners system prompt

# Azure AI Agent Service Development In this exercise, you use the Azure AI Agent service tools in the [Microsoft Foundry portal](https://ai.azure.com/?WT.mc_id=academic-105485-koreyst) to create a agent for Flight Booking. The agent will be able to interact with users and provide information about flights. ## Prerequisites To complete this exercise, you need the following: 1. An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/free/?WT.mc_id=academic-105485-koreyst). 2. You need permissions to create an Microsoft Foundry hub or have one created for you. - If your role is Contributor or Owner, you can follow the steps in this tutorial. ## Create an Microsoft Foundry hub > **Note:** Microsoft Foundry was formerly known as Azure AI Studio. 1. Follow these guidelines from the [Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-studio/?WT.mc_id=academic-105485-koreyst) blog post for creating an Microsoft Foundry hub. 2. When your project is created, close any tips that are displayed and review the project page in Microsoft Foundry portal, which should look similar to the following image:  ## Deploy a model 1. In the pane on the left for your project, in the **My assets** section, select the **Models + endpoints** page. 2. In the **Models + endpoints** page, in the **Model deployments** tab, in the **+ Deploy model** menu, select **Deploy base model**. 3. Search for the `gpt-4o-mini` model in the list, and then select and confirm it. > **Note**: Reducing the TPM helps avoid over-using the quota available in the subscription you are using.  ## Create an agent Now that you have deployed a model, you can create an agent. An agent is a conversational AI model that can be used to interact with users. 1. In the pane on the left for your project, in the **Build & Customize** section, select the **Agents** page. 2. Click **+ Create agent** to create a new agent. Under the **Agent Setup** dialog box: - Enter a name for the agent, such as `FlightAgent`. - Ensure that the `gpt-4o-mini` model deployment you created previously is selected - Set the **Instructions** as per the prompt you want the agent to follow. Here is an example: ``` You are FlightAgent, a virtual assistant specialized in handling flight-related queries. Your role includes assisting users with searching for flights, retrieving flight details, checking seat availability, and providing real-time flight status. Follow the instructions below to ensure clarity and effectiveness in your responses: ### Task Instructions: 1. **Recognizing Intent**: - Identify the user's intent based on their request, focusing on one of the following categories: - Searching for flights - Retrieving flight details using a flight ID - Checking seat availability for a specified flight - Providing real-time flight status using a flight number - If the intent is unclear, politely ask users to clarify or provide more details. 2. **Processing Requests**: - Depending on the identified intent, perform the required task: - For flight searches: Request details such as origin, destination, departure date, and optionally return date. - For flight details: Request a valid flight ID. - For seat availability: Request the flight ID and date and validate inputs. - For flight status: Request a valid flight number. - Perform validations on provided data (e.g., formats of dates, flight numbers, or IDs). If the information is incomplete or invalid, return a friendly request for clarification. 3. **Generating Responses**: - Use a tone that is friendly, concise, and supportive. - Provide clear and actionable suggestions based on the output of each task. - If no data is found or an error occurs, explain it to the user gently and offer alternative actions (e.g., refine search, try another query). ``` > [!NOTE] > For a detailed prompt, you can check out [this repository](https://github.com/ShivamGoyal03/RoamMind) for more information. > Furthermore, you can add **Knowledge Base** and **Actions** to enhance the agent's capabilities to provide more information and perform automated tasks based on user requests. For this exercise, you can skip these steps.  3. To create a new multi-AI agent, simply click **New Agent**. The newly created agent will then be displayed on the Agents page. ## Test the agent After creating the agent, you can test it to see how it responds to user queries in Microsoft Foundry portal playground. 1. At the top of the **Setup** pane for your agent, select **Try in playground**. 2. In the **Playground** pane, you can interact with the agent by typing queries in the chat window. For example, you can ask the agent to search for flights from Seattle to New York on 28th. > **Note**: The agent may not provide accurate responses, as no real-time data is being used in this exercise. The purpose is to test the agent's ability to understand and respond to user queries based on the instructions provided.  3. After testing the agent, you can further customize it by adding more intents, training data, and actions to enhance its capabilities. ## Clean up resources When you have finished testing the agent, you can delete it to avoid incurring additional costs. 1. Open the [Azure portal](https://portal.azure.com) and view the contents of the resource group where you deployed the hub resources used in this exercise. 2. On the toolbar, select **Delete resource group**. 3. Enter the resource group name and confirm that you want to delete it. ## Resources - [Microsoft Foundry documentation](https://learn.microsoft.com/en-us/azure/ai-studio/?WT.mc_id=academic-105485-koreyst) - [Microsoft Foundry portal](https://ai.azure.com/?WT.mc_id=academic-105485-koreyst) - [Getting Started with Azure AI Studio](https://techcommunity.microsoft.com/blog/educatordeveloperblog/getting-started-with-azure-ai-studio/4095602?WT.mc_id=academic-105485-koreyst) - [Fundamentals of AI agents on Azure](https://learn.microsoft.com/en-us/training/modules/ai-agent-fundamentals/?WT.mc_id=academic-105485-koreyst) - [Azure AI Discord](https://aka.ms/AzureAI/Discord)

--- description: 'Cherrypick a file deleted from the given commit between branches using Git.' mode: 'agent' --- # Cherry-picking a File Between Branches Using Git Your goal is to cherry-pick a specific file deleted from a given commit between branches in a Git repository. Use the Git command line interface to accomplish this task. ## Inputs - **Commit Hash**: $COMMIT - The hash of the commit from which to cherry-pick the file. - **File Path**: $FILE_PATH - The path of the file to be cherry-picked. If you don't have the commit hash or file path, please ask the user for these details. ## Instructions 1. **Identify the Commit**: Determine the commit hash from which you want to cherry-pick the file. 2. **Cherry-pick the File**: Use the `git checkout` command to cherry-pick the specific file from the identified commit. If the file doesn't exist in the given commit, find the closest commit where the file exists. 3. **Commit the Changes**: Ask the user to stage and commit the changes to finalize the cherry-pick.