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| Section | Weight | Objectives |
|---|---|---|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Integrate agents with enterprise systems
|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
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NEW QUESTION # 86
Drag and Drop Question
A company has an approved custom connector that uses a REST API for an internal system.
An agent in Copilot Studio must call this connector during conversations to retrieve or update data.
To meet the business needs, the solution must meet the following requirements:
- Make the connector actions available for the agent to invoke.
- Ensure authentication is handled at the service level, not per user.
- Pass conversation context into the connector when it is called.
- Surface the returned data of the connector to the user in the
conversation.
You need to configure the agent and the connector action to meet the requirements.
What should you configure for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Add the connector as a tool in the agent
To make the custom connector actions available for the agent to invoke, the correct configuration action is to add the connector as a tool in the agent.
Box 2: Create or reuse a connection for the connector
The correct configuration action to ensure authentication is handled at the service level (and not per user) is to create or reuse a connection for the connector.
Service-Level Auth: In Copilot Studio, when you use a custom connector, you must establish a connection that determines how credentials are supplied.
Connection Creation: By creating a connection using a fixed service account or API key-and configuring it to be shared or run under that specific context-the agent authenticates at the system/service level.
Box 3: Map topic variables to the tool inputs
The correct configuration action is to map topic variables to the tool inputs.
When you add a custom connector to an agent in Microsoft Copilot Studio, it functions as a "tool" or an action. To pass specific data-such as conversation context or user details-from the ongoing chat into that connector, you must map the active Copilot Studio topic variables to the input parameters defined by the connector's REST API.
Box 4: Parse the JSON response and assign it to a topic variable
To surface the returned data of the connector to the user in Copilot Studio, the correct configuration action is to parse the JSON response and assign it to a topic variable.
Data Extraction: Custom connectors return raw JSON data from REST APIs.
Variable Storage: Copilot Studio cannot display raw JSON directly to users in a clean way.
User Delivery: You must parse that JSON payload to isolate specific fields and save them into topic variables, which can then be inserted into message nodes for the user to read.
Reference:
https://learn.microsoft.com/en-us/power-platform/release-plan/2024wave2/microsoft-copilot-studio/create-rest-api-copilot-connectors-copilot-studio
NEW QUESTION # 87
A company is extending agents in Copilot Studio with both external capabilities and enterprise content access. Some user requests require grounded answers, while other requests require executing actions.
To meet the business needs, the agent must meet the following requirements:
Ground answers using results from enterprise data.
Invoke callable functions exposed through a standardized tool interface.
Write an update to a system by using an authenticated action during the conversation.
You need to integrate the correct approach to meet the requirements.
Answer:
Explanation:
NEW QUESTION # 88
Drag and Drop Question
A company has an Azure AI Search vector index that contains enterprise content and wants to use it as a knowledge source for an agent in Copilot Studio.
To meet business needs, the knowledge source must meet the following requirements:
- The agent must connect to the Azure AI Search service.
- The agent must use a supported authentication method for the
connection.
- The agent must ensure answers are grounded using the specified Azure
AI Search index.
You need to connect to Azure AI Search as a knowledge source for the agent.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Initiate the process to add a knowledge source to the agent
You start inside Copilot Studio by navigating to your agent's settings and choosing to add a new knowledge source.
Step 2: Create a new Azure AI Search connection
From the available knowledge source options, you select Azure AI Search, which prompts the creation of a new connection.
Step 3: Configure the authentication method and provide the required connection details You input the necessary credentials (such as your Azure AI Search endpoint and API key or OAuth details) to authenticate the connection securely.
Step 4: Specify the Azure AI Search index to use for grounding
Once connected, you select the specific vector index that contains your enterprise content so the model knows where to look.
Step 5: Associate the configured knowledge source with the agent
Finally, you save and link this configured search source to the agent, enabling it to ground its responses using your enterprise data.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-azure-ai-search
NEW QUESTION # 89
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
An agent uses a flow that calls an external service which can occasionally fail or time out.
When a failure occurs, the agent must meet the following requirements:
- Must not terminate silently.
- Must send a notification containing the error details.
You need to configure the agent flow so that failures are handled in a controlled and predictable way.
Solution: Send a notification with relevant error details.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Configure run after conditions for failure paths.
You should configure the "Run after" conditions in Power Automate (the underlying flow engine) to handle these failures in a controlled and predictable way.
By default, a cloud flow step only runs if the previous step is successful. If your external service fails or times out, all subsequent steps will normally skip, causing the flow to fail silently from the perspective of the Copilot Studio agent.
How to Configure the Flow for Failure Handling
To meet your requirements, you need to create a parallel or sequential failure path using the following steps:
1. Add your Notification Action
2. Configure "Run After" Settings
Incorrect:
* Retry the failing action without handling failure.
* Send a notification with relevant error details.
Reference:
https://www.matthewdevaney.com/3-power-automate-error-handling-patterns-you-must-know/
NEW QUESTION # 90
Drag and Drop Question
A company uses an agent in Copilot Studio to answer questions based on enterprise content.
The content is indexed in Azure AI Search. Responses must be generated by a Microsoft Foundry model.
To meet the business needs, the solution must meet the following requirements:
- Users are able to trace each answer back to its source.
- The agent retrieves information from a centralized data index.
- Responses are generated by an enterprise-approved foundation model.
You need to configure generative answers for the agent.
What should you configure for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Instruct the agent to cite sources in knowledge settings
The specific behavior of how the agent presents that information-such as enforcing citations and tracing links back to the source documents-is controlled by the instructions and configurations within the agent's knowledge and conversation settings. You must explicitly configure the agent's prompt instructions or system settings to format the output with source citations so users can trace the answers.
Box 2: Configure Azure AI Search as the grounding data source
By adding Azure AI Search as a knowledge source Microsoft Copilot Studio enables the Retrieval-Augmented Generation (RAG) pattern. This ensures your generative AI model retrieves specific enterprise content from your centralized index and uses it to ground responses.
Box 3: Deploy a model in Foundry to an agent and connect to Copilot Studio Model Control: To strictly guarantee that an enterprise-approved foundation model (such as a specific Microsoft Foundry model) generates the response, you must manually deploy that specific model and link it to your agent.
Connection Workflow: Deploying the custom model in Azure AI Studio (formerly encompassing parts of Azure AI Foundry) and connecting it to Copilot Studio ensures the orchestration layer routes prompts directly to your certified LLM.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/ai-search
NEW QUESTION # 91
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