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The Microsoft Microsoft Certified: Azure AI Apps and Agents Developer Associate certification is a globally recognized credential that validates the skills and knowledge required to install, configure, operate, and troubleshoot small to medium-sized enterprise networks. To earn this prestigious certification, candidates must pass the Microsoft AI-103 exam, which covers a wide range of networking topics, including network fundamentals, network access, IP connectivity, IP services, security fundamentals, and automation and programmability.
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You have a customer support agent that uses the Microsoft Foundry Agent Service. Sometimes, customers return to a session days later to continue the same support case, and the agent must resume with the full historical context. The agent must provide the following: • Multi-turn continuity within the session • Cross-session continuity for the same case • Access to the full interaction history, including user messages, agent messages, tool calls, and tool outputs You need to ensure that the agent automatically reloads the complete history on each new turn. What should you do?
A. Persist only the final model response stored in the client application and prepend the
response to future prompts.
B. Enable memory summarization on the agent definition to persist the context automatically.
C. Create and reuse a conversation by storing the conversation’s ID and supplying the ID on subsequent requests.
You have a Microsoft Foundry project. You plan to build a customer support solution that contains an agent. The solution must meet the following requirements: • Provide accurate, context-aware responses grounded in internal product documentation stored in Azure AI Search. • Require deep, multi-step reasoning across long contexts. • Generate detailed natural language responses. Which type of model should you use to power the agent?
A. a multimodal model
B. a key phrase extraction model
C. a small language model (SLM)
D. a large language model (LLM)
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem. After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen. You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents. Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content. You need to improve response completeness. Solution: You increase the value of the temperature parameter. Does this meet the goal?
A. Yes
B. No
You have an app named App1 that uses a Microsoft Foundry multimodal model deployment. App1 runs optical character recognition (OCR) on uploaded images and appends the OCR output to the prompt as additional context. Some uploaded images contain embedded text. You need to prevent potentially malicious instructions from being processed by the model. What should you use?
A. protected material text
B. prompt shields for user prompts
C. image moderation
D. prompt shields for documents
You have an Azure Speech in Foundry Tools resource that hosts a custom speech to text model deployed to a custom endpoint. An agent uses the endpoint to perform real-time speech recognition. You are approaching the expiration date of the custom speech to text model. What is the expected behavior when the model expires?
A. Speech recognition requests will fall back to the most recent base model for the same locale.
B. Speech recognition requests will continue to use the expired custom model until the model is removed manually.
C. Speech recognition requests will return a 4xx error until a new custom model is deployed.
D. The custom model will be deleted automatically when the model expires.
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