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Oracle 1z0-1157-26 Exam Syllabus Topics:

Oracle Agentic AI Foundations Associate Sample Questions:

Question 1

Why is chunking necessary before generating embeddings for large documents?

A. To remove semantic meaning from the document.
B. To automatically encrypt content before indexing.
C. To convert text into SQL-compliant rows.
D. To overcome token limits for large documents.

Question 2

Which approaches are supported by OCI Enterprise AI Agents?

A. Deploy using Python-only or Java-only options.
B. Call the Responses API directly or deploy a hosted agent application.
C. Build a frontend agent or a backend agent.
D. Select a free or paid deployment model.

Question 3

In OpenAI Agents SDK, how does the model select which tool to call?

A. It calls every registered tool before answering.
B. It uses tool names, descriptions, and schemas.
C. It selects a tool randomly unless hardcoded.
D. It selects the first registered tool by name.

Question 4

Which SQL function computes distance between vectors in Oracle AI Vector Search?

A. EMBEDDING_DISTANCE()
B. SCORE_SIMILARITY()
C. VECTOR_DISTANCE()
D. VECTOR_SCORE()

Question 5

Which Python package is installed first for a simple OCI Responses API setup?

A. requests-html
B. openai
C. boto3
D. django

Solutions: