Oracle 1z0-1157-26 valid exam dumps : Agentic AI Foundations Associate

  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Updated: Sep 23, 2026
  • Q&As: 60 Questions and Answers

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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionObjectives
Introduction to AI Agents- Agent development concepts
  • 1. Function calling and tool use
    • 2. OpenAI Agents SDK guardrails
      • 3. Multi-agent design patterns and handoffs
        - AI agent fundamentals and architecture
        • 1. AI agents, traditional chatbots, and rule-based systems
          • 2. Safety, guardrails, and responsible agentic workflows
            • 3. Core agent components: LLMs, tools, and orchestration loops
              • 4. Agent reasoning patterns including Chain-of-Thought and ReAct
                OCI Enterprise AI Agents- OCI Enterprise AI platform
                • 1. Responses API, tools, memory, and vector stores
                  • 2. Agent development, orchestration, and execution
                    • 3. OCI Enterprise AI Agents service
                      • 4. Building and running AI agents
                        • 5. Deployment and scaling
                          Agentic AI for Oracle AI Database- Oracle AI Database agentic AI capabilities
                          • 1. Oracle AI Database Private Agent Factory
                            • 2. Oracle AI Vector Search
                              • 3. Document chunking, embedding generation, and retrieval
                                • 4. Vector data types, embeddings, and similarity search
                                  • 5. Oracle Autonomous AI Database MCP Server
                                    • 6. Grounding agent responses with enterprise data
                                      • 7. Select AI
                                        LangChain for AI Agents- LangChain fundamentals
                                        • 1. Tools, tool schemas, and tool execution
                                          • 2. Building agents with LangChain
                                            • 3. LangChain and LangChain Expression Language
                                              • 4. Agent invocation and orchestration flow
                                                OpenAI Responses API and Agents SDK- OpenAI agent development
                                                • 1. Multi-agent handoffs
                                                  • 2. Function calling and tools
                                                    • 3. Guardrails and tracing
                                                      • 4. OpenAI Agents SDK
                                                        • 5. Responses API
                                                          Introduction to MCP- Model Context Protocol fundamentals
                                                          • 1. MCP clients and servers
                                                            • 2. Tool discovery and interoperability
                                                              • 3. MCP concepts and architecture

                                                                Oracle Agentic AI Foundations Associate Sample Questions:

                                                                Question #1

                                                                What is the high-level workflow for Oracle AI Vector Search?

                                                                • A. Generate embeddings - > Store vectors - > Create indexes - > Search and query - > Feed into LLM
                                                                • B. Generate embeddings - > Store vectors - > Search and query - > Feed into LLM
                                                                • C. Create indexes - > Search and query - > Feed into LLM - > Store vectors
                                                                • D. Create indexes - > Generate embeddings - > Store vectors - > Feed into LLM - > Search and query
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: A  🗳️

                                                                Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).

                                                                Question #2

                                                                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 overcome token limits for large documents.
                                                                • D. To convert text into SQL-compliant rows.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: C  🗳️

                                                                Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).

                                                                Question #3

                                                                What is short-term memory compaction in OCI Enterprise AI Agents?

                                                                • A. A summarization process for long conversations
                                                                • B. A network optimization for agent requests
                                                                • C. A runtime optimization for Python tools
                                                                • D. A masking process for prompt content
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: A  🗳️

                                                                Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).

                                                                Question #4

                                                                In the given LangChain chain, what is the role of StrOutputParser()? chain = prompt

                                                                • A. It stores tool execution history.
                                                                • B. StrOutputParser()
                                                                • C. It sends the prompt to the model API.
                                                                • D. It extracts plain text from the model response.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: D  🗳️

                                                                Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).

                                                                Question #5

                                                                What does the @function_tool decorator do in the OpenAI Agents SDK?

                                                                • A. Converts a regular Python function into a tool the agent can call.
                                                                • B. Caches the function's return value to disk for faster subsequent calls.
                                                                • C. Registers the function as an HTTP endpoint the agent calls via REST.
                                                                • D. Automatically retries the function if it raises an exception during execution.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: A  🗳️

                                                                Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).

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