Oracle Agentic AI Foundations Associate - 1z0-1157-26

Oracle 1z0-1157-26 test insides dumps
  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Updated: Sep 08, 2026
  • Q & A: 60 Questions and Answers
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Oracle 1z0-1157-26 Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: Model Context Protocol (MCP) Fundamentals15%- MCP architecture and integration
  • 1. Integrating MCP capabilities into agentic AI workflows
    • 2. Role of MCP in standardizing integration between AI agents and external tools
      • 3. MCP hosts, clients, servers, tools, resources, and prompts
        • 4. JSON-RPC 2.0 message format
          • 5. MCP transport options including stdio and Streamable HTTP
            Topic 2: LangChain for AI Agents5%- LangChain fundamentals and agent construction
            • 1. LangChain agent reasoning and tool execution flow
              • 2. LangChain tools, prompts, and chains
                • 3. LangChain core abstractions: chat models, prompts, tools, and agents
                  Topic 3: Agentic AI for Oracle AI Database25%- Oracle AI Database agentic AI capabilities
                  • 1. Oracle AI Database Private Agent Factory
                    • 2. Oracle AI Vector Search, Select AI, and MCP integration
                      • 3. Oracle AI Vector Search workflow: document chunking, embedding generation, similarity search, and retrieval
                        • 4. Oracle Autonomous AI Database MCP Server
                          • 5. Grounding agent responses with enterprise data from Oracle AI Database
                            • 6. VECTOR data type, vector embeddings, and similarity search
                              • 7. Select AI for natural-language interaction with Oracle AI Database
                                Topic 4: Introduction to AI Agents15%- AI agent fundamentals
                                • 1. Safety considerations and guardrail techniques
                                  • 2. Core components of an AI agent: LLM, tools, and orchestration loop
                                    • 3. Agent reasoning patterns: Chain-of-Thought and ReAct
                                      • 4. Differentiate AI agents from traditional chatbots and rule-based workflows
                                        Topic 5: OCI Enterprise AI Agents25%- OCI Enterprise AI platform and agent services
                                        • 1. OCI Enterprise AI Agents development, orchestration, and execution
                                          • 2. OCI Enterprise AI Agents building blocks: Responses API, tools, memory, and vector stores
                                            • 3. OCI Enterprise AI platform services for the enterprise AI agent lifecycle
                                              • 4. Building and running AI agents with OCI Enterprise AI Agents
                                                • 5. Deployment and scaling options
                                                  Topic 6: OpenAI Responses API and Agents SDK15%- OpenAI agent stack
                                                  • 1. Guardrails for validating inputs, outputs, and agent actions
                                                    • 2. Function calling and tools
                                                      • 3. Multi-agent design patterns and handoffs
                                                        • 4. OpenAI Responses API for agentic applications
                                                          • 5. Agents SDK primitives: Agent, Runner, Tool, Handoffs, and Guardrails
                                                            Oracle Agentic AI Foundations Associate Sample Questions:
                                                            Question #1

                                                            Which behavior is NOT a characteristic of modern LLM-based AI agents?

                                                            • A. Using external APIs or databases
                                                            • B. Pursuing goals across multiple steps
                                                            • C. Adjusting behavior based on observations
                                                            • D. Requiring every execution path to be predefined
                                                            Answer: D

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                                                            Question #2

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

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

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                                                            Question #3

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

                                                            • A. boto3
                                                            • B. openai
                                                            • C. requests-html
                                                            • D. django
                                                            Answer: B

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                                                            Question #4

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

                                                            • A. Create indexes - > Search and query - > Feed into LLM - > Store vectors
                                                            • B. Create indexes - > Generate embeddings - > Store vectors - > Feed into LLM - > Search and query
                                                            • C. Generate embeddings - > Store vectors - > Create indexes - > Search and query - > Feed into LLM
                                                            • D. Generate embeddings - > Store vectors - > Search and query - > Feed into LLM
                                                            Answer: C

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                                                            Question #5

                                                            Agent has multiply(a,b) and divide(a,b) . User: "What is 15 multiplied by 8, then divided by 3?" How does the OpenAI Agents SDK handle this?

                                                            • A. The SDK automatically combines all arithmetic operations into a single tool call.
                                                            • B. The model calls multiply(15, 8) , receives the result, then calls divide(120, 3) .
                                                            • C. The model calls every available arithmetic tool before answering.
                                                            • D. The Runner performs all arithmetic internally without involving the model or tools.
                                                            Answer: B

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