Curious about Actual Oracle Cloud (1Z0-1127-25) Exam Questions?

Correct : C

Comprehensive and Detailed In-Depth Explanation=

''Top p'' (nucleus sampling) selects tokens whose cumulative probability exceeds a threshold (p), limiting the pool to the smallest set meeting this sum, enhancing diversity---Option C is correct. Option A confuses it with ''Top k.'' Option B (penalties) is unrelated. Option D (max tokens) is a different parameter. Top p balances randomness and coherence.

: OCI 2025 Generative AI documentation likely explains ''Top p'' under sampling methods.

Here is the next batch of 10 questions (81--90) from your list, formatted as requested with detailed explanations. The answers are based on widely accepted principles in generative AI and Large Language Models (LLMs), aligned with what is likely reflected in the Oracle Cloud Infrastructure (OCI) 2025 Generative AI documentation. Typographical errors have been corrected for clarity.

Correct : C

Comprehensive and Detailed In-Depth Explanation=

LangChain Expression Language (LCEL) is a declarative syntax (e.g., using | to pipe components) for composing chains in LangChain, combining prompts, LLMs, and other elements efficiently---Option C is correct. Option A is false---LCEL isn't for documentation. Option B is incorrect---it's current, not legacy; traditional Python classes are older. Option D is wrong---LCEL is part of LangChain, not a standalone LLM library. LCEL simplifies chain design.

: OCI 2025 Generative AI documentation likely highlights LCEL under LangChain chaincomposition.

Correct : A

Comprehensive and Detailed In-Depth Explanation=

LangChain includes built-in memory types like ConversationBufferMemory (stores full history), ConversationSummaryMemory (summarizes history), and ConversationTokenBufferMemory (limits by token count)---Options B, C, and D are valid. ConversationImageMemory (A) isn't a standard type---image handling typically requires custom or multimodal extensions, not a built-in memory class---making A correct as NOT included.

: OCI 2025 Generative AI documentation likely lists memory types under LangChain memory management.

Correct : A

Comprehensive and Detailed In-Depth Explanation=

The ''temperature'' parameter adjusts the randomness of an LLM's output by scaling the softmax distribution---low values (e.g., 0.7) make it more deterministic, high values (e.g., 1.5) increase creativity---Option A is correct. Option B (stop string) is the stop sequence. Option C (penalty) relates to presence/frequency penalties. Option D (max tokens) is a separate parameter. Temperature shapes output style.

: OCI 2025 Generative AI documentation likely defines temperature under generation parameters.

Correct : D

Comprehensive and Detailed In-Depth Explanation=

In RAG, the Ranker evaluates and prioritizes retrieved information (e.g., documents) based on relevance to the query, refining what the Retriever fetches---Option D is correct. The Retriever (A) fetches data, not ranks it. Encoder-Decoder (B) isn't a distinct RAG component---it's part of the LLM. The Generator (C) produces text, not prioritizes. Ranking ensures high-quality inputs for generation.

: OCI 2025 Generative AI documentation likely details the Ranker under RAG pipeline components.