troubleshooting

Which two metrics would you monitor to ensure a generative AI deployment on OCI is operating efficiently? (Choose two.)

A prompt engineer is designing a system prompt for a customer support agent. The goal is to ensure the agent always responds in a polite, professional tone and never provides medical advice. Which approach best achieves this?

A developer is using the OCI Generative AI service API and receives a '400 Bad Request' with error 'Model not found'. What is the most likely cause?

A company wants to deploy a custom fine-tuned model for retrieval-augmented generation (RAG) using dedicated AI cluster. They need to ensure the model can handle concurrent requests from multiple applications with consistent latency. What should they configure?

An enterprise is building a document Q&A application with OCI Generative AI. They want to minimize hallucinations. Which TWO techniques should they implement? (Choose two.)

Which TWO are valid methods to monitor the performance of a generative AI model deployed on OCI Data Science?

An organization uses Oracle AI Vector Search in Oracle Database 23ai to store embeddings for a LangChain RAG application. They need to perform similarity search with high recall and low latency for a large dataset (10M vectors). Which index configuration should they choose?

A user wants to test different prompt variations with a generative model interactively without writing code. Which OCI Generative AI tool should they use?

A data scientist is comparing BLEU, ROUGE, and BERTScore to evaluate a summarization model. The client cares most about whether the summary captures all key facts from the source document. Which metric is most aligned with this requirement?

In LangChain, which component is responsible for loading data from a specific file format, such as PDF or CSV, into a document object?

Which of the following is a known limitation of large language models where the model generates plausible-sounding but factually incorrect information?

A developer needs to extract structured data from news articles in JSON format, but the model occasionally outputs extra fields or omits required fields. Which prompt engineering approach would MOST reliably enforce the exact schema?

A prompt engineering team is designing a system prompt for a chatbot that should adopt a professional and concise tone. Which prompt pattern is BEST suited for this requirement?

A company is using dedicated AI cluster for fine-tuning. Which TWO best practices help optimize cost?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Which LangChain abstraction is used to wrap OCI Generative AI's chat models (e.g., Cohere Command R) for use in a LangChain chain?

Which three factors most significantly affect the quality of an LLM's output? (Select THREE)

Which TWO are advantages of using retrieval-augmented generation (RAG) over fine-tuning for incorporating new knowledge?

A company deployed OCI Generative AI for a customer service chatbot. They are using the Cohere command model. The chatbot is generating responses that are too brief and often cut off mid-sentence. They have limited budget. What should they do?

A company is deploying a large generative AI model on OCI using GPU compute instances. They want to optimize inference cost while maintaining acceptable latency. Which TWO strategies should they implement?

A developer is using OCI Generative AI to build a question-answering system over a large corpus of technical manuals. The developer uses the Cohere Embed model to generate embeddings and stores them in an OCI OpenSearch cluster. Queries are slow and the team needs to reduce latency. Which approach is BEST for improving search speed while maintaining acceptable accuracy?

A developer needs to generate embeddings for a set of search queries to be used in a semantic search system. Which input type should they specify when calling the Embedding API?

A company has a collection of PDF documents that are 500 pages each. They want to build a RAG system using LangChain and FAISS. They need to ensure that each chunk has enough context for accurate retrieval while keeping chunk size small enough for efficient embedding. They also want some overlap between chunks to avoid losing context at boundaries. Which text splitter configuration is most appropriate?

A prompt engineer is refining a prompt that currently produces outputs with excessive repetition. Which TWO parameters can be adjusted to reduce repetition? (Choose two.)

Refer to the exhibit. A user receives this error when calling the OCI Gen AI inference endpoint. What is the most likely cause?

A team wants to use OCI Generative AI to generate synthetic data for training a model. They are concerned about the cost of API calls. Which pricing model would be most cost-effective for high-volume batch processing?

A developer is using the Chat API for a multi-turn conversation. They want the assistant to adopt a formal tone and always identify itself as 'OracleBot'. How should they configure the API request?

Which OCI service provides a managed vector database capability that can be used as a knowledge base in a RAG architecture?

An OCI Generative AI user wants to host a fine-tuned model with guaranteed low latency for a production application. Which option should they choose?

A company wants to process a large batch of documents to generate summaries using OCI Generative AI. They need the most cost-effective option without compromising on summary quality. Which approach should they use?

When evaluating a summarization model, the team notices that the ROUGE-L score is high but human evaluators rate the summaries poorly for coherence. What does this discrepancy MOST likely indicate?

An organization deploys a fine-tuned model for legal document analysis using OCI Generative AI Service. They need to ensure that only authorized users in the 'LegalTeam' group can access the model endpoint. Which policy statement should be used?

An application needs to generate embeddings for text in multiple languages (English, Spanish, French). Which OCI Generative AI embedding model should be used?

A data scientist wants to quickly test a prompt with different parameters like temperature and max tokens without writing code. Which OCI GenAI feature should they use?

In LangChain, which class should be used to wrap Oracle Cloud Infrastructure's Generative AI service as a chat model?

An organization is deploying a large language model on OCI using a dedicated AI cluster. They need to minimize inference latency. Which configuration step is most critical?

A developer notices that the RAG system returns irrelevant chunks when the user query contains typos or abbreviations. Which technique would BEST improve retrieval robustness for such queries?

Which LangChain abstraction is responsible for storing and retrieving conversation history to maintain context across multiple turns in a chatbot?

An application uses LangChain's ConversationalRetrievalChain with memory. Users report that the chatbot occasionally repeats information from earlier in the conversation even when the new question is unrelated. What is the most likely cause?

Which prompt pattern is most suitable when a user needs to generate a structured report following a specific template every time?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A data scientist is using OCI Generative AI Service to generate product descriptions. They notice that the output often repeats phrases. Which parameter adjustment would MOST directly address this issue?

A team is designing a RAG system for a multilingual knowledge base. Which TWO strategies are appropriate? (Choose two.)

Which TWO of the following are valid ways to reduce latency when using OCI Generative AI Service?

A developer is using the OCI Generative AI service and notices that the cost per API call is higher than expected. Which factor contributes MOST to the cost of an LLM inference call?

A developer is using Oracle AI Vector Search with LangChain to build a RAG system on top of Oracle Database 23ai. They have created a VECTOR column and built an HNSW index. To improve recall at the cost of some accuracy, which index parameter should they adjust?

A developer is using LangChain's RecursiveCharacterTextSplitter with chunk_size=1000 and chunk_overlap=200. Which statement best describes the resulting chunks?

An organization plans to deploy a custom fine-tuned model for a real-time chat application requiring consistent low-latency responses. They expect high throughput during business hours. Which OCI Generative AI infrastructure choice best meets these requirements?

A startup is building a customer support chatbot using RAG with OCI Generative AI. They have a large corpus of FAQ documents stored as PDFs in OCI Object Storage. The developer uses OCI Language to embed the text and stores vectors in OCI OpenSearch. During testing, the chatbot often fails to answer questions because relevant FAQ entries are not retrieved. The team suspects the chunking size is too large, causing loss of specific details. After reducing chunk size, retrieval improves slightly but still misses many answers. What should the team do NEXT?

A developer is implementing a text generation pipeline using OCI Generative AI and needs to produce diverse, creative outputs for a marketing campaign. Which sampling strategy should they choose?

A company wants to build a RAG application using OCI Generative AI Agents. Which TWO components are required to set up the agent?

Refer to the exhibit. Users in the group cannot create a new custom model deployment on a Dedicated AI Cluster. What is the most likely missing permission?

When using Cohere Command models on OCI Generative AI, a developer wants to ground a response based on a provided document. Which syntax should be used to embed document content in the prompt?

An OCI user wants to generate embeddings for a large corpus of technical documents to enable semantic search. Which type of model should they use?

A team wants to use a prompt pattern that combines reasoning with acting, where the model alternates between thinking and taking actions (e.g., tool calls). Which pattern fits this requirement?

A user wants to use OCI Generative AI to generate marketing copy. They want the output to be more creative and varied. Which parameter should they adjust?

A data scientist wants to generate a response that lists top-3 product features in a bulleted format with no introductory text. Which prompt engineering technique should be used?

An organization wants to use OCI Generative AI for real-time document translation. They need high availability across regions. Which deployment option meets this requirement?

Which THREE models are available as part of the OCI Generative AI service?

A company uses a RAG pipeline with OCI Data Science and Cohere embeddings. They notice that retrieval recall is low for domain-specific acronyms. What is the best practice to improve this?

A team is deploying a chatbot that must never output harmful or biased statements. They plan to use a pre-trained LLM with in-context learning. Which additional measure is MOST effective at reducing harmful outputs without retraining?

A team is prompting a model to translate English to French. They notice the model occasionally mixes French with other Romance languages. Which prompt refinement strategy would MOST likely improve language consistency?

A developer wants to index a large corpus of HTML web pages for a RAG pipeline using LangChain. They need to load the content from URLs, split the text into chunks, and generate embeddings. Which combination of LangChain components should they use?

A developer is using ChatPromptTemplate with MessagesPlaceholder to handle conversation history. What is the purpose of MessagesPlaceholder in the prompt template?

An OCI customer is deploying a chatbot using a pre-trained LLM. They are concerned about the model generating biased or harmful content. Which TWO strategies should they implement as part of their responsible AI approach? (Choose two.)

An organization needs to choose a model for a multilingual customer support chatbot that must understand and respond in five different languages. Which TWO models available in OCI Generative AI are suitable?

A team wants to create a prompt library for their organization's LLM applications. Which practice is MOST important for maintaining prompt quality over time?

Which THREE components are required to deploy a custom generative AI model on OCI Data Science model deployment?

Which TWO methods can be used to invoke a generative AI model deployed on OCI?

An enterprise RAG application experiences high latency during peak hours. The architecture uses OCI OpenSearch with a single node cluster storing 5 million vectors (768 dimensions). The search uses exact k-NN (EF_SEARCH=500). The average query takes 1.5 seconds, but the SLA requires <500ms. The team considers several options: A) Switch to ANN with lower recall (HNSW with ef_search=50), B) Scale OpenSearch cluster to 3 nodes, C) Reduce embedding dimension to 256 using PCA, D) Increase the number of shards from 1 to 10. Which option provides the best balance of latency reduction and minimal impact on retrieval quality? (Assume all options are feasible)

When invoking the OCI Generative AI service from a RAG application, the developer receives a 401 Unauthorized error. The application uses resource principal authentication from an OCI Data Science notebook session. What is the most likely fix?

A developer is using the Embedding API to create embeddings for a clustering task. They want to ensure the embeddings are optimized for clustering similar documents. Which input type should they specify?

A healthcare company must use OCI Generative AI for medical report generation. They need to ensure PHI is not sent to third-party models. Which approach best ensures data stays within OCI?

A prompt engineer is designing a system to answer customer queries using OCI Generative AI. They want to ensure the model's responses are concise, accurate, and consistent. Which TWO prompt engineering practices should they implement? (Select two.)

A developer uses a Cohere Command model with a preamble: 'You are a helpful assistant that answers questions based on the provided document.' They also include a user message with a query and a relevant document excerpt. However, the model often ignores the document and uses its own knowledge. Which improvement is MOST effective?

An enterprise is using OCI Generative AI with a RAG architecture. They observe that the LLM sometimes produces hallucinated answers that are not supported by the retrieved documents. Which strategy is most effective in reducing these hallucinations?

A company wants to deploy a custom generative AI model for generating synthetic data for training other models. The model requires approximately 20GB of memory and must be accessible via a REST API with authentication. Additionally, the team needs to monitor for data drift over time. Which combination of OCI services best meets these requirements with minimal operational overhead?

Which prompting technique involves providing the model with a few examples of input-output pairs within the prompt to guide its behavior?

A research team is experimenting with few-shot prompting to improve a model's performance on a complex reasoning task. They find that the model's performance degrades when the few-shot examples are too similar to each other. What is the likely cause and best remedy?

A developer uses the OCI Generative AI Chat API to build a multi-turn conversational agent. They notice the model starts to lose context after several exchanges. What is the MOST likely cause?

Which of the following is a key limitation of large language models that RAG (Retrieval-Augmented Generation) aims to address?

An organization requires low-latency inference for a custom fine-tuned model that will be used in a real-time application. They also need guaranteed availability and isolation from other tenants. Which infrastructure option should they choose?

An OCI Generative AI practitioner observes that a Cohere Command model generates responses with outdated information about a recent event. The model was fine-tuned six months ago. Which technique should be applied to incorporate new knowledge without retraining the model?

An organization needs to fine-tune a Cohere Command R model for a custom domain. They have prepared a dataset in JSONL format. Which component of the fine-tuning job specifies the base model and the training dataset location?

A developer is using the OCI Generative AI Chat API with Cohere Command R+ to build a multi-turn conversational agent. They want the agent to always respond in a formal tone, regardless of the user's phrasing. Which parameter should they set in the API request to achieve this consistently?

A developer is using Cohere Command R+ via OCI Generative AI and wants to ground answers in a provided set of documents using the `documents` parameter. Which prompt structure ensures the model correctly adheres to the documents?

A DBA has created the above vector index. After running queries, they observe that recall is lower than expected for approximate searches. Which change would most likely improve recall while maintaining query performance?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A company is using OCI Generative AI to generate code snippets and notices that the model sometimes produces code with security vulnerabilities. They have a small dataset of secure code examples. Which approach would be most effective to reduce vulnerabilities?

A team is building a code generation assistant using OCI Generative AI. They notice that the model occasionally produces code with subtle security vulnerabilities. Which approach would most effectively reduce this risk without compromising the assistant's usefulness?

A prompt engineer is using the self-consistency technique to improve answer reliability. Which TWO steps are essential when implementing self-consistency?

A machine learning engineer is fine-tuning a Cohere Command R model using T-Few. They have prepared a JSONL dataset with 500 prompt-completion pairs. After submitting the fine-tuning job, they notice the model's performance on validation data is poor. Which action is MOST likely to improve performance?

A researcher is comparing BLEU and ROUGE scores for a machine translation model. They notice that the BLEU score is high but the ROUGE score is low. Which scenario is MOST consistent with this observation?

A company's RAG application ingests news articles that are updated frequently. The vector store in OCI OpenSearch contains embeddings of the articles. The team notices that outdated information is still retrieved even after updating the source documents. What is the most effective way to ensure the vector store reflects the latest content?

Which THREE of the following are known limitations of LLMs that practitioners must account for?

Which TWO factors most directly impact the consistency of text generated by an LLM when the same prompt is used multiple times?

Which of the following sampling strategies is most likely to produce the most diverse and creative text?

Which LangChain document loader should be used to load text from a web page given its URL?

An AI engineer is designing a prompt that requires the model to solve a complex math problem. They want the model to explore multiple reasoning paths and then aggregate the final answer. Which prompting technique BEST fits this requirement?

A data scientist is iteratively refining a prompt for a text classification task. Which TWO practices are essential for systematic prompt improvement?

A company wants to use OCI Generative AI to summarize customer feedback. They need low latency and high throughput. Which configuration should they choose?

An engineer is using the ReAct pattern to build a reasoning agent. The agent should first reason about the user query, then call an external API, and finally incorporate the API result into a final answer. Which prompt structure best implements this pattern?

A prompt engineer is tasked with reducing hallucinations in a document-grounded generation task using Cohere Command R. Which system prompt component is MOST effective for enforcing that the model only uses provided documents?

A startup needs to deploy a large language model for a customer support chatbot that requires low latency and cost efficiency. They are evaluating OCI Generative AI models. Which model type is most appropriate?

A team wants to deploy an LLM for real-time inference with low latency. Which OCI deployment option is best?

A company wants to build a multi-modal RAG system that can retrieve both text and images based on a user query. Which approach is most aligned with OCI GenAI capabilities?

An AI application uses LangChain's LCEL with the | operator to compose a chain: prompt | model | output_parser. During testing, the developer notices that the output_parser is not receiving the expected input format from the model. What is the most likely cause?

A developer is building a code generation assistant. The model occasionally produces syntactically correct but semantically wrong code. Which technique directly addresses semantic correctness?

When using an LLM for code generation, a developer notices the model occasionally produces syntactically incorrect code. Which approach is most likely to reduce syntax errors while still allowing diverse output?

A data scientist is using the OCI Generative AI Playground to test a model for a text generation task. They want to control the output to be more focused and avoid repeating the same phrases. Which THREE parameter adjustments should they consider?

A company is using OCI Generative AI service to generate product descriptions. They notice that the model sometimes generates biased content. Which approach should they take to mitigate bias while maintaining performance?

An application needs to generate embeddings for customer reviews to cluster them by sentiment. Which input type should be specified in the Embedding API call?

An organization is deploying a generative AI model that requires GPU acceleration for inference. They are using OCI Data Science Model Deployment. The model is expected to handle variable traffic, with occasional spikes. Which scaling option should they configure to ensure cost-efficiency and responsiveness?

A developer receives the above error when querying a RAG application. What is the most likely cause and recommended action?

Which THREE steps are required to deploy a custom generative AI model using OCI Data Science Model Deployment?

You need to build a RAG pipeline using LangChain and OCI Generative AI. The pipeline must load PDF documents, split them into chunks, embed them, store in a vector store, and retrieve relevant chunks at query time. Which THREE components are essential? (Choose THREE.)

A machine learning engineer is preparing a dataset for fine-tuning a model in OCI Generative AI. The dataset consists of customer support conversations with questions and desired answers. What is the required format for the training data?

Which TWO of the following are sources of training data for fine-tuning a model in OCI Generative AI?

A company is building a RAG application using OCI Generative AI and OCI Search with OpenSearch. Users report that the responses from the LLM are not relevant to the queries, even though the document chunks seem appropriate. What is the most likely cause?

Which prompt engineering technique asks the model to explain its reasoning process step-by-step before arriving at the final answer?

A developer is using the ReAct pattern to build a reasoning agent. Which of the following best describes the two main steps in this pattern?

A company is deploying OCI Generative AI for a chatbot that must answer customer queries within 500ms. They choose a dedicated AI cluster but observe 2-second latency. What is the most likely cause?

A company wants to build a RAG-based assistant that answers queries using documents stored in OCI Object Storage. Which OCI Generative AI service should they use?

Which TWO are best practices for building a RAG application on OCI? (Choose two.)

Which TWO of the following are valid ways to consume OCI Generative AI models?

An enterprise needs to deploy a custom fine-tuned model for real-time inference with strict latency requirements. They also need to manage costs by paying only for usage. Which three steps are required to achieve this? (Select THREE)

A team is fine-tuning a generative AI model on OCI using a custom dataset. The training job fails with an out-of-memory error. Which THREE actions should they take to resolve this issue?

A data scientist is evaluating an LLM for a summarization task. They have a set of human-written reference summaries. Which THREE metrics are commonly used to evaluate summarization quality? (Choose three.)

A developer wants to integrate OCI Generative AI into a web application. Which API authentication method is recommended for programmatic access?

A developer is building a text generation application using OCI Generative AI and wants to control the creativity of the output. Which THREE sampling parameters can they adjust? (Choose three.)

A data scientist is fine-tuning a model using T-Few in OCI Generative AI. They have prepared a dataset with prompt/completion pairs. Which file format is required for the training data upload?

A developer is troubleshooting an OCI Generative AI inference request that returns a 400 Bad Request error. Which three common causes could result in this error? (Choose three.)

A financial services firm needs to ensure that only members of the 'DataScientists' group can use OCI Generative AI resources in the 'prod' compartment. Which IAM policy statement should be applied?

A user wants to quickly test different prompts and parameters (temperature, max tokens) with various OCI Generative AI models without writing any code. Which tool should they use?

A prompt engineer is iteratively refining a prompt for a product review summarizer. They want to test which prompt version yields the most accurate summaries. Which approach should they use?

A prompt engineer wants the model to adopt a formal and authoritative tone when generating financial reports. Which approach is MOST effective?

A data scientist is using self-consistency decoding to improve the accuracy of a reasoning task. Which of the following best describes the process?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Your organization has deployed a generative AI model for a multilingual translation service on OCI Model Deployment. The model is a 13B parameter transformer hosted on a single VM.GPU.A100.1 shape with 2 replicas. Recently, the service experiences intermittent timeouts when a burst of requests arrives. You have enabled autoscaling based on CPU utilization, but the scaling is too slow. After investigation, you find that the model inference time is highly variable due to different sequence lengths. You need to ensure the service can handle sudden spikes without timeouts. Which solution should you implement?

A data scientist is evaluating an LLM's performance on a summarization task. Which TWO metrics are most suitable for this evaluation?

Refer to the exhibit. A user in group GenAIUsers reports that they cannot call the OCI Generative AI API. What is the most likely issue?

Which THREE factors should be considered when designing a chunking strategy for a RAG application?

A developer is tuning parameters for a text-generation model and wants to reduce the likelihood of the same phrase appearing repeatedly. Which parameter should be adjusted?

A team is planning to use OCI Generative AI to summarize large documents. They need to choose between on-demand (pay-as-you-go) and dedicated cluster pricing. Which THREE factors should they consider when deciding? (Choose three.)

A prompt engineer wants to generate a poem in a specific rhyming scheme (ABAB). Which combination of prompt components is LEAST likely to succeed?

Which TWO actions should be taken to monitor model drift in a deployed generative AI model? (Select TWO)

Which TWO of the following are valid approaches to serve a RAG application in OCI with low latency?

A generative AI model deployed on OCI Model Deployment is experiencing high tail latency. The model is a large language model that processes variable-length input sequences. Profiling shows that inference time varies significantly: short inputs (100 tokens) take 100ms, while long inputs (2000 tokens) take 2 seconds. The application requires consistent low latency (<500ms) for most requests. You want to reduce the variance in inference time without major changes to the model architecture. Which technique should you apply?

A developer receives the above error when trying to send a request to a model endpoint. What is the most likely reason?

A data scientist is using the OCI Generative AI Playground to test a summarization model. They want to generate shorter summaries and avoid repetitive phrasing. Which parameter adjustments should they make?

Which LangChain memory type stores the entire conversation history as a list of messages and is best for simple, short conversations?

A startup wants to minimize costs when using OCI Generative AI service for a chatbot application that experiences sporadic usage. Which deployment strategy is most cost-effective?

A company has fine-tuned a custom Llama 3 model using OCI Data Science for a chatbot. They now need a production-grade inference endpoint with auto-scaling. Which OCI service should they use?

A company has deployed a generative AI endpoint using a custom fine-tuned model. They observe that the endpoint is returning 429 (Too Many Requests) errors during business hours. They need to handle this without losing requests. What should they implement?

A team is deploying an LLM-based application that must adhere to strict data residency requirements. All processing must occur within a specific OCI region. Which OCI service should they use to host and serve the LLM?

A company wants to reduce costs for a high-volume, latency-tolerant text generation workload using OCI Generative AI. Which TWO strategies should they consider?

During inference with OCI Generative AI, you notice that the model is generating repetitive phrases. Which combination of parameters can help reduce repetition?

A security administrator needs to grant a group of data scientists the ability to use OCI Generative AI service resources in the compartment 'genai-dev'. They want to allow the group to create endpoints and run inference, but not to manage IAM policies. Which policy statement is correct?

Which TWO of the following are true about positional encoding in transformer models?

An architect is optimizing an LLM application that processes long documents. The model has a 4096 token limit, but the documents are often 8000 tokens. They are using a chunking strategy. However, model responses sometimes miss key information that spans across chunks. Which technique most directly addresses this issue?

Which TWO factors most significantly influence the computational cost of fine-tuning a large language model?

A data scientist is using the OCI Generative AI service to generate text completions. The API calls are returning HTTP 400 errors with the message 'Invalid model parameters'. What is the most likely cause?

Which authentication method should be used to securely call the OCI Generative AI API from a microservice running on OCI Compute?

Which OCI Generative AI model is best suited for generating embeddings from text that can be used for semantic search across multiple languages?

A multi-turn chatbot needs to maintain context across user queries. The context window is limited. What design should be used?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Refer to the exhibit. A developer runs the command and receives the error. What is the issue?

A company wants to use OCI Generative AI to summarize customer reviews. Which model parameter should be adjusted to control the creativity of the summary?

An OCI user wants to reduce the cost of running a generative AI model while maintaining output quality. Which THREE strategies can help achieve this?

A team wants to use OCI Generative AI Agents to build a RAG system that answers questions from documents stored in OCI Object Storage. What must they create first?

A manufacturing company uses OCI OpenSearch to build a RAG application that retrieves procedural documents. After deployment, queries often return outdated procedures even though the vector index was refreshed. What is the most likely cause?

Which tokenization algorithm is commonly used by models like GPT and BERT, and works by merging frequently occurring character pairs iteratively?

A company is using OCI Generative AI service with a dedicated AI cluster for text generation. They notice that the latency is higher than expected. The cluster is in the Ashburn region, and users are distributed globally. What is the most effective way to reduce latency?

Which parameter controls the randomness of the model's output by adjusting the probability distribution of the next token?

A data scientist is evaluating a summarization model on a news article dataset. They compute ROUGE-L and BLEU scores. The ROUGE-L score is high, but the BLEU score is low. Which of the following best explains this discrepancy?

A developer is using the OCI Generative AI Agents service to build a RAG application. They have uploaded policy PDFs to an OCI Object Storage bucket. What is the next step to make the documents searchable?

In LangChain's Expression Language (LCEL), what does the pipe (|) operator do when connecting components?

A company is deploying a generative AI model for a real-time inference API. To ensure high availability and cost efficiency under variable load, which two configurations should they implement? (Choose two.)

A LangChain application using ChatOCIGenAI is hitting rate limits from the OCI Generative AI service. The developer wants to implement retry logic with exponential backoff. Which approach is most appropriate in LangChain?

Which TWO factors are most important when deciding between on-demand and dedicated AI clusters for OCI GenAI?

An enterprise is deploying an LLM application on OCI and must minimize hallucinations. Which TWO strategies should they implement? (Choose two.)

A team wants to compare the semantic similarity between two sentences using embeddings. Which THREE steps are required?

A LangChain application uses an agent with a calculator tool and a search tool. The agent is supposed to answer a question that requires both arithmetic and web lookup, but it only uses the search tool and gives an approximate answer. Which agent type is MOST likely to correctly combine the tools?

A retail company uses OCI Generative AI to generate product descriptions. They observe the model occasionally produces biased content. Which technique should be applied to reduce bias in model outputs?

Which three statements about transformer architecture are correct? (Choose three.)

A company requires a generative AI service to automatically summarize customer support transcripts. Which OCI Generative AI model is most suitable for this task?

Which OCI service provides pre-trained models for custom text classification without requiring fine-tuning?

A developer is creating a fine-tuning job for a Cohere Command R model using OCI Generative AI. Which TWO of the following are required when submitting the fine-tuning job?

An organization is deploying multiple generative AI models on a shared dedicated AI cluster. They need to isolate resource usage for each model to avoid interference. Which strategy is recommended?

A financial firm deploys a RAG application using OCI OpenSearch. They observe that the LLM sometimes generates incorrect answers that are not supported by the retrieved documents. Which technique directly addresses this issue?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A developer needs to include the conversation history in a prompt for a LangChain chatbot. They want to insert previous exchanges between the user and the AI into the prompt at a specific position. Which component should they use?

A prompt engineer is developing a multi-step reasoning application using the ReAct pattern. The model sometimes outputs incomplete reasoning or forgets to perform an action. Which improvement to the prompt is MOST likely to address this issue?

A prompt engineer wants to reduce the model's tendency to generate overly creative or off-topic responses when summarizing financial reports. Which parameter adjustment is MOST appropriate?

Which of the following is a recognized limitation of large language models?

A team wants to evaluate an LLM's performance on a text classification task. Which metric is most appropriate for a balanced dataset?

A developer notices that an LLM's responses are too verbose. Which parameter adjustment would most effectively reduce verbosity?

A data scientist is fine-tuning a Llama 2 model on a custom dataset for a summarization task. After fine-tuning, the model produces summaries that are too similar to the input text, often copying sentences verbatim. Which adjustment is MOST likely to reduce copying and improve abstractive summarization?

A developer is debugging a RAG pipeline where the LLM frequently ignores retrieved documents and produces hallucinations. Which THREE factors could contribute to this problem?

An enterprise is deploying a chat application using a large language model. Users report that the model sometimes generates toxic or biased responses. Which best practice should be applied to mitigate this issue?

A prompt engineer is iteratively refining a prompt for a summarization task. Which THREE practices should she adopt to improve prompt performance systematically?

You are using the OCI Generative AI Playground with a Cohere Command R model. You want the model to generate more varied and creative responses. Which parameter should you increase?

In LangChain, what is the purpose of the LCEL (LangChain Expression Language) | operator?

A prompt engineer notices that the model's output frequently repeats the same phrases. Which parameter adjustment is MOST likely to reduce this repetition?

A startup wants to quickly prototype a chatbot using OCI Generative AI service. They have no prior experience with OCI. They want to test different models and parameters without writing any code and within a few minutes. They also want to save prompts and compare results. Which approach should they use?

An organization is implementing a RAG system using OCI GenAI. Which two are best practices for optimizing retrieval and generation? (Choose two.)

Which OCI Generative AI model is designed to rerank and improve the relevance of documents retrieved by a search system?

A prompt engineer wants to use chain-of-thought prompting to improve arithmetic reasoning. Which TWO steps are essential for implementing this technique?

A team is deploying a RAG system that uses OCI Generative AI to answer questions about internal HR policies. The system must comply with data residency requirements: all data processing must stay within a specific OCI region. The team uses OCI Data Science for orchestration. Which architecture BEST meets the data residency requirement?

A developer wants to integrate OCI GenAI into a Java application. Which SDK should they use?

A company is designing a generative AI solution on OCI that must comply with data privacy regulations. Which three best practices should they follow? (Choose three.)

Which THREE are valid ways to interact with OCI Generative AI?

A developer wants to compose a LangChain pipeline using the LCEL (LangChain Expression Language) to combine a prompt template, a model, and an output parser. Which operator is used for this composition?

A data scientist is evaluating different models for a summarization task. Which two metrics are commonly used to evaluate the quality of generated summaries?

A data scientist needs to fine-tune a model using OCI Generative AI. They have prepared a dataset in JSONL format with prompt/completion pairs. The fine-tuning job is configured with the T-Few technique. What is a key characteristic of T-Few fine-tuning?

A team has deployed a generative AI model using OCI Data Science model deployment. The endpoint is behind a load balancer. Users report that after 5 minutes of inactivity, the first request takes over 30 seconds to respond, while subsequent requests are fast. What is the most likely cause and solution?

Refer to the exhibit. The output is very short and cuts off mid-sentence. Which parameter is most likely the cause?

A developer notices that a text generation model produces repetitive phrases when using greedy decoding. Which sampling strategy would best introduce controlled randomness to reduce repetition while maintaining coherence?

A developer wants to integrate generative AI capabilities into an application using REST API calls. Which OCI Generative AI service endpoint should they use for text generation?

A team deploys a generative AI model endpoint and notices intermittent 429 Too Many Requests errors. The endpoint is configured with auto-scaling using a dedicated AI cluster. What is the most likely cause?

A company uses OCI Generative AI service to power a chatbot. After deployment, the chatbot starts generating inappropriate responses. Which action should be taken first?

A team uses OCI Generative AI's summarization feature to condense legal documents. The summaries sometimes omit critical clauses. Which parameter adjustment is most likely to improve completeness?

A company uses OCI Generative AI Agents to build a RAG application that answers questions from documents stored in OCI Object Storage. The knowledge base is updated daily. Which step is necessary to ensure the agent incorporates the latest documents?

A financial firm wants to use OCI Generative AI for contract analysis. They need to reduce costs by using a smaller, specialized model. Which approach should they take?

A company needs to generate embeddings for a large corpus of legal documents to enable semantic search. Which type of model should they use?

An organization is deploying a RAG application with Oracle AI Vector Search. They need to ensure that the vector index supports low-latency queries and can handle updates to the underlying documents (inserts, deletes, modifications) without significant performance degradation. Which two index features should they consider? (Choose TWO.)

Which OCI Generative AI service component is designed to convert text into vector representations for use in semantic search?

A developer is using the Cohere Command model via OCI Generative AI and wants to ground responses in a specific uploaded document. Which syntax should be used in the preamble to enable document-grounded generation?

A company is designing a generative AI application using OCI Generative AI. Which two factors should be considered when selecting the appropriate model? (Choose two.)

A retail company uses OCI Generative AI Agents to power a product recommendation chatbot on their e-commerce website. The chatbot is integrated with a knowledge base containing product descriptions, customer reviews, and inventory data. Recently, the chatbot has started recommending out-of-stock products frequently, leading to customer frustration. The development team verified that the knowledge base is updated in real-time with inventory data. The chatbot's configuration uses a chunking strategy with a chunk size of 500 tokens and an overlap of 50 tokens. The team suspects the issue is related to how the agent retrieves information. They have access to OCI Logging and Monitoring. Which course of action should the team take first?

A company wants to use OCI Generative AI to summarize customer support tickets. They need to ensure that the model does not output any sensitive information. Which technique should they implement?

A developer is getting a 401 Unauthorized error when calling the OCI Generative AI inference API. What is the most likely cause?

A developer is using the OCI GenAI Chat API to build a multi-turn customer support chatbot. They want the assistant to always introduce itself as 'SupportBot' and never mention being an AI. How should they configure the API call?

A company wants to use OCI Generative AI Agents to build a question-answering system over documents stored in OCI Object Storage. Which component acts as the knowledge source for the agent?

You need to convert a set of customer support tickets into vector embeddings for a similarity search application. Which OCI Generative AI model should you use?

A prompt engineer is designing a system that generates SQL queries from natural language. The model sometimes produces unsafe queries (e.g., DROP TABLE). Which constraint in the system prompt would BEST mitigate this risk?

A data scientist needs to fine-tune a model on OCI Generative AI. Which of the following is a required parameter in the fine-tuning request?

Which two are essential components of the Transformer architecture? (Select TWO)

Refer to the exhibit. What is the solution?

A regulatory compliance team needs to restrict access to the OCI Generative AI service so that only users in the 'AI_Engineers' group can create fine-tuning jobs and endpoints. Which IAM policy statement should be used?

A company deploys a large language model on a dedicated AI cluster with 4 nodes. The model requires 128 GB of memory per instance, but the nodes have only 64 GB each. During inference, the nodes experience out-of-memory errors. What is the best solution?

A company uses OCI Generative AI Service to build a chatbot for customer support. They notice that the model sometimes generates inappropriate responses. What is the MOST effective way to mitigate this without retraining the model?

A team is deploying a generative AI model using OCI Functions for serverless inference. They are experiencing cold start latency of over 10 seconds for the first invocation after idle periods. What is the best strategy to reduce cold start latency?

Which TWO are best practices for securing a generative AI endpoint on OCI? (Select TWO)

A healthcare organization plans to deploy a RAG application on OCI that handles sensitive patient data. They require that all LLM inference and embedding processing happen within a controlled environment to avoid data leakage to public endpoints. Which OCI feature should they use?

A data scientist is creating a fine-tuning job in OCI Generative AI. They have prepared a JSONL dataset with prompt/completion pairs. What is the correct format for each line in the JSONL file?

A prompt engineer is using the ReAct pattern to enable the model to reason and act (e.g., call tools). Which THREE components are essential in the prompt to implement ReAct correctly?

A company needs to classify customer support tickets into 20 categories. They have a labeled dataset of 50,000 examples. They want to use OCI Generative AI Embedding API to generate embeddings, then train a classifier. Which input type should they use for the embedding API when processing the training examples?

During multi-turn conversation with an OCI GenAI model, the model repeats user messages from earlier turns. What is the most likely cause?

Which TWO actions are best practices when deploying a RAG application using OCI OpenSearch and OCI Generative AI?

A company wants to use OCI Generative AI service to generate marketing copy that adheres to brand guidelines. Which technique should they use?

A prompt engineer is testing a new prompt for a Q&A system. The prompt includes ambiguous wording that causes the model to answer inconsistently. Which TWO steps should the engineer take to resolve this? (Choose two.)

A machine learning engineer is deploying a fine-tuned Llama 2 model on OCI Data Science model deployment. The deployment fails with an error: 'Model artifact exceeds the maximum allowed size of 10 GB.' The model files total 12 GB. What is the best approach to resolve this?

A company uses an LLM to generate product descriptions. The outputs are consistently too verbose and include irrelevant details. The prompt includes a simple instruction: 'Describe the product.' Which adjustment to the prompt is most likely to yield concise, relevant descriptions?

A data scientist is building a text summarization system using an LLM. They want to evaluate the model's output against human-written summaries. Which TWO metrics are most appropriate for this evaluation? (Choose two.)

An e-commerce company fine-tuned a Cohere Command model on their product catalog to generate product descriptions. During inference, they notice the model outputs are too repetitive: it often repeats similar phrases across different products, and the descriptions lack diversity. The team wants to increase the variety of the generated text without sacrificing relevance. They are currently using temperature=0.8, top_p=0.9, frequency_penalty=0, and presence_penalty=0. Which parameter adjustment should they make to most effectively increase diversity?

A financial institution uses OCI GenAI to power a customer support chatbot. The compliance team requires that responses are strictly consistent with regulatory guidelines and approved responses. The company has a curated set of question-answer pairs that cover common scenarios. They want to ensure that the chatbot never deviates from these approved answers. The data science team is considering various approaches to enforce this consistency. Which approach is most effective?

A company is using Oracle AI Vector Search in Oracle Database 23ai for semantic search over product descriptions. They need to create an index that supports approximate nearest neighbor search with high recall and moderate indexing time. Which index type and parameters should they choose?

A team fine-tuned a Cohere Command R model using the T-Few technique on a dataset of JSONL prompt/completion pairs. After deployment, they observe that the model's responses are too repetitive. Which parameter adjustment in the OCI Generative AI Playground would BEST address this issue?

A data scientist wants to deploy a fine-tuned LLM on OCI for inference with low latency. Which OCI service should they use?

A data scientist receives an error when calling the embed_text API: "InvalidRequest: input too long". What is the most likely cause and solution?

An organization maintains a library of prompt templates for various use cases. Which three practices are essential for effective prompt management? (Choose three.)

An organization needs to deploy a model that can both understand and generate text, such as for a translation task where the input is in English and output is in French. Which model architecture is most suitable?

Which THREE factors should be considered when choosing between fine-tuning a model and using a pre-trained model with prompt engineering? (Select three.)

A healthcare startup is building a chatbot that retrieves patient treatment guidelines using OCI Generative AI Service and OCI OpenSearch. They require that all retrieved documents are from approved sources only and that the system can explain which source was used for each response. Which combination of features should they implement?

An enterprise is deploying a generative AI model that must comply with data residency regulations. Which two configurations should they implement? (Select TWO.)

A prompt engineer is designing a ReAct pattern prompt to enable an LLM to use external tools. Which of the following is a key characteristic of the ReAct pattern?

A developer is building a LangChain RAG pipeline with OCI Generative AI. Which TWO components are needed to create embeddings from documents and store them for retrieval?

A company wants to build a customer support chatbot using OCI Generative AI. They have a large number of historical support tickets. Which approach is most effective for leveraging this data to improve the chatbot's responses?

Which of the following metrics is most suitable for evaluating a translation model's output against multiple reference translations?

A company is deploying a fine-tuned Cohere model on OCI Generative AI service for real-time inference. They need to ensure low latency even during demand spikes. Which configuration should they prioritize?

A company is deploying a generative AI model on OCI for an internal application that must comply with strict security policies. The model will be accessed by a limited group of users. Which three actions should the administrator take to ensure security? (Choose three.)

An LLM application generates product descriptions. The output is sometimes repetitive (e.g., 'innovative' appears multiple times). Which parameter adjustment is MOST likely to reduce this repetition without harming creativity?

A company is using OCI Generative AI Agents to build a customer support assistant. They have uploaded product manuals to OCI Object Storage. Which two components are required to create the agent? (Select TWO)

A data scientist observes that their fine-tuned LLM performs well on training data but generates repetitive and dull responses in production. What is the most likely cause and best solution?

A security administrator wrote the above IAM policy for a compartment named MyCompartment. Users in the GenerativeAIUsers group can successfully list dedicated AI clusters and models in MyCompartment, but when they try to create an inference endpoint using a model from a different compartment (SharedModels), they get an authorization error. What is the most likely missing policy statement?

A data scientist is designing a prompt to generate a structured report with sections for Summary, Findings, and Recommendations. Which output format specification in the prompt would be MOST effective?

A data scientist is debugging a RAG system where the generated answers are not relevant to the retrieved documents. Which TWO factors are MOST likely causing this issue?

A global enterprise is deploying a generative AI application that requires high availability across multiple OCI regions. The application must automatically fail over to a secondary region if the primary region becomes unavailable. What is the recommended architecture to achieve this?

A data scientist is preparing to fine-tune a foundation model on OCI. Which two actions should they take to optimize costs? (Select TWO.)

During fine-tuning a model using T-Few in OCI Generative AI, the job fails with a 'dataset format error'. The training dataset is a JSONL file. Which of the following is the MOST likely cause?

Which evaluation metric is designed to measure the overlap of n-grams between a generated summary and a reference summary, focusing on recall of content words?

What is the PRIMARY purpose of the 'stop sequences' parameter in text generation?

A developer uses the ReAct agent in LangChain with a calculator tool and a search tool. The agent receives the question: 'What is the population of Paris multiplied by 3?' The agent first calls the search tool to find the population, then calls the calculator tool to multiply it by 3. Which component is responsible for deciding the sequence of tool calls?

A team is implementing a conversational chatbot that needs to remember a user's previous messages within the same session. They are using LangChain with OCI Generative AI. Which memory type and persistence approach should they choose for session-only memory?

A developer is using LangChain to build a RAG pipeline with Oracle Database 23ai as the vector store. Which LangChain wrapper should they use to create embeddings and store them in the database?

A team wants to use an LLM to answer questions about a private codebase that is updated hourly. They cannot afford to fine-tune every hour. Which OCI feature or approach is most suitable?

A practitioner is using a Cohere Command model on OCI for a translation task. They notice that the output is often incomplete and cuts off mid-sentence. Which parameter should they adjust to address this?

Which TWO components are essential in a Retrieval-Augmented Generation (RAG) pipeline?

A team is fine-tuning a large language model for a domain-specific Q&A application. After fine-tuning, they observe that the model performs well on the training distribution but struggles with out-of-distribution (OOD) questions. Which approach would best improve OOD robustness?

A team is troubleshooting a chatbot that sometimes outputs harmful content despite having a system prompt with safety instructions. Which THREE measures should they implement to reduce the risk?

Which THREE factors are important when designing a multi-turn conversational agent using OCI Generative AI Agents?

A developer is testing the OCI Generative AI API by sending a request to generate text using the Cohere Command R model. The request returns the following error: 'The model 'cohere.command-r-08-2024' is not available in this region. Please check the model availability in your region.' The developer is using the us-ashburn-1 region. What is the most likely cause of this error?

A practitioner needs to choose a pre-trained model for a sentiment analysis task on customer reviews. The model must be efficient for inference and capable of handling multiple languages. Which architecture is MOST suitable?

A data scientist deployed a fine-tuned Llama 2 7B model on OCI Model Deployment with a single VM.GPU.A10.1 shape. Users report average latency of 3 seconds per request, which is too high for the intended real-time application. The model is used for short text generation (max 128 tokens). The data scientist wants to reduce per-request latency without significant accuracy loss. Which action would be most effective?

Which of the following is a distinguishing feature of in-context learning compared to fine-tuning?

You are a cloud architect at a global e-commerce company. The company is building a RAG-based product support chatbot using OCI Generative AI Service and OCI OpenSearch. The chatbot must answer customer questions in real-time by retrieving from a product knowledge base containing over 10 million documents. The current architecture uses a single vector index with all documents, and the LLM (Cohere Command R+) returns answers in English only. The team observes that queries from non-English customers often return irrelevant results, and the chatbot sometimes fails to generate answers within the 5-second SLA. The leadership wants to support 10 languages and reduce the average response time to under 3 seconds. You need to propose a solution that improves both relevance and latency. Which course of action should you take?

What is the key advantage of multi-head attention over single-head attention in transformer models?

A startup is building a chatbot for customer support using OCI Generative AI Service. The chatbot needs to answer queries about product features based on a knowledge base of product documentation. Which configuration is most appropriate for this use case?

A retail company wants to generate product descriptions from attribute data. They have no prior AI experience. Which approach is most appropriate?

An AI application uses chain-of-thought prompting to solve math problems. The team observes that the model sometimes arrives at correct answers but with flawed reasoning. Which technique can specifically help by aggregating multiple reasoning paths?

A company is deploying a large language model for a customer service chatbot. The model needs to understand industry-specific jargon and maintain low latency. Which approach best balances these requirements?

A developer is using OCI Generative AI Service to generate product descriptions. The outputs are often too generic and lack brand-specific tone. The developer has a small set of 20 high-quality example descriptions. What is the most efficient approach to improve output quality?

A developer is using a large language model to generate code snippets. The model often produces code that is syntactically correct but functionally incorrect. What is the most effective way to improve the functional correctness of the generated code?

A team is building an agent using LangChain that needs to perform calculations and search the web for current information. Which combination of tools and agent type should they use?

What is the primary difference between pre-training and fine-tuning in the context of large language models?

A team fine-tunes an embedding model for a legal document RAG system but observes low retrieval recall. Which technique is most likely to improve recall?

A developer is using OCI Generative AI with a Cohere Command model for text generation. They want the output to be more creative and diverse, but still relevant. Which sampling strategy should they use?

An organization requires low-latency inference for a custom fine-tuned model deployed on OCI Generative AI. The model must be isolated from other tenants. Which infrastructure choice meets these requirements?

Refer to the exhibit. A developer runs the command and immediately tries to use the endpoint. The application fails with an error indicating the endpoint is not active. What is the most likely reason?

A team uses Cohere's `rerank` endpoint after initial retrieval to improve result quality. What is the main benefit of reranking?

Which of the following is an example of a prompt template?

A customer support company uses Cohere Command on OCI to answer user queries. They have enabled grounding with a knowledge base of product manuals. However, for about 20% of queries, the model provides incorrect product recommendations that are not in the manuals. The team has verified the knowledge base is up to date. What is the most likely cause and solution?

Which component of the Transformer architecture allows the model to focus on different parts of the input sequence when generating each output token?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A developer wants the model to generate a bullet list of steps to troubleshoot a network issue. Which output format specification should be included in the prompt?

A user wants to access the OCI Generative AI service programmatically. Which credential method is recommended for use in a production application running on OCI Compute?

What is the primary goal of chain-of-thought prompting?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A developer is using tree-of-thought prompting to solve a complex planning problem. Which THREE characteristics are typical of tree-of-thought?

What is the primary purpose of setting the 'top-k' parameter in an LLM?

Refer to the exhibit. A developer has set this policy to allow an OCI Data Science session to generate embeddings. However, the API call returns a 403 Forbidden. Which of the following is likely missing?

Which two actions are required when deploying a custom fine-tuned model using the OCI Generative AI service? (Choose two.)

Which THREE parameters can be adjusted to reduce repetition in generated text? (Choose three.)

Refer to the exhibit. What is the primary reason the response is incomplete?

An OCI practitioner is comparing BERTScore with traditional n-gram metrics (ROUGE, BLEU) for evaluating summarization. Which THREE statements about BERTScore are true?

What is the primary purpose of setting a low temperature (e.g., 0.1) when generating text with an LLM?

An organization wants to deploy a model that can summarize long financial reports (5000+ tokens) without losing context. Which model architecture is best suited for this requirement?

What is the main advantage of using chain-of-thought (CoT) prompting over standard few-shot prompting for complex reasoning tasks?

A company deploys a fine-tuned model on an OCI Generative AI dedicated AI cluster. After deployment, they observe high latency during peak hours. The cluster has only one replica. Which action would most effectively reduce latency without increasing cost unnecessarily?

A company is deploying a large language model in a customer-facing chatbot. The model's responses must be both accurate and safe. Which combination of techniques should be employed?

Which THREE are common prompt failures that can degrade model performance?

Which TWO measures can help reduce the risk of generating toxic or unsafe content when using OCI Generative AI Service?

A developer is building a LangChain application that uses OCI Generative AI service. They want to implement streaming responses from the LLM to improve user experience. Which TWO actions are necessary to enable streaming?

A prompt engineer wants to generate a JSON object from an LLM response. Which prompt component is MOST critical to ensure the output is valid JSON?

What is the primary benefit of using a Dedicated AI Cluster over On-Demand serving for deploying generative AI models on OCI?

Which of the following best describes the role of a Retriever in a LangChain RAG pipeline?

A developer is using the OCI Generative AI Chat API with a system prompt to guide the assistant's behavior. They notice that after a few turns, the assistant starts ignoring the system instructions. What is the MOST likely cause?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A team is fine-tuning an LLM on OCI Generative AI for a domain-specific task. They have a dataset of 10,000 labeled examples. What is a best practice to avoid catastrophic forgetting during fine-tuning?

Which TWO are advantages of using LoRA for fine-tuning?

A data science team is using OCI Data Science to fine-tune a model. They notice that training jobs are failing due to out-of-memory errors on the notebook session. What should they do to resolve this?

An LLM-based application must comply with data privacy regulations by not memorizing personally identifiable information (PII). Which technique best reduces memorization of PII?

A financial services company has deployed a custom fine-tuned model using OCI Generative AI service on a dedicated AI cluster for automated report generation. They use a Python application that sends prompts via the OCI SDK. Recently, they started seeing 429 Too Many Requests errors intermittently. The dedicated cluster has 2 replicas and the application is making about 100 requests per second. The cluster's documented throughput is 50 requests per second per replica. The company has not set up any throttling limits. What is the most likely cause of the 429 errors?

A financial services company is concerned about data privacy when using OCI Generative AI service for processing sensitive customer data. They want to ensure that their data is not used to improve the model and is encrypted at rest and in transit. Which combination of OCI features should they implement?

A company is deploying a RAG system for internal document search using OCI OpenSearch as the vector store. Users report that queries about recent policy changes return no results, even though the new policies were ingested. Which configuration is most likely missing?

A developer is building a RAG pipeline with LangChain. They have loaded PDF documents with PDFLoader. Which TWO steps must they perform before indexing the documents into a vector store?

Which OCI Generative AI parameter controls the diversity of generated text by increasing the probability of less likely tokens?

A developer is building a multi-turn chatbot using the OCI Generative AI Chat API. Which THREE parameters or features should they configure to maintain coherent conversation history?

A company wants to deploy a private instance of a large language model on OCI for sensitive data processing. What is the recommended approach?

Which THREE are known challenges when deploying large language models in production?

A company is building a document summarization pipeline using OCI Generative AI. They need to summarize thousands of legal documents efficiently. Which approach minimizes cost while maintaining quality?

An organization needs to select a tokenisation algorithm for a multilingual LLM that will process English, Chinese, and Korean text efficiently. Which tokenisation method is BEST suited for this requirement?

A data scientist is building a RAG pipeline on OCI. Which TWO components are essential for the retrieval step?

You are a data scientist at a legal firm. The firm uses OCR to digitize court documents and then indexes them in OCI OpenSearch for a RAG application. The application uses OCI Generative AI Service (Cohere Command) to answer questions about case law. Recently, the team noticed that the answers are often factually incorrect or include information not present in the retrieved documents. After reviewing the pipeline, you find that the chunking strategy splits documents into 512-token chunks with 128-token overlap. The embedding model is Cohere Embed v3 (English), and the retrieval returns the top 5 chunks. The LLM has a context window of 4096 tokens. The team suspects that the chunking strategy is causing loss of context. What is the best course of action to improve answer accuracy?

A data scientist needs to create vector embeddings for a multilingual customer feedback dataset to perform clustering analysis. Which OCI Generative AI embedding model should they choose?

An OCI user observes that their Mistral model produces very repetitive text when temperature is set to 0.9 and top-p to 1.0. Which adjustment is most likely to reduce repetition?

A developer wants to interactively test different prompts and parameters (temperature, top_p, frequency_penalty) with a Cohere Command R model before integrating it into an application. Which tool should they use?

Your team has deployed a fine-tuned GPT-2 model on OCI Model Deployment for a simple text generation API. The model performs text completion for short prompts (e.g., 50 tokens). The endpoint is working but response times are over 10 seconds for these short prompts. The model size is approximately 500MB and you used a VM.Standard.E3.Flex shape (2 OCPU, 16GB RAM). The deployment is in a single replica with no autoscaling. You have verified that the network latency is minimal (<5ms). The model was trained in OCI Data Science using a GPU shape, but during deployment you selected a CPU shape to reduce cost. The model is a transformer-based neural network. You've also confirmed that the deployment is healthy and there are no errors in the logs. The memory usage is within limits. What is the most likely cause of the high latency?

An OCI CLI command above returns embeddings for the phrase 'Hello world'. The developer notices that the embedding vector length is 384 dimensions. However, they expected 768 dimensions. What is the most likely cause?

A user sends an inference request with the JSON parameters shown. They notice the model is returning very short responses. What is the most likely cause?

A company is fine-tuning a Llama model on OCI with dedicated AI cluster. They want to use their own training data stored in Oracle Object Storage. What must they do to ensure the fine-tuning job can access the data?

An LLM generates a response that contains a plausible-sounding but factually incorrect statement about a historical event. This is an example of which known limitation?

A development team wants to generate code snippets from natural language. Which model strategy should they adopt?

A practitioner is choosing a model for a code generation assistant that must run on OCI with low latency. Which THREE considerations are most important?

Which THREE factors directly influence the quality of responses in a RAG system? (Choose three.)

Refer to the exhibit. A developer ran the OCI CLI command shown and received the JSON output. What does the output indicate about the model's confidence and why?

A developer is using OCI Data Science to create a RAG pipeline. They have ingested documents into a vector store using OCI Generative AI's text-embedding model. During testing, they notice that queries return very few results (often 0 or 1) even when the knowledge base contains relevant documents. They have set the top-k parameter to 10. What is the most likely cause?

An application mixes RAG with other data sources. The vector search returns too many irrelevant chunks. What is the best approach to filter them?

An OCI user is comparing two embedding models: one with 768 dimensions and another with 1024 dimensions. Which of the following trade-offs is most relevant?

A prompt engineer is designing a prompt for legal document analysis. The model should output JSON with a specific structure. Which TWO practices are essential to include in the prompt?

A developer wants to implement a simple RAG pipeline using OCI Language's text generation and embedding models. Which OCI SDK method is used to generate embeddings for a text chunk?

A data scientist is using OCI Generative AI to process a large batch of legal documents. The total cost is higher than expected. Which factor is most likely the primary driver of cost?

Which API should a developer use to send a multi-turn conversation history to an LLM, including a system message and previous user/assistant exchanges, using OCI Generative AI?

A developer is using the Cohere Command R model with a preamble set to "You are a helpful assistant." The user message contains a question. The model's response is factual but lacks detail. To encourage more comprehensive answers, which modification should be made?

A data scientist is using OCI Data Science with the Generative AI service to fine-tune a Cohere Command model on a custom dataset of customer support tickets. After training, the model produces poor, irrelevant responses. What is the most likely cause?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A developer is using Cohere Command R with document-grounded generation. Which THREE elements must be included in the prompt to enable effective document grounding?

Which THREE of the following are core LangChain components?

A prompt engineer wants the LLM to adopt the persona of a 'friendly customer support agent' for all interactions. Which approach is most effective?

You want to test different prompts and parameters (temperature, max tokens) for a summarization task using a foundation model without writing any code. Which OCI tool should you use?

Which TWO of the following are best practices when implementing a RAG application using OCI OpenSearch as a vector store?

A team is building a LangChain agent that needs to answer questions using both a company-internal knowledge base (stored in Oracle AI Vector Search) and live web search. Which THREE components should they include in the agent setup?

An organization wants to use OCI Generative AI for a multilingual translation task. They need high quality and must avoid biases present in the training data. Which THREE strategies should they consider? (Select THREE.)

An organization wants to deploy a chatbot that uses a custom fine-tuned model. They have provisioned a Dedicated AI Cluster with 4 model units. During peak hours, they observe high latency and want to reduce it. What is the most cost-effective change?

Which model architecture is used by BERT for natural language understanding tasks?

A company has a large dataset of legal documents in multiple languages. They need to find documents semantically similar to a query. Which step is essential for this task?

A researcher wants to compare two summarization models. Model A achieves a higher ROUGE-L score than Model B, but human evaluators prefer Model B's summaries. Which of the following is the MOST likely reason?

A company wants to use LangChain to build a chatbot that remembers previous conversations across sessions. Which TWO components should they use together?

Which three characteristics of LLMs can lead to hallucinations? (Select THREE)

A company wants to use Cohere Command for a customer support chatbot that references a knowledge base. The chatbot must maintain conversational context across multiple turns. Which TWO Cohere-specific features should they use?

A data scientist is using a large language model to summarize customer support tickets. The model occasionally generates summaries that include hallucinated details not present in the original ticket. Which technique would best reduce hallucinations while maintaining summary quality?

A company wants to build a sentiment analysis system for customer reviews. They have a labeled dataset of 10,000 reviews. Which approach is most cost-effective and likely to yield good performance?

Which THREE of the following are supported capabilities of OCI Generative AI Service?

A machine learning engineer evaluates OCI Generative AI for a real-time content generation application. They need to meet a SLAs of 99.9% availability. Which deployment architecture satisfies the requirement with the lowest cost?

A team is using LangChain's ConversationalRetrievalChain with ConversationBufferMemory to build a chatbot. After a few turns, the chatbot starts repeating information from earlier messages. What is the MOST likely cause?

A developer wants to deploy a custom generative AI model that was trained using OCI Data Science. Which service should they use to expose the model as an API endpoint?

A healthcare company is using OCI Generative AI to analyze patient records and generate clinical summaries. The company must comply with HIPAA regulations, which require that all protected health information (PHI) be encrypted at rest and in transit, and that access be logged and audited. The current architecture uses an OCI Data Science model deployment with a public endpoint. The model is stored in an OCI Object Storage bucket that is publicly accessible for testing. The company is now moving to production. The compliance officer has flagged the following issues: (1) The model endpoint is publicly accessible. (2) The bucket containing the model is public. (3) No audit logs are enabled. The company wants to remediate these issues while maintaining the ability to invoke the model from on-premises applications via a secure connection. Which set of actions should the architect take?

A company is using OCI GenAI with a Dedicated AI Cluster to serve a large language model for real-time chat applications. They notice high inference latency (average 2 seconds per response) and want to reduce it to under 500 milliseconds without significantly degrading the quality of responses. The cluster is configured with NVIDIA A100 GPUs. The model is the base Cohere Command model (52B parameters). They have explored increasing batch size, but that increases latency for interactive use cases. Which action should they take?

Which OCI Generative AI model family is specifically designed to convert text into vector embeddings for semantic search and clustering tasks?

A data scientist is deploying a custom generative AI model using OCI Data Science. After deploying the model to an endpoint, they notice that inference requests are failing with a timeout error when the payload size exceeds 1 MB. What is the most likely cause and solution?

Your team is deploying a generative AI model for a clinical decision support system. The model must meet HIPAA compliance requirements. You have trained a model using OCI Data Science and now need to deploy it so that patient data is protected. The application requires real-time inference. Which set of actions should you take to ensure compliance while maintaining low latency?

A company wants to create a chatbot that answers questions based on a large internal document set that is updated weekly. They have limited ML expertise. Which approach is recommended?

A company uses OCI GenAI to build a content moderation system that filters toxic language in user-generated comments. They have a small labeled dataset of 1,000 comments (500 toxic, 500 non-toxic) and need an efficient solution that balances accuracy, cost, and latency. They are considering different model options: fine-tuning a large LLM (e.g., Cohere Command), using a pre-trained LLM with prompting, fine-tuning a smaller BERT-based classifier, or building a rule-based system. The team has moderate ML experience and wants to deploy using OCI Data Science. Which approach is most efficient for this binary classification task?

A company wants to use OCI Generative AI service to automatically generate product descriptions for an e-commerce catalog. They have 10,000 products. What is the best approach to ensure high-quality, consistent descriptions?

Which THREE are essential steps in the prompt engineering process for an LLM?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A company needs to ensure that only authorized users can invoke an endpoint for a generative AI model. Which OCI feature should be used to control access?

A company needs to generate vector embeddings for a multilingual document set to support semantic search across English and French documents. Which embedding model should they use?

A data scientist is fine-tuning a model on OCI Generative AI to generate code comments. They use a dataset of 10,000 examples. After fine-tuning, the model generates comments that are too similar to the training data and lack generalization. What is the most likely cause?

A healthcare company is deploying an OCI Generative AI service to summarize patient notes. They have recently moved from a managed serving endpoint to a dedicated AI cluster to ensure data privacy. The fine-tuned model is deployed on a dedicated cluster in the US West region. Users report that the summarization responses are now slower and occasionally timeout. The IT team checks the metrics: the cluster has 1 replica and CPU utilization is at 90%. The Object Storage bucket containing the model artifacts is in the same region. They have increased the timeout in their client configuration to 120 seconds, but still get timeouts. What should they do first to address the issue?

An LLM is being used to answer customer queries about a product catalog. The answers are fluent but sometimes include plausible-sounding but incorrect product details. What is this phenomenon called, and which technique is most effective to mitigate it?

In the OCI Generative AI Playground, a developer wants to control how creative the model responses are. Which parameter should they adjust?

A company wants to use OCI Generative AI Agents to create a RAG-powered customer support system. Which THREE components are essential for the agent to work?

A data scientist needs to fine-tune a Llama 3 model for a legal document classification task. They have a dataset of 10,000 labeled examples. Which fine-tuning technique available in OCI Generative AI is most suitable for efficiently adapting the model with limited computational overhead?

An OCI user observes that their embedding model returns vectors that are not normalized, and they want to compute cosine similarity between two text embeddings. What should they do?

An AI developer is building a document Q&A application using LangChain and OCI Generative AI. They need to split large PDF documents into smaller chunks before embedding. Which text splitter should they use to ensure splits respect sentence boundaries while also controlling chunk size?

A developer uses OCI Generative AI's chat endpoint with a system message placed after user messages. The model ignores the system message. What is the most likely reason?

Which TWO are required components to implement a basic RAG system using OCI services? (Choose two.)

A prompt engineer is testing different versions of a prompt to improve accuracy on a classification task. Which practice is most appropriate for systematic refinement?

A developer wants to call the OCI Generative AI service from a Python application running on an OCI Compute instance. Which method is the most secure for authenticating the API calls?

Which of the following is a decoder-only model architecture?

A company's AI system uses RAG to answer customer questions. Users often get incomplete answers because the retrieved chunks do not contain all relevant information. Which step in the RAG pipeline is most likely the issue?

An organization wants to deploy a generative AI chatbot using OCI Generative AI service. The chatbot must comply with data residency requirements by ensuring that all data processing occurs within a specific geographic region. What is the best practice to achieve this?

A company is deploying a LangChain agent that uses a custom tool to query an external API. The agent must handle rate limits gracefully. Which approach should the developer implement?

A team is building a code generation assistant and needs to choose between fine-tuning a base LLM or using in-context learning with a few examples. They have 500 high-quality code examples. The assistant must generate code for a wide variety of tasks. Which approach is BETTER and why?

A team is using OCI Generative AI Agents to build a customer support bot. The bot sometimes generates answers that contradict the knowledge base. What is the most likely cause?

An organization needs to deploy a fine-tuned model for real-time inference with strict latency requirements. They have provisioned a Dedicated AI Cluster with 2 model units. Which statement about this setup is accurate?

A company uses OCI Generative AI to power a chatbot for customer support. They notice that the model's responses sometimes contain factual inaccuracies. Which strategy would best reduce hallucination?

Refer to the exhibit. The dashboard shows latency grouped by modelId, but some points are missing for certain modelIds. Which of the following is the most likely reason?

A company deploys a fine-tuned Llama 2 model using OCI Generative AI service. They want to ensure low-latency inference for a real-time chat application. Which deployment option should they use?

Which TWO techniques are commonly used to reduce the memory footprint of LLM inference?

Which TWO factors are most likely to cause hallucinations in LLMs?

Which OCI Generative AI model family is optimized for generating text embeddings that capture semantic meaning for tasks like clustering and classification?

A prompt engineer is designing a system that must extract structured data from unstructured text. The model occasionally outputs extra text beyond the required JSON. Which parameter should be adjusted to enforce strict output format?

A company wants to implement a retrieval-augmented generation (RAG) chatbot using OCI Generative AI Agents. Which TWO services or components are required for this solution?

Which TWO techniques can help reduce bias in LLM outputs?

A developer is using a Cohere Command model via OCI Generative AI. They want the model to generate responses strictly in JSON format for a specific task, but the model sometimes outputs additional explanatory text. Which prompt engineering technique is MOST effective?

In OCI Generative AI, when using the Cohere Command model, which parameter is used to discourage the model from repeating the same phrases?

A developer is using the OCI Generative AI Chat API to create a customer support bot. They want the bot to maintain a consistent personality and follow specific guidelines. Which TWO settings should they use?

A data scientist needs to fine-tune a large language model on a custom dataset of 10,000 prompt-completion pairs. They want to minimize cost while still updating the model effectively. Which fine-tuning technique is used by OCI Generative AI service?

A developer is troubleshooting low recall in a vector search. Which THREE factors should be checked? (Choose three.)

A data scientist is designing a prompt for code generation and needs to reduce the likelihood of the model generating incorrect or hallucinated code. Which two parameter adjustments are most effective? (Choose two.)

A developer is using the Cohere Command model for text generation and wants to ensure the output is deterministic for testing purposes. Which sampling strategy should they use?

A team is building a Retrieval-Augmented Generation (RAG) pipeline using OCI Generative AI. They need to store and retrieve document embeddings for semantic search. Which OCI service is most appropriate as the vector store?

Which Oracle AI Vector Search index type is designed for approximate nearest neighbor search and uses a navigable small world graph?

Which prompting technique involves providing the model with a small set of input-output examples within the prompt to guide its behavior?

A team is fine-tuning a foundation model on a large dataset stored in OCI Object Storage. They want to minimize data transfer costs. What is the best practice for locating the storage?

A company is deploying a multi-language chatbot using OCI Generative AI Service. The chatbot must support English, Spanish, and French. The team finds that responses in Spanish are less accurate than in English. They have a small bilingual dataset. What is the best approach?

A company is using OCI Generative AI for a RAG-based code assistant. They index source code repositories into a vector store. Developers report that the assistant often suggests deprecated APIs or outdated code snippets, even though the latest code is in the repository. The index was built a week ago and has not been updated. They plan to set up incremental updates. However, they notice that even after re-indexing the latest commits, the issue persists. What is the most likely oversight?

Refer to the exhibit. A data scientist received this output after submitting a fine-tuning job. What is the most effective change to resolve the out-of-memory error?

A developer is evaluating OCI GenAI model families. Which three are correct characteristics of the available models? (Choose three.)

A company fine-tunes an LLM on internal support tickets. After deployment, the model hallucinates company-specific product names. What is the most effective mitigation?

A data scientist is designing a RAG pipeline using LangChain and Oracle AI Vector Search. They want to ensure that the retrieved documents are diverse and not overly similar to each other. Which TWO approaches can achieve this?

A healthcare startup is building a chatbot to answer patient inquiries using a large language model (LLM) deployed on OCI Data Science AI Quick Actions. The chatbot must comply with HIPAA regulations, so all patient data must remain within the OCI tenancy and never be sent to third-party APIs. The team has fine-tuned a Llama 2 7B model on de-identified medical records using OCI Data Science notebooks. The model is deployed as a managed endpoint via AI Quick Actions. Early testing shows that the chatbot sometimes generates responses containing specific patient names or dates of birth that were present in the fine-tuning dataset. Moreover, the model occasionally hallucinates medication dosages that are not medically accurate. Which course of action should the team take to address both issues while maintaining HIPAA compliance?

You deployed a generative AI model on OCI Model Deployment with autoscaling configured based on average CPU utilization. The model is a large language model that heavily utilizes the GPU. During peak hours, the scaling is too slow to keep up with demand, resulting in high latency for users. You want to improve the responsiveness of autoscaling. Which change should you make?

An OCI GenAI practitioner wants to deploy a model that can generate code from natural language descriptions. Which type of model is most suitable?

A developer is deploying a fine-tuned model using OCI Generative AI service. They want to use a custom container image for inference. Which statement is true?

Which of the following best describes the role of the self-attention mechanism in a Transformer model?

A team is optimizing a RAG pipeline for OCI Generative AI. They observe that the model's responses are verbose and often include irrelevant details from the retrieved chunks, reducing user satisfaction. They have already tuned the prompt template. What is the most effective next step?

A developer is using LangChain's LCEL to build a RAG pipeline. They want to add streaming of the final answer to the user. Which LCEL feature enables streaming output from the model?

Which TWO of the following are valid similarity metrics used in vector search?

A developer is using the OCI Generative AI Chat API to build a multi-turn conversational agent. They want the model to remember previous exchanges within the same session. How should they manage conversation history?

A company uses OCI Generative AI Service to generate personalized email content. They need to ensure that personally identifiable information (PII) is not included in the model's training data. What should they do?

Refer to the exhibit. An administrator receives the error shown when attempting to deploy a custom model. What is the most likely cause?

An administrator needs to ensure that only specific users in the finance department can invoke a generative AI model deployed on OCI. Which IAM policy should be used?

A healthcare company is building a RAG-based chatbot to answer patient queries using medical documents stored in OCI Object Storage. They use OCI Generative AI service with Cohere Command R+ model and OCI OpenSearch as the vector database. The chatbot is deployed on OCI Compute with a Flask application. After deployment, the latency for each query is 15-20 seconds, which is unacceptable. Logs show that the embedding generation step (using OCI Generative AI embedding API) takes 8-10 seconds, and the vector search in OpenSearch takes 5-7 seconds. The team has already enabled connection pooling and increased the compute instance shape to the maximum allowed. Which action would MOST effectively reduce the overall latency?

In LangChain, which component is responsible for connecting a language model to a retriever and a prompt template to answer questions based on retrieved documents?

Which two factors are essential for calculating the cost of using OCI Generative AI for text generation? (Choose two.)

A developer is building a RAG pipeline using LangChain and OCI Generative AI. They need to split a large PDF into overlapping chunks for embedding. Which text splitter and parameter settings are MOST appropriate?

A financial institution needs to deploy a fine-tuned model on OCI with strict data residency requirements. They must ensure that data used for inference never leaves a specific OCI region. The model is stored in Object Storage in the same region. What additional configuration is needed?

A team wants to deploy a LangChain agent that can perform mathematical calculations, look up current weather, and search the web. Which tools should they include in the agent's toolkit?

In the transformer architecture, what is the primary purpose of positional encoding?

A team wants to use the Embedding API to convert product descriptions into vectors for a semantic search application. They have descriptions in English and Spanish. Which embedding model should they use?

Which LangChain component is responsible for splitting long documents into smaller, overlapping chunks before embedding?

During a fine-tuning job for a text generation model, the loss curve shows that the training loss decreases steadily, but the evaluation loss increases after a few epochs. Which action is most likely to improve the model's generalization?

Which THREE factors should be considered when choosing between a fine-tuning and a prompt engineering approach?

In a Transformer model, what is the role of positional encoding?

A company has deployed a model on a Dedicated AI Cluster and needs to monitor inference performance metrics such as request latency, throughput, and error rates. Which OCI service provides built-in monitoring dashboards for these metrics?

An organization is deploying an LLM for document question answering. They want to reduce hallucinations and ensure answers are grounded in provided documents. Which THREE techniques should they implement? (Choose three.)

A developer is using a prompt template that includes placeholders like {context} and {question}. They want to version these templates for A/B testing. Which practice is BEST for managing prompt templates?

A prompt engineer is designing a system that generates step-by-step recipes for users. Which TWO prompt patterns are MOST relevant for this task?

A data scientist needs to generate embeddings for a collection of documents to be used for both clustering and semantic search. They want to use appropriate input types for each task. Which TWO input types should they use from the Cohere Embed API? (Choose two.)

Refer to the exhibit. A developer encounters this error. Which action should they take to resolve the issue?

A developer wants to invoke an OCI Generative AI model from an application running on a compute instance in OCI. The instance is in a private subnet. What is the most secure method to access the model endpoint?

A developer needs to authenticate API calls to OCI Generative AI from a compute instance. Which TWO methods can be used?

A company uses LangChain with OCI Generative AI. They notice that their agent-based application occasionally exceeds the rate limits of the OCI Generative AI service, causing errors. Which strategy is MOST effective for handling rate limits in a production LangChain application?

A company is deploying a chatbot powered by OCI Generative AI. They want to inject the conversation history into the model prompt to maintain context. However, they notice that after a long conversation, the model starts to ignore earlier messages. What is the most likely cause?

A company wants to deploy a fine-tuned model for real-time inference with consistent low latency. They are evaluating dedicated AI clusters. Which THREE factors should they consider when provisioning the cluster?

A financial services company must deploy a fine-tuned model for transaction categorization. The model must be isolated from other tenants and provide predictable low-latency inference. The compliance team also requires that training data never leaves the OCI tenancy. Which THREE steps should the team take? (Choose three.)

Given the CLI output from `oci generative-ai model list`, what can be determined about the model 'my-fine-tuned-model'?

A developer is using chain-of-thought prompting to solve a multi-step math problem. The model produces an incorrect final answer, but the intermediate reasoning steps appear logical. Which technique should be applied to improve accuracy?

A team is implementing a RAG pipeline in OCI. They have a large collection of PDF documents. After chunking and embedding the documents, retrieval quality is poor. Which step is MOST likely the root cause?

A company has multiple teams sharing an OCI Generative AI Dedicated AI Cluster. They need to ensure that each team can only access their own fine-tuned models and cannot see or invoke models from other teams. What is the best approach?

Which OCI Generative AI model would you use to reorder search results to improve relevance ranking?

A developer needs to build a chain that first summarizes a long document, then translates the summary into French. Which LangChain chain type allows executing these steps in sequence with the output of one step feeding into the next?

Which TWO of the following are advantages of using Byte-Pair Encoding (BPE) tokenization compared to word-level tokenization?

A data scientist is using OCI Data Science to fine-tune a Cohere command model on domain-specific documents. They observe that the fine-tuned model generates repetitive text. What is the most likely cause?

A developer is building a RAG application using Oracle Cloud Infrastructure (OCI) Document Understanding and OCI Generative AI. After chunking documents and generating embeddings, the developer observes that the retrieval step often returns chunks that are semantically unrelated to the query. Which action is MOST likely to improve retrieval relevance?

Which of the following best describes the role of attention in transformer models?

A prompt engineer wants to ensure the model outputs a JSON object with specific keys. Which prompt component is most appropriate to specify this requirement?

An organization needs to deploy a custom fine-tuned model for real-time inference with consistent low latency, and they must keep the model isolated from other tenants. Which deployment option should they choose?

An enterprise deployed a custom fine-tuned model for generating financial reports. After the first month, the model's outputs began to include outdated information and occasional factual errors. The team suspects data drift. What is the best course of action?

A developer notices that an LLM occasionally generates harmful or biased responses despite a system prompt instructing it to be safe. Which technique can help mitigate this at inference time without retraining?

A research team is comparing two LLMs for a translation task. Model A uses greedy decoding, Model B uses beam search with width=5. Both models are otherwise identical. Which statement about their outputs is MOST likely true?

A company has deployed a fine-tuned GPT model on OCI Generative AI using a dedicated AI cluster with 2 nodes. The endpoint is used by an internal application that generates product descriptions. Recently, the application started receiving timeouts and slow responses. The monitoring dashboard shows that the cluster's CPU utilization is consistently above 90%, and the request queue is growing. The team has verified that the model and code have not changed. The application traffic has increased by 20% over the past month. What should the team do to resolve the issue?

An organization stores its knowledge base in Oracle Autonomous Database and wants to build a RAG chatbot using OCI Generative AI. The chatbot must retrieve the most relevant documents based on user queries. Which indexing approach is BEST suited for efficient similarity search on text embeddings?

Which of the following is a common prompt injection vulnerability?

An enterprise RAG system must ensure that retrieved data comes only from authorized sources. Which OCI feature should be used to enforce this?

Which of the following best describes the difference between pre-training and fine-tuning?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

An organization wants to use OCI Generative AI for a high-volume summarization workload. They estimate 10 million tokens per month and need consistent low latency. Which pricing model is most cost-effective?

A practitioner wants to generate embeddings for a set of legal documents to enable semantic search. Which type of model should they use?

A large enterprise is deploying a generative AI model for internal document summarization. The model is deployed on OCI Data Science using a custom container. The inference endpoint is behind a public load balancer. The security team requires that all traffic between the client and the endpoint be encrypted in transit and that the endpoint not be accessible from the public internet. The current setup uses a public load balancer with an SSL certificate. The VCN has a public subnet for the load balancer and a private subnet for the model deployment. The security team is concerned that the load balancer is publicly accessible. The enterprise wants to maintain high availability and low latency. What should the architect do to meet the security requirements?

A document processing pipeline uses OCI Document Understanding to extract text from PDFs, then creates embeddings with OCI Generative AI. Some documents exceed the embedding model's token limit. What is the best approach?

A healthcare company is deploying OCI Generative AI Service for clinical decision support. They must ensure that model outputs are auditable, explainable, and free from patient data exposure. Which combination of OCI features should they use?

Which scenario BEST describes a prompt injection vulnerability?

A data scientist wants to generate a concise summary of a long legal document. The model should output a bullet list of key points. Which prompt component is LEAST important for this task?

A team is evaluating two LLMs for a summarization task. Model X has a BERTScore of 0.85, Model Y has a BERTScore of 0.82. However, human evaluators prefer Model Y. Which TWO reasons could explain this discrepancy?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Which LangChain component is responsible for storing and retrieving message history across multiple turns in a conversation?

A developer is using OCI Generative AI for a question-answering system. The model frequently provides outdated information because the training data cutoff is over a year old. Which approach would most effectively address this issue?

A team is iteratively refining a prompt for a summarization task. Which THREE activities are essential for effective iterative prompt refinement?

Which OCI Generative AI service model family supports fine-tuning with custom datasets?

A developer wants to use OCI Generative AI Service to summarize long documents. Which endpoint should they use to send the document content?

Which TWO are common causes of poor answer quality in a RAG system built on OCI Generative AI? (Choose two.)

A startup is using OCI Generative AI serverless inference for a text generation application. They notice that the latency is high during peak hours. They have a budget to increase costs moderately. Which action would most effectively reduce latency?

A company uses RAG (Retrieval-Augmented Generation) with OCI OpenSearch and OCI Generative AI. The system retrieves irrelevant documents. What is the first step to debug?

A company wants to use OCI Generative AI Agents for a question-answering system over their internal knowledge base stored in OCI Object Storage. The data consists of PDF and Word documents. What is the first step to make this data usable by the agent?

Which of the following is a primary limitation of large language models that can lead to generating factually incorrect information?

A legal firm needs an AI assistant that can answer questions based on a large corpus of internal regulations that change quarterly. The firm also requires high accuracy and the ability to cite sources. Which approach should the firm choose?

A company uses OCI Generative AI to generate product descriptions in XML format. The engineer wants to improve adherence to the XML schema. Which THREE prompt components are most critical? (Select three.)

Which THREE components are essential for a production-grade generative AI deployment on OCI? (Select THREE)

An OCI administrator is configuring access control for OCI Generative AI. Which three IAM components are required to allow a group of data scientists to call the GenerateText API? (Choose three.)

Which TWO parameters directly control the randomness and diversity of generated tokens?

A data scientist is evaluating two LLMs for a summarization task. Model X scores 45 on ROUGE-L, while Model Y scores 42. However, in human evaluation, Model Y is preferred 60% of the time. What is the most likely explanation?

Refer to the exhibit. A developer sends this JSON payload to the /chat endpoint. The response includes an error that 'maxTokens' must be an integer. What is the issue?

Which OCI Generative AI API is used to send a message and receive a model-generated response while maintaining a conversation history?

A developer is building a LangChain-powered application that must maintain conversation history across multiple turns. They want to store the chat history in Oracle Database. Which memory type and persistence approach should they use?

An organization wants to use OCI Generative AI to build a summarization tool but must ensure that all inference requests are logged for audit purposes. Which approach should they take?

Which TWO actions are required to use a custom fine-tuned model via OCI Generative AI? (Choose two.)

A data scientist is fine-tuning a generative AI model on OCI Data Science using a custom container with GPU resources. The training job fails with an out-of-memory error despite the GPU instance having sufficient memory. The job works fine on a smaller dataset. What is the most likely cause?

In the self-attention mechanism, what is the role of the 'scaling factor' (division by sqrt(d_k)) in the softmax computation?

A developer is building a multilingual search application and needs to generate embeddings for user queries in multiple languages. Which two options are correct? (Select TWO)

Which OCI Generative AI model is specifically designed to generate embeddings for English text?

When using LangChain's RetrievalQA chain with `chain_type="stuff"`, what happens if the retrieved documents exceed the model's context window?

What is the primary purpose of the self-attention mechanism in a Transformer model?

A developer is implementing a text generation pipeline and wants to produce diverse, creative outputs. They set temperature=1.2, top_k=50, and top_p=1.0. What is the MOST likely effect of this combination?

Which TWO of the following sampling strategies introduce randomness into text generation?

During deployment of a generative AI model, the inference endpoint returns high latency and timeouts. The model is deployed on a dedicated AI cluster with multiple nodes. What is the most likely cause?

Refer to the exhibit. A user receives this error when using the OCI CLI to chat with a model. What is the most likely cause?

Your company uses OCI Data Science for model development and deployment. You have a generative AI model that requires dynamic batching for efficient inference. You deployed the model using the OCI Model Deployment service with a custom inference script in a Docker container. However, you notice that the batch size is fixed at 1, leading to low throughput. The model can process multiple requests together efficiently. You want to implement dynamic batching to increase throughput without significantly increasing latency for individual requests. What is the best approach?

An AI assistant needs to solve complex math word problems step by step. Which prompting technique is most suitable?

An ML engineer is selecting a pre-trained model for a code generation task. The model must be able to generate syntactically correct code in multiple programming languages. Which model family is BEST suited for this task?

A company is building a customer support chatbot that uses Retrieval-Augmented Generation (RAG) with OCI Generative AI. They need low-latency responses and the ability to update the knowledge base daily. Which architecture best meets these requirements?

A developer is building a RAG application using OCI Generative AI. They notice that the generated responses often contain outdated information even though the knowledge base is updated daily. What is the most likely cause?

A developer wants to deploy a RAG application using OCI Generative AI for both embedding and text generation while minimizing costs. Which strategy is most effective?

A team is fine-tuning a Llama 3 model using OCI Generative AI. The training dataset contains 10,000 prompt-completion pairs in JSONL format. After submitting the fine-tuning job, it fails with a 'Data validation error'. What is the most likely cause?

A developer is using Cohere Command to answer questions grounded in internal technical manuals. They want to ensure the model only answers based on the provided documents and does not use its pre-trained knowledge. Which Cohere-specific technique should be applied?

Which of the following is NOT an available model in OCI Generative AI service?

A company has deployed a generative AI model endpoint on OCI. They want to monitor token usage and latency for cost optimization. Which OCI service should they use to collect these metrics?

During fine-tuning, a user notices the loss does not decrease after several epochs. The dataset is a JSONL file with 500 prompt/completion pairs. What is the MOST likely cause?

A multinational corporation uses OCI Generative AI to power a customer support chatbot. The chatbot uses a fine-tuned model deployed on a dedicated AI cluster in the us-ashburn-1 region. The application is used globally, and users in Europe are experiencing high latency (over 2 seconds) compared to users in North America (under 500 ms). The company has a requirement to keep all data within the US due to compliance, so they cannot deploy in Europe. The latency is not due to network bandwidth but due to the inference time. The monitoring shows that the cluster is at 80% utilization during peak hours. The team wants to reduce the latency for European users without violating data residency. What is the best course of action?

A data scientist is fine-tuning a model on OCI Generative AI with a custom dataset. They receive a "QuotaExceeded" error during training. What is the most likely cause?

Which prompting technique involves generating multiple independent reasoning paths and then selecting the most common answer?

Refer to the exhibit. A developer runs this command and sees that the 'cohere.embed-english-v3.0' model is INACTIVE. What is the most likely cause?

Which TWO of the following are benefits of using OCI Generative AI service compared to self-hosting an LLM?

A researcher is evaluating two LLMs for a summarization task. Model A achieves a ROUGE-L score of 0.45 and a BERTScore of 0.92. Model B achieves a ROUGE-L score of 0.50 and a BERTScore of 0.88. Which model is likely better for producing summaries that are semantically faithful to the source, even if not using the exact same words?

In Oracle AI Vector Search, which index type is designed for approximate nearest neighbor search and employs a hierarchical navigable small world graph, offering high recall and fast search speeds for high-dimensional data?

A security team requires that all OCI GenAI API calls be logged and audited. Despite enabling Audit logs in OCI, they do not see GenAI API calls. What is the most likely reason?

An OCI user is troubleshooting a prompt that sometimes produces outputs containing offensive language. The prompt uses a system prompt to set a professional tone. Which THREE steps should the user take to mitigate this issue? (Select three.)

Which TWO of the following are required to fine-tune a model using OCI Generative AI Service?

A data scientist is using the OCI Generative AI SDK to create embeddings for a large corpus of legal documents. They want to perform semantic search. Which endpoint should they use?

A developer is using the OCI Generative AI API to generate text. The responses are often too short and incomplete. Which parameter adjustment is most likely to produce longer, more complete responses?

Which THREE are valid considerations when designing a RAG pipeline that uses OCI Generative AI and OCI OpenSearch? (Choose three.)

A RAG system returns irrelevant chunks even though the embedding model and vector index are correctly configured. After reviewing, the chunks are too large and contain extraneous information. Which combination of adjustments should be made to improve relevance?

A financial company deploys a generative AI model for document analysis. They need to ensure that the model does not expose sensitive information in its responses. Which OCI service should they use to implement content filtering?

An application using OCI Generative AI produces inconsistent responses to the same user query. The developer suspects the model's output variability is too high. Which parameter adjustment would most directly reduce output randomness?

A data scientist wants to compare the semantic similarity between two sentences generated by an LLM. Which evaluation metric is most suitable for this purpose?

A company is using OCI Generative AI service to power a customer support chatbot. They observe that the chatbot sometimes provides outdated information because the model was trained on data up to 2022. They want to incorporate real-time knowledge without retraining the model. Which approach should they use?

Which THREE of the following are known limitations of large language models that practitioners must consider?

An architect needs to ensure that an LLM deployed in OCI does not reveal sensitive information in its outputs. Which technique should be used?

A security administrator needs to grant a group of data scientists access to use OCI Generative AI resources (models, endpoints) in compartment 'GenAI-Prod', but not allow them to create or manage infrastructure. Which IAM policy statement should be used?

Which of the following is the correct format for a training dataset used in OCI Generative AI fine-tuning?

An organization wants to fine-tune a large language model on OCI using their proprietary data. They are concerned about data privacy and want to ensure that fine-tuning data does not leave the OCI region. Which OCI service should they use to securely store and manage their training data?

Which TWO of the following are characteristics of decoder-only models like GPT? (Select TWO)

An enterprise with strict data residency requirements wants to use OCI Generative AI. They must ensure that no training data or inference data leaves a specific OCI region. Which configuration option should they choose?

What is the primary benefit of using a system prompt to set the persona and tone before the user message?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A DevOps engineer is setting up monitoring and logging for a generative AI inference endpoint. Which three resources should they enable? (Select THREE.)

Which TWO of the following are best practices for building a RAG pipeline in OCI?

A data engineer is building a RAG application using OCI Generative AI Agents. They have documents stored in OCI Object Storage. Which resource must they create to make these documents searchable by the agent?

A developer is using LangChain's ChatPromptTemplate to construct a prompt for a conversational agent. The prompt should include a system message, a placeholder for conversation history, and the latest user query. Which TWO components should they include in the template?

Which parameter controls the randomness of the model's output by scaling the probability distribution before sampling?

Which prompting technique involves providing the model with a small number of input-output examples within the prompt to guide its behavior?

A data scientist has fine-tuned a Cohere Command R model using the T-Few technique. They now need to deploy this custom model for real-time inference with low latency. What is the recommended deployment option in OCI Generative AI?

A developer is building a RAG application using OCI Generative AI Agents. They want to ensure the agent only retrieves information from approved documents in a specific compartment. Which THREE steps are required?

An application uses an LLM to summarize legal documents. The summaries sometimes include hallucinations (details not in the original text). Which prompt engineering technique is MOST effective at reducing hallucinations?

An AI engineer is designing a prompt to generate a report summary. The prompt currently says: 'Summarize the following text.' The output is often too verbose. Which modification would best enforce a concise, bullet-list format?

A developer is using the OCI Generative AI Chat API to build a conversational assistant. They want the assistant to adopt a formal tone regardless of user input. Which parameter should they set in the API request?

A research institution uses OCI Data Flow to process large-scale document corpora for a RAG system. They want to minimize latency for end-user queries. Which architecture decision would most effectively reduce query latency?

An OCI GenAI model generates English to French translation. Which metric is most appropriate to evaluate its quality?

A company wants to use OCI Generative AI to analyze legal documents and extract key clauses. Which model type is best suited for this task?

During iterative refinement, a prompt engineer tests two prompt variants on the same 100 inputs and measures accuracy. Variant A yields 85% accuracy, Variant B yields 82%. However, Variant B's outputs are more concise and preferred by users. What should the engineer do NEXT?

Your organization uses OCI Data Science to train a generative AI model for code generation. After training, you want to deploy it as a REST API. You create a model deployment using the OCI console, but after 30 minutes the deployment status is still 'Creating'. You check the logs and see the message: 'Insufficient capacity for shape VM.GPU.A10.1 in availability domain AD-1'. The deployment is configured with a single replica. You have verified your tenancy has sufficient service limits for GPU instances. What should you do to resolve this issue quickly?

Which tokenization algorithm is commonly used in models like GPT and BERT and builds tokens by merging the most frequent pairs of characters or subwords iteratively?

A researcher wants to compare the performance of two LLMs on OCI Generative AI: a base model and an instruct model. They notice the instruct model often refuses to generate certain types of content. Which factor most likely explains this behavior?

An AI engineer is testing a large language model on OCI Generative AI and receives this error: 'Token limit exceeded. Maximum context length is 4096 tokens.' The prompt is 4000 tokens long. What is the most effective way to resolve the issue without losing important context?

An administrator notices that a dedicated AI cluster is not scaling down after a period of low traffic. What could be the cause?

A company is using OCI Generative AI Agents to implement a RAG system for employee onboarding. They want to ensure the agent only answers from the uploaded documents and avoids making up information. Which THREE configuration steps should they take?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A data scientist needs to generate vector embeddings for a large corpus of text documents to use in a semantic search application. Which OCI service is best suited for this task?

A data scientist is designing a prompt to extract structured information (e.g., JSON) from text using an instruct model on OCI Generative AI. The model sometimes outputs additional text beyond the JSON, breaking parsing. Which prompt engineering technique is most effective to enforce structured output?

An OCI AI Language text classification request returns the output shown. Which conclusion is most accurate?

A model generates code with security issues. Which approach is best to mitigate this?

A developer is using the OCI Generative AI Chat API to build a multi-turn conversational assistant. They want the assistant to adopt a formal tone throughout the conversation. Which parameter should they set in the API request to achieve this?

Refer to the exhibit. A developer runs the OCI CLI command and receives the output. However, the text "Hello, how are you?" is actually a mix of English and French words. Why does the model assign only 0.03 to French?

A company runs batch inference jobs daily using the OCI Generative AI service. The current cost is higher than expected. Which change would most effectively reduce cost while maintaining throughput?

A RAG application is hallucinating because the LLM receives irrelevant context from the retrieval step, even when topK is set to 3. Which strategy would best reduce hallucination by improving the relevance of retrieved documents?

A user wants to invoke an OCI Generative AI endpoint from a cloud function. What is the required authentication method?

A machine learning engineer is designing a RAG pipeline in OCI to improve the accuracy of an LLM-based FAQ bot. Which TWO components are essential for the retrieval phase? (Select TWO.)

Which TWO deployment options are available for using fine-tuned models with OCI Generative AI service?

Which parameter controls the creativity and randomness of a model's output by adjusting the probability distribution before sampling the next token?

What is the role of the softmax function in the output layer of an LLM?

A user has a prompt that exceeds the model's token limit. What is the best practice to handle this?

An organization wants to allow its data science group to use OCI Generative AI services but restrict access to a specific compartment. Which IAM policy statement correctly achieves this?

Which TWO of the following are common applications of large language models in enterprise settings?

A team wants to use OCI Generative AI Agents to build a question-answering system over documents stored in OCI Object Storage. They have created a knowledge base and are ready to test. Which API should they use to interact with the agent for multi-turn conversations?

A developer is building a RAG pipeline using LangChain and Oracle AI Vector Search. After loading and splitting PDF documents, they generate embeddings and store them in Oracle Database using OracleVS. Which method should they call on the vector store object to create a retriever that uses similarity search with a configurable number of results?

A team is evaluating two embedding models for a similarity search task. Model A has a higher BERTScore on a reference dataset. Model B has a lower perplexity on the same dataset. Which model is likely better for retrieval?

A financial services company deployed a fine-tuned model using OCI Generative AI Service to generate investment advice based on quarterly reports. The model was trained on 10,000 labeled examples and achieved high accuracy in testing. However, after three months in production, the model's outputs have become inconsistent and sometimes recommend investments based on outdated market conditions. The team has received multiple complaints from users about inaccurate advice. The model is deployed on a dedicated AI cluster with auto-scaling disabled. The OCI audit logs show no configuration changes. The team suspects data drift and wants to mitigate it without incurring high costs. They have a pipeline that can collect new labeled data monthly, but it takes two weeks to process. What should the team do?

Which model family is NOT currently available in OCI Generative AI service?

Which LangChain memory type is best suited for a long-running conversation where token consumption must be minimized, and the gist of previous exchanges should be retained?

An organization needs to extract text from PDF documents and convert them into embeddings for a RAG pipeline using OCI. Which OCI service is best suited for extracting text from PDFs?

Which component of the Transformer architecture allows each token to consider the relevance of every other token in the input sequence?

A company is deploying a RAG pipeline using OCI Data Science and OCI Generative AI. The pipeline uses a Cohere command model for generation and a Cohere embed model for retrieval. The team notices that the model occasionally produces hallucinated answers that are not supported by the retrieved context. Which strategy is MOST effective at reducing hallucinations?

A data scientist is evaluating an LLM's performance on a summarization task. They observe that the model produces fluent summaries but often misses key information. Which TWO metrics would best capture this issue? (Select TWO.)

An architect is designing a multi-tenant application using OCI Generative AI. Each tenant has custom instructions and data. To minimize cost while maintaining isolation, which deployment approach is recommended?

A developer is using LangChain's ConversationBufferMemory to store chat history. They notice that after many turns, the prompt becomes too large and exceeds the model's context window. What is the BEST memory type to use for this scenario?

A data scientist is using the OCI Generative AI Embeddings API to generate vectors for a classification task. Which TWO input types are appropriate for this use case?

A developer notices that an LLM-based question-answering system sometimes provides answers that are correct but from an outdated version of the knowledge base. The system uses RAG with a vector database updated daily. What is the MOST likely root cause?

A company is building a chatbot that must maintain a professional tone and avoid discussing off-topic subjects. Which TWO prompt engineering approaches should they combine to enforce these requirements?

A healthcare startup is building an AI assistant to help doctors draft clinical notes from patient-physician conversations. They have a large language model that is fine-tuned on medical data. During testing, they notice the model occasionally generates plausible-sounding but incorrect medical recommendations. The startup wants to deploy the assistant to assist doctors, not replace them. They have the following options: (A) Deploy the model as-is and rely on doctors to catch errors, (B) Add a disclaimer that the model may make mistakes, (C) Implement a fact-checking pipeline that cross-references outputs with a trusted medical knowledge base before presenting to doctors, (D) Reduce the model's temperature to 0 to ensure deterministic outputs. Which option best balances safety and utility?

An administrator runs the above CLI command to check the status of a dedicated AI cluster. The cluster is ACTIVE with capacity 10. However, a user reports that inference requests to this cluster are failing with a '429 Too Many Requests' error. What is the most likely cause?

A developer is building a code generation assistant and needs to ensure the LLM follows a specific output format (e.g., JSON). Which approach is MOST effective for achieving format adherence without retraining?

Which THREE techniques are commonly used to improve the quality of text generation?

An administrator wants to grant a group of data scientists permission to use OCI Generative AI resources in a specific compartment, but prevent them from creating Dedicated AI Clusters. Which IAM policy statement achieves this?

A company uses OCI Generative AI to generate legal document summaries. They have a custom model deployed on a dedicated AI cluster. They want to ensure that the model is not used by unauthorized users. They also need to log all inference requests for auditing. Which combination of OCI services should they use?

What is the primary benefit of using a Dedicated AI Cluster for inference in OCI Generative AI?

An organization wants to combine keyword search and vector search to improve retrieval accuracy in their RAG pipeline. Which OCI service provides built-in hybrid search capabilities?

A security administrator needs to grant a data science team access to use OCI Generative AI resources (e.g., run inference, create fine-tuning jobs) but only within a specific compartment. What is the correct IAM policy statement?

A data scientist is using OCI Generative AI to generate synthetic data for training. They observe that the model's outputs lack diversity and often repeat the same phrases. Which combination of parameter adjustments would BEST increase output diversity?

A company wants to use OCI Generative AI to build a multilingual customer support chatbot. They need to understand customer queries in multiple languages and generate responses in the same language. Which TWO actions should they take? (Choose two.)

A developer is using the OCI Generative AI Generate API (not Chat API) to create a single-turn text completion. They need to include a system-level instruction that guides the model's behavior for that request. Which parameter should they use?

A developer is using OCI Generative AI Service to generate code snippets. They want to ensure the output is as deterministic as possible for testing. Which combination of parameters should they use?

A developer wants to compare two sentences for semantic similarity using embeddings. Which distance or similarity metric is most commonly used for dense vector representations?

A developer is using the OCI Generative AI Playground to test a Cohere Command R model. They want to reduce repetitiveness in the generated responses. Which parameter should they increase?

An organization is concerned about the safety of generated content. Which OCI feature allows them to define custom policies to block inappropriate outputs?

A developer is fine-tuning a Cohere Command R model using OCI Data Science and the T-Few technique. They have prepared a dataset. What is the required format for the training data?

A financial institution uses an LLM for generating investment advice. They are concerned about hallucinations. Which method is most effective?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A practitioner is developing a legal document summarization system and needs to reduce hallucinations. Which prompting technique is most effective for improving factual accuracy by exploring multiple reasoning paths?

Which TWO OCI Generative AI features are available in the Playground for testing models?

A company has deployed a generative AI model on OCI to generate product descriptions. After a recent update, the model started producing outputs with repetitive phrases and poor coherence. The inference endpoint is configured with default parameters. Which single parameter adjustment is most likely to improve output quality?

Which fine-tuning technique does OCI Generative AI use to efficiently update model parameters without modifying the entire model, enabling faster training on limited data?

A company notices that some inference requests to their deployed model on OCI Generative AI take longer than acceptable. They want to reduce per-request latency. What should they do?

Refer to the exhibit. A user runs the command shown and receives the error: 'ServiceError: NotAuthorizedOrNotFound'. What is the MOST likely cause?

What is the primary purpose of the self-attention mechanism in a transformer model?

A developer is comparing different foundation models for a text completion API on OCI. Which TWO of the following are model families available through OCI Generative AI service? (Choose two.)

A company is deploying a generative AI service on OCI using the OCI Data Science service with a large language model (LLM) in a VCN. The model inference endpoint must be accessible only from a private subnet within the same VCN. Which networking component should be configured to enable this?

A data engineer wants to migrate a large corpus of PDFs to OCI for use with GenAI. Which storage and preprocessing approach is most efficient for RAG?

A data scientist wants to improve the accuracy of a summarization model on medical texts. Which OCI service feature is most suitable?

An organization needs to ensure that all inference requests to OCI Generative AI are logged for compliance. Which OCI feature should be enabled?

A company uses OCI Generative AI service with a Cohere Command model for a real-time chat application and experiences high latency. They have already set max_tokens to 50 and temperature to 0.2. Which further change would be most effective in reducing latency?

A prompt engineer is troubleshooting a chatbot that consistently fails to follow instructions when the user includes adversarial input. Which two strategies can mitigate prompt injection attacks? (Choose two.)

Which TWO are benefits of using few-shot prompting compared to zero-shot prompting?

A team wants to reduce hallucinations in their LLM-powered question-answering system. Which TWO techniques are most effective?

A company is deploying a LangChain application using OCI Generative AI. They need to comply with a policy that requires all prompts sent to the LLM to be logged for audit, and they must also handle rate limits gracefully. Which TWO strategies should they implement?

A data scientist is configuring a fine-tuning job in OCI Generative AI. Which TWO of the following are required inputs for creating the job?

A prompt library manager wants to implement version control for prompt templates used across multiple applications. Which THREE practices should they adopt?

A data scientist is evaluating the cost of deploying a fine-tuned model for a high-volume production application. They need low latency but are cost-sensitive. Which TWO considerations should they evaluate when choosing between on-demand (shared) and dedicated cluster pricing?

A developer wants to build a RAG application that processes highly sensitive medical records. The documents are already stored in OCI Object Storage. Which vector storage strategy best balances security and performance?

A team uses OCI Generative AI’s fine-tuning capability to adapt a base model. After fine-tuning, they evaluate the model but see degraded performance on certain edge cases. What is the most likely cause?

Refer to the exhibit. A user in GenAI-Users group tries to run a text generation inference but gets permission denied. What is the most likely issue?

A developer is using the OCI Generative AI SDK in Python to call the cohere.command model. They are getting a 401 Unauthorized error. They have configured the SDK with their tenancy OCID and user OCID. What is the most likely missing piece?

A data scientist is fine-tuning a Cohere model on OCI Generative AI service for a custom classification task. They have a dataset of 1000 labeled examples. What is the minimum recommended dataset size for fine-tuning?

Which THREE factors should be considered when designing a vector search index for a RAG application that supports multiple languages?

An organization needs to implement a RAG application with Oracle AI Vector Search but has strict latency requirements. They have millions of vectors. Which index type is likely to provide the best search speed while maintaining reasonable recall?

Which TWO factors should be considered when selecting a base model for fine-tuning on OCI Generative AI service?

A data scientist uses OCI Generative AI Playground to test a Cohere Command R model for a summarization task. They want the summary to be concise and avoid repeating phrases. Which parameter adjustments would BEST achieve this?

A developer is building a conversational AI application using LangChain and needs to persist chat history across sessions. Which TWO approaches can they use? (Choose TWO.)

Which THREE steps are necessary to secure access to the OCI Generative AI inference API in a production environment?

Refer to the exhibit. A team created this dedicated AI cluster. However, when they try to create a model deployment, the deployment fails with an error indicating insufficient public IPs. What change to the cluster configuration should they make?

An e-commerce company uses OCI Generative AI to generate product descriptions. They have fine-tuned the model on their product catalog. They notice that the descriptions are accurate but lack creativity and are repetitive. They want to maintain accuracy while adding variety. What change should they make?

An AI specialist is troubleshooting why a fine-tuned model produces inconsistent results across different inference calls. What is the most likely cause?

A company is deploying a LangChain application on OCI and needs to implement error handling and rate limit management. Which THREE strategies should they consider? (Choose THREE.)

A team is building a multilingual semantic search application. They need to index documents in English, Spanish, and French, and later search using queries in any of these languages. Which embedding model should they use?

An organization is fine-tuning a large language model on OCI Data Science. They must ensure that the training data remains within a specific geographic region and is encrypted at rest. Which combination of resources should they use?

Which statement accurately describes the T-Few fine-tuning technique used in OCI Generative AI?

A team is building a conversational chatbot using LangChain and OCI Generative AI. They want to maintain a summary of the conversation rather than storing the entire history, to keep within token limits. Which memory class should they use, and what additional step is required when initializing the memory?

An organization is planning to use OCI Generative AI for sensitive customer data. Which three OCI services or features should they consider for data governance and security?

An engineer sets beam search width to 1 during inference on OCI Generative AI. What is the most likely effect on output?

An administrator needs to grant a data science team access to create and manage generative AI model endpoints in a specific compartment. Which policy should they create?

Which THREE of the following are best practices when deploying a generative AI model on OCI?

A developer needs to integrate OCI Generative AI into a Python application. Which SDK should they use?

During fine-tuning of a Cohere model on OCI Data Science, the loss curve shows a sharp spike after epoch 3. What is the most appropriate action?

You are a machine learning engineer at a large e-commerce company. You have been tasked with deploying a large language model to power a customer service chatbot that handles product returns and refunds. The model will answer customer queries based on a knowledge base of return policies and FAQs. The company has strict requirements: (1) responses must be factually accurate and grounded in the knowledge base, (2) the system must be cost-effective, and (3) latency should be under 2 seconds per response. You decide to use a pre-trained LLM from OCI Data Science and implement retrieval-augmented generation (RAG). You have two options for the retriever: a dense embedding-based retriever (e.g., using OCI AI Language embeddings) or a sparse keyword-based retriever (e.g., BM25). You also need to decide on the generation model size: a 7B parameter model or a 70B parameter model. You run a pilot test: with the dense retriever + 7B model, average latency is 1.8 seconds and accuracy is 85%. With the sparse retriever + 7B model, latency is 1.2 seconds but accuracy drops to 75%. With the 70B model (any retriever), latency exceeds 5 seconds. Which combination should you choose to meet all requirements?

A developer makes an API call to generate text with top_p=1.5. What is the correct way to fix this error?

A data scientist fine-tunes a model using OCI Data Science and wants to deploy it as a managed endpoint in OCI Generative AI. What must they do first?

A company has fine-tuned a Cohere Command R model using T-Few and wants to deploy it for real-time inference with the lowest possible latency. They have provisioned a dedicated AI cluster with 2 model units. However, latency is still higher than expected. Which action is MOST likely to reduce latency?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

An organization wants to deploy an LLM for legal document analysis where accuracy is critical, and the model must not reference any external data outside the provided legal corpus. Which approach BEST satisfies these requirements?

A developer wants the LLM to solve a math problem by reasoning step by step. Which prompting technique should they use?

A data scientist is building a RAG application that processes PDF invoices. The extraction step uses OCI Document Understanding to convert PDFs to text. The scientist then splits the text into chunks and generates embeddings using OCI Generative AI. However, the retrieval often misses critical fields like invoice numbers and dates. Which preprocessing step would MOST likely improve retrieval of these specific fields?

Which TWO actions are recommended best practices for managing costs when using OCI Generative AI dedicated AI clusters?

A data science team at a healthcare company has fine-tuned a Llama 2 model using OCI Data Science and registered it in the Model Catalog. They want to deploy it as a managed endpoint using OCI Generative AI. The model requires 64 GB of GPU memory. The team has created a dedicated AI cluster with a single node shape that has 48 GB GPU memory. When they attempt to deploy the model, the deployment fails with an error indicating insufficient resources. The team has verified that the model artifact is correct and that the compartment policies allow deployment. What should the team do to successfully deploy the model?

You manage a generative AI model deployed on OCI Model Deployment that serves a chatbot application. The model is a 13B parameter LLM on a VM.GPU.A100.1 shape. Recently, you rolled out a new version of the model that is supposed to improve response quality. However, after the update, the application starts returning HTTP 500 errors and memory usage spikes. You need to update to the new version without causing downtime. The current deployment has 2 replicas with autoscaling enabled. Which strategy should you use to safely deploy the new model version?

Refer to the exhibit. A user runs 'oci generative-ai model list' and sees this output. They then try to use 'cohere.command-light' but get an error. What is the most likely reason?

Which three techniques are commonly used to reduce the risk of prompt injection in LLM applications? (Choose three.)

When tuning the temperature parameter for a text generation task, which effect does setting temperature to 0.1 have compared to 0.9?

A developer is building a summarization pipeline using OCI Generative AI. They want to ensure the summary includes key points from the entire document without truncation. Which parameter should they primarily adjust?

An organization wants to ensure that prompts submitted to an LLM do not contain sensitive customer data. Which practice is most effective?

Which OCI Generative AI model family is specifically designed for reranking search results to improve relevance?

Which TWO are best practices for prompt management in production environments?

An organization wants to use an LLM to summarize legal documents. Which consideration is most important for ensuring accurate summaries?

A data scientist wants to fine-tune a generative AI model on proprietary customer data. What is a best practice for preparing the training dataset?

An administrator needs to grant a group of data scientists access to use OCI Generative AI resources in a specific compartment. Which IAM policy statement should they use?

A company needs to integrate OCI Generative AI Service with an existing application that uses OCI IAM for authentication. They want to use resource principal to allow the application to call the service without storing API keys. Which step is REQUIRED?

A company wants to use OCI Generative AI Agents to build a RAG application over documents stored in OCI Object Storage. What must they create first?

During iterative prompt refinement, a team evaluates two prompt variants on 100 test queries. Variant A scores 85% accuracy but occasionally generates offensive content. Variant B scores 80% accuracy with no safety issues. Which evaluation criterion should take priority for a customer-facing application?

A multinational corporation plans to deploy OCI Generative AI in multiple OCI regions for disaster recovery. They have fine-tuned a custom model in the primary region. What is the recommended approach to make the fine-tuned model available in the secondary region with minimal manual effort?

A data scientist wants to fine-tune a Cohere Command R model using the T-Few technique. They have prepared a dataset in JSONL format with prompt/completion pairs. Which step is REQUIRED before creating the fine-tuning job?

In a LangChain RAG pipeline using Oracle AI Vector Search, the developer wants to retrieve chunks that are both relevant and diverse to cover multiple aspects of a query. Which retrieval method should they configure on the retriever?

A developer is building a RAG pipeline using OCI Data Science and wants to store vector embeddings. Which OCI service is optimized for vector search and can be used as a vector store?

Which THREE techniques effectively reduce query latency in a RAG system?

A prompt engineer notices that the model sometimes generates outputs that include parts of the system prompt or user message verbatim. This is likely a symptom of which common prompt failure?

A financial services company is deploying a RAG system for regulatory compliance queries. The system uses OCI Data Science to run a custom embedding model fine-tuned on regulatory documents. The index in OpenSearch uses cosine similarity and HNSW algorithm. Users report that queries containing synonyms to regulatory terms (e.g., "AML" vs "Anti-Money Laundering") often fail to retrieve relevant documents. Which combination of improvements would be MOST effective? (Assume budget and latency constraints)

A developer notices that the RAG application returns irrelevant chunks for user queries. The embedding model used is `cohere.embed-english-light-v3.0`. Which action is MOST likely to improve relevance?

During fine-tuning of a large language model on OCI, you notice that the model's performance on the validation set is not improving after several epochs, but the training loss continues to decrease. What is the most likely cause?

Which of the following sampling strategies selects tokens based on a cumulative probability threshold from the highest probability tokens?

A machine learning engineer is evaluating the performance of a translation model using BLEU score. Which THREE statements about BLEU are correct? (Choose three.)

A healthcare company is using OCI GenAI to generate patient summaries from clinical notes. The model output sometimes includes hallucinated medical facts, such as incorrect dosages or diagnoses, which could be dangerous. The team needs to improve factual accuracy while maintaining data privacy. They have a large collection of internal medical knowledge bases (clinical guidelines, drug databases) that are stored in OCI Object Storage. The current implementation uses a zero-shot prompt with the base Cohere Command model. The data science team has limited GPU resources and wants to avoid building a complex pipeline. Which course of action best addresses the hallucination problem?

A developer is testing a RAG application using OCI Generative AI. They receive an error: 'The model cohere.command-r-plus-v1:0 is not supported in this region.' What is the most likely cause?

A developer runs an OCI GenAI chat request with system prompt "You are a sarcastic assistant." The output is offensive. How can the developer enforce safety policies?

A data scientist is fine-tuning a Llama 2 7B model on a custom dataset using OCI Data Science. After training, the model generates fluent but factually incorrect statements about the new domain. Which post-training technique would BEST address this issue without retraining?

A developer notices that the ConversationalRetrievalChain in their LangChain application is not retaining context from previous turns in the conversation. Which component is most likely missing or misconfigured?

A data scientist in group DataScientists uses the OCI Generative AI SDK to start a fine-tuning job in compartment AIResources. They receive the error shown. What is the most likely cause?

In few-shot prompting, what is the primary purpose of including examples in the prompt?

A prompt engineer is testing two versions of a prompt for a content generation task. They want to measure which version produces more factual and concise outputs. Which evaluation approach is BEST?

An administrator created the above IAM policies. A member of the GenerativeAIAdmins group reports they cannot invoke the model endpoint. Which permission is missing?

Which component of the Transformer architecture allows the model to weigh the importance of different tokens in the input sequence when generating each output token?

An engineer configured the above index mapping for vector search. When performing a k-NN search, the results are unexpected. What is the most likely issue?

A team has fine-tuned a Cohere Command R model using T-Few on a dataset of 5,000 prompt/completion pairs. After deployment, they notice the model sometimes generates off-topic responses. Which action is most likely to improve response relevance without requiring new training data?

A developer wants to use LangChain to create an agent that can perform calculations and look up information from a database. Which tools should be provided to the agent?

A developer wants to generate text using the OCI Generative AI service via the API. Which endpoint should they use to send a text generation request?

A user repeatedly gets the same phrase output by the model. Which parameter adjustment is MOST likely to reduce such repetitive patterns?

What is the primary purpose of an embedding model in a RAG pipeline?

An AI team is fine-tuning a large language model using OCI Data Science and plans to deploy the fine-tuned model using the Generative AI service's custom model deployment. What is the required format for the model artifacts?

A team fine-tuned a Cohere Command R model in OCI GenAI and validated it. They now need to deploy it for production inference with a dedicated endpoint. What is the correct sequence of steps?

A retail company uses OCI Generative AI Service to build a RAG chatbot for product recommendations. The chatbot should consider both the user's query and the retrieved product descriptions. Which component of the RAG pipeline is responsible for combining these inputs before sending to the LLM?

Which LangChain document loader would be most appropriate to load content from a public website for inclusion in a knowledge base?

A company is building a chatbot using OCI Generative AI service. They want to ensure that the model responses are grounded in their internal knowledge base. Which approach should they use?

A developer is using OCI GenAI to generate structured data. They often get responses that include additional commentary or markdown. Which prompt engineering technique should they use to ensure only JSON output?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

An OCI Generative AI user notices that a model generates repetitive phrases when summarizing technical articles. Which parameter adjustment is MOST likely to reduce this repetition?

A team has deployed a generative AI model and needs to monitor inference performance and set up alerts for increased error rates. Which OCI service should they integrate with?