1Z0-1127 LangChain and AI Application Development — All Questions With Answers

Question 1mediummultiple choice

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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?

Question 2easymultiple choice

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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?

Question 3mediummultiple choice

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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?

Question 4hardmultiple choice

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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?

Question 5easymultiple choice

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

Question 6mediummultiple choice

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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?

Question 7mediummultiple choice

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

Question 8hardmultiple choice

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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?

Question 9mediummultiple choice

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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?

Question 10easymultiple choice

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

Question 11mediummultiple choice

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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?

Question 12hardmultiple choice

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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?

Question 13mediummulti select

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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?

Question 14hardmulti select

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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?

Question 15easymulti select

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Which THREE of the following are core LangChain components?

Question 16mediummultiple choice

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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?

Question 17easymultiple choice

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

Question 18mediummultiple choice

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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?

Question 19easymultiple choice

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

Question 20hardmultiple choice

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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?

Question 21mediummultiple choice

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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?

Question 22mediummultiple choice

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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?

Question 23mediummultiple choice

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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?

Question 24easymultiple choice

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

Question 25hardmultiple choice

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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?

Question 26mediummultiple choice

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

Question 27hardmultiple choice

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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?

Question 28mediummulti select

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A developer is deploying a LangChain agent that uses an LLM from OCI Generative AI. The agent interacts with external APIs and must handle rate limits gracefully. Which TWO practices should the developer implement?

Question 29mediummulti select

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In a LangChain RAG pipeline using OCI Generative AI, which THREE components are essential for ingesting documents into a vector store?

Question 30easymulti select

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A developer wants to persist chat history for a LangChain application so that conversations survive application restarts. Which TWO approaches are appropriate?

Question 31mediummultiple choice

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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?

Question 32mediummultiple choice

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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?

Question 33hardmultiple choice

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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?

Question 34easymultiple choice

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

Question 35mediummultiple choice

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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?

Question 36hardmultiple choice

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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?

Question 37easymultiple choice

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In a LangChain RetrievalQA chain, which method on a vector store is used to create the retriever object?

Question 38mediummultiple choice

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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?

Question 39hardmultiple choice

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An enterprise is building a LangChain application that must use Oracle AI Vector Search for retrieval. They need to store embeddings in an Oracle Database 23ai table with a VECTOR column. Which index type should they create to support efficient similarity search with exact nearest neighbor queries?

Question 40easymultiple choice

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Which LangChain document loader would you use to load data from a webpage given its URL?

Question 41mediummultiple choice

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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?

Question 42mediummultiple choice

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

Question 43mediummulti select

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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?

Question 44hardmulti select

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A LangChain ReAct agent is failing to correctly use a custom tool that requires a specific parameter format. The agent keeps calling the tool with incorrect parameters. Which THREE steps should the developer take to debug and fix the issue?

Question 45easymulti select

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

Question 46mediummultiple choice

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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?

Question 47mediummultiple choice

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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?

Question 48easymultiple choice

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

Question 49mediummultiple choice

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

Question 50mediummultiple choice

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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?

Question 51hardmultiple choice

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A developer observes that their LangChain RAG pipeline sometimes returns duplicate or near-duplicate documents in the retrieved set, reducing the diversity of information provided to the LLM. Which retrieval parameter should they adjust to improve diversity?

Question 52mediummultiple choice

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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?

Question 53easymultiple choice

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

Question 54hardmultiple choice

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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?

Question 55mediummultiple choice

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A developer is using LangChain's SequentialChain to process text: first, summarize a long document, then translate the summary to French. How should they configure the chain to pass the output of the first step as input to the second?

Question 56hardmultiple choice

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An application uses ConversationalRetrievalChain with a vector store retriever. Users report that the chatbot sometimes provides answers that are not grounded in the retrieved documents. Which step in the RAG pipeline is most likely the cause?

Question 57easymultiple choice

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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?

Question 58mediummulti select

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A developer is using LangChain to build a RAG pipeline that processes PDF documents. They need to split the text into chunks and store embeddings in Oracle Database 23ai. Which two components are essential? (Choose TWO.)

Question 59mediummulti select

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A team is designing a production-grade LangChain agent that uses multiple tools, including a custom SQL query tool and a web search tool. They need to ensure the agent handles errors gracefully and logs all actions. Which three practices should they implement? (Choose THREE.)

Question 60hardmulti select

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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.)

Question 61mediummultiple choice

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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?

Question 62easymultiple choice

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

Question 63hardmultiple choice

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A developer uses RecursiveCharacterTextSplitter with chunk_size=500 and chunk_overlap=100. After splitting, a particular chunk ends with an incomplete sentence. What is the likely cause?

Question 64mediummultiple choice

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A developer wants to create a LangChain chain that takes a user's question, retrieves relevant documents from a vector store, and then generates an answer using an LLM. Which chain is MOST appropriate for this task?

Question 65hardmultiple choice

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An organization using Oracle AI Vector Search for a RAG application wants to minimize latency for vector similarity searches on a dataset of 10 million vectors. Which index type and parameter combination is MOST likely to achieve the lowest latency while maintaining high recall?

Question 66easymultiple choice

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

Question 67mediummultiple choice

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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?

Question 68mediummultiple choice

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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?

Question 69hardmultiple choice

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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?

Question 70easymultiple choice

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

Question 71mediummultiple choice

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A developer wants to ensure that a LangChain RetrievalQA chain returns diverse results, avoiding near-duplicate passages in the retrieved context. Which retrieval parameter should be configured on the retriever?

Question 72hardmultiple choice

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An application uses Oracle AI Vector Search with a VECTOR data type column. The team wants to perform a similarity search to find the top 5 most similar vectors to a query vector. Which SQL clause is necessary to achieve this?

Question 73mediummulti select

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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.)

Question 74mediummulti select

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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.)

Question 75hardmulti select

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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.)

Question 76mediummultiple choice

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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?

Question 77mediummultiple choice

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A team is using LangChain's LCEL to build a RAG pipeline. They want to add a step that logs the retrieved documents before passing them to the LLM. How can they achieve this while keeping the chain composable?

Question 78easymultiple choice

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

Question 79hardmultiple choice

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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?

Question 80easymultiple choice

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A developer wants to use LangChain to connect to OCI Generative AI Service for text generation. Which LangChain wrapper class should they use for the chat model?

Question 81hardmultiple choice

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A company is deploying a LangChain agent for internal data analysis. The agent uses a ReAct pattern with tools including a Python REPL and a SQL query tool. What is the PRIMARY security concern when exposing this agent to non-technical users?

Question 82mediummultiple choice

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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?

Question 83mediummulti select

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A developer is building a RAG application with LangChain and Oracle AI Vector Search. They need to choose a text splitter that respects semantic boundaries (e.g., paragraphs, sentences) and a vector store that supports transactional updates in Oracle Database 23ai. Which TWO options should they select?

Question 84mediummulti select

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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?

Question 85mediummulti select

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A developer is using LangChain's RetrievalQA chain with a vector store. They want to improve the diversity of retrieved documents to avoid redundant information. Which TWO parameters or methods should they adjust?

Question 86easymulti select

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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?

Question 87hardmulti select

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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?

Question 88mediummulti select

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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?

Question 89hardmulti select

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A developer is using LangChain with Oracle AI Vector Search (OracleVS) to store embeddings. They notice that similarity search queries are slow. Which THREE actions could improve query performance?

Question 90easymulti select

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A developer wants to load a CSV file containing customer feedback and split it into chunks for a RAG pipeline. Which TWO LangChain components should they use?

Question 1mediummultiple choice

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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?

Question 2easymultiple choice

Read the full LangChain and AI Application Development explanation →

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?

Question 3mediummultiple choice

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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?

Question 4hardmultiple choice

Read the full LangChain and AI Application Development explanation →

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?

Question 5easymultiple choice

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

Question 6mediummultiple choice

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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?

Question 7mediummultiple choice

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

Question 8hardmultiple choice

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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?

Question 9mediummultiple choice

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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?

Question 10easymultiple choice

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

Question 11mediummultiple choice

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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?

Question 12hardmultiple choice

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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?

Question 13mediummulti select

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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?

Question 14hardmulti select

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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?

Question 15easymulti select

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Which THREE of the following are core LangChain components?

Question 16mediummultiple choice

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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?

Question 17easymultiple choice

Read the full LangChain and AI Application Development explanation →

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

Question 18mediummultiple choice

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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?

Question 19easymultiple choice

Read the full LangChain and AI Application Development explanation →

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

Question 20hardmultiple choice

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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?

Question 21mediummultiple choice

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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?

Question 22mediummultiple choice

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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?

Question 23mediummultiple choice

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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?

Question 24easymultiple choice

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

Question 25hardmultiple choice

Read the full LangChain and AI Application Development explanation →

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?

Question 26mediummultiple choice

Read the full LangChain and AI Application Development explanation →

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

Question 27hardmultiple choice

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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?

Question 28mediummulti select

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A developer is deploying a LangChain agent that uses an LLM from OCI Generative AI. The agent interacts with external APIs and must handle rate limits gracefully. Which TWO practices should the developer implement?

Question 29mediummulti select

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In a LangChain RAG pipeline using OCI Generative AI, which THREE components are essential for ingesting documents into a vector store?

Question 30easymulti select

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A developer wants to persist chat history for a LangChain application so that conversations survive application restarts. Which TWO approaches are appropriate?

Question 31mediummultiple choice

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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?

Question 32mediummultiple choice

Read the full LangChain and AI Application Development explanation →

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?

Question 33hardmultiple choice

Read the full LangChain and AI Application Development explanation →

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?

Question 34easymultiple choice

Read the full LangChain and AI Application Development explanation →

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

Question 35mediummultiple choice

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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?

Question 36hardmultiple choice

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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?

Question 37easymultiple choice

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In a LangChain RetrievalQA chain, which method on a vector store is used to create the retriever object?

Question 38mediummultiple choice

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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?

Question 39hardmultiple choice

Read the full LangChain and AI Application Development explanation →

An enterprise is building a LangChain application that must use Oracle AI Vector Search for retrieval. They need to store embeddings in an Oracle Database 23ai table with a VECTOR column. Which index type should they create to support efficient similarity search with exact nearest neighbor queries?

Question 40easymultiple choice

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Which LangChain document loader would you use to load data from a webpage given its URL?

Question 41mediummultiple choice

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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?

Question 42mediummultiple choice

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

Question 43mediummulti select

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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?

Question 44hardmulti select

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A LangChain ReAct agent is failing to correctly use a custom tool that requires a specific parameter format. The agent keeps calling the tool with incorrect parameters. Which THREE steps should the developer take to debug and fix the issue?

Question 45easymulti select

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

Question 46mediummultiple choice

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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?

Question 47mediummultiple choice

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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?

Question 48easymultiple choice

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

Question 49mediummultiple choice

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

Question 50mediummultiple choice

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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?

Question 51hardmultiple choice

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A developer observes that their LangChain RAG pipeline sometimes returns duplicate or near-duplicate documents in the retrieved set, reducing the diversity of information provided to the LLM. Which retrieval parameter should they adjust to improve diversity?

Question 52mediummultiple choice

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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?

Question 53easymultiple choice

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

Question 54hardmultiple choice

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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?

Question 55mediummultiple choice

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A developer is using LangChain's SequentialChain to process text: first, summarize a long document, then translate the summary to French. How should they configure the chain to pass the output of the first step as input to the second?

Question 56hardmultiple choice

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An application uses ConversationalRetrievalChain with a vector store retriever. Users report that the chatbot sometimes provides answers that are not grounded in the retrieved documents. Which step in the RAG pipeline is most likely the cause?

Question 57easymultiple choice

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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?

Question 58mediummulti select

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A developer is using LangChain to build a RAG pipeline that processes PDF documents. They need to split the text into chunks and store embeddings in Oracle Database 23ai. Which two components are essential? (Choose TWO.)

Question 59mediummulti select

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A team is designing a production-grade LangChain agent that uses multiple tools, including a custom SQL query tool and a web search tool. They need to ensure the agent handles errors gracefully and logs all actions. Which three practices should they implement? (Choose THREE.)

Question 60hardmulti select

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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.)

Question 61mediummultiple choice

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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?

Question 62easymultiple choice

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

Question 63hardmultiple choice

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A developer uses RecursiveCharacterTextSplitter with chunk_size=500 and chunk_overlap=100. After splitting, a particular chunk ends with an incomplete sentence. What is the likely cause?

Question 64mediummultiple choice

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A developer wants to create a LangChain chain that takes a user's question, retrieves relevant documents from a vector store, and then generates an answer using an LLM. Which chain is MOST appropriate for this task?

Question 65hardmultiple choice

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An organization using Oracle AI Vector Search for a RAG application wants to minimize latency for vector similarity searches on a dataset of 10 million vectors. Which index type and parameter combination is MOST likely to achieve the lowest latency while maintaining high recall?

Question 66easymultiple choice

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

Question 67mediummultiple choice

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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?

Question 68mediummultiple choice

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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?

Question 69hardmultiple choice

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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?

Question 70easymultiple choice

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

Question 71mediummultiple choice

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A developer wants to ensure that a LangChain RetrievalQA chain returns diverse results, avoiding near-duplicate passages in the retrieved context. Which retrieval parameter should be configured on the retriever?

Question 72hardmultiple choice

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An application uses Oracle AI Vector Search with a VECTOR data type column. The team wants to perform a similarity search to find the top 5 most similar vectors to a query vector. Which SQL clause is necessary to achieve this?

Question 73mediummulti select

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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.)

Question 74mediummulti select

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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.)

Question 75hardmulti select

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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.)

Question 76mediummultiple choice

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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?

Question 77mediummultiple choice

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A team is using LangChain's LCEL to build a RAG pipeline. They want to add a step that logs the retrieved documents before passing them to the LLM. How can they achieve this while keeping the chain composable?

Question 78easymultiple choice

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

Question 79hardmultiple choice

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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?

Question 80easymultiple choice

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A developer wants to use LangChain to connect to OCI Generative AI Service for text generation. Which LangChain wrapper class should they use for the chat model?

Question 81hardmultiple choice

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A company is deploying a LangChain agent for internal data analysis. The agent uses a ReAct pattern with tools including a Python REPL and a SQL query tool. What is the PRIMARY security concern when exposing this agent to non-technical users?

Question 82mediummultiple choice

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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?

Question 83mediummulti select

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A developer is building a RAG application with LangChain and Oracle AI Vector Search. They need to choose a text splitter that respects semantic boundaries (e.g., paragraphs, sentences) and a vector store that supports transactional updates in Oracle Database 23ai. Which TWO options should they select?

Question 84mediummulti select

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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?

Question 85mediummulti select

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A developer is using LangChain's RetrievalQA chain with a vector store. They want to improve the diversity of retrieved documents to avoid redundant information. Which TWO parameters or methods should they adjust?

Question 86easymulti select

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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?

Question 87hardmulti select

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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?

Question 88mediummulti select

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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?

Question 89hardmulti select

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A developer is using LangChain with Oracle AI Vector Search (OracleVS) to store embeddings. They notice that similarity search queries are slow. Which THREE actions could improve query performance?

Question 90easymulti select

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A developer wants to load a CSV file containing customer feedback and split it into chunks for a RAG pipeline. Which TWO LangChain components should they use?