Applications of Foundation Models

A company is building a RAG application using Amazon Bedrock Knowledge Bases. They want to ensure that the model only answers based on the retrieved documents and does not use its internal knowledge. Which configuration should they use?

A company runs a question-answering application on Amazon Bedrock that answers from a large knowledge base. Recently, users have reported that the model gives incomplete answers, often missing details from the middle of documents. The team suspects the chunking strategy is suboptimal. Which adjustment is MOST likely to improve completeness?

A company is developing a generative AI application using Amazon Bedrock for code generation. They want to reduce costs without sacrificing throughput. Which THREE approaches can help achieve cost optimization?

A company is designing a RAG pipeline for a legal document review system. They need to ingest hundreds of documents, create embeddings, and store them for retrieval. Which THREE steps are essential in the ingestion phase of the RAG pipeline?

A company is using Bedrock Knowledge Bases with Amazon OpenSearch Serverless as the vector store. They need to ensure that the vector search returns results within 500ms for real-time queries. The current average latency is 800ms. Which change is MOST likely to reduce latency?

A company is using Amazon Bedrock to build a code generation assistant for internal developers. They want to reduce costs by processing batch requests during off-peak hours. Which Bedrock feature should they use?

A team is evaluating two different foundation models for a sentiment analysis task. They have a labeled test dataset. Which evaluation approach should they use to compare the models' performance on this task?

A company is building a RAG application with Amazon Bedrock Knowledge Bases. They want to ensure that the retriever returns the most semantically relevant chunks. They are using a large document corpus with many similar passages. Which chunking strategy is MOST likely to improve retrieval accuracy?

A company is deploying a customer‑facing chatbot using Amazon Bedrock. They need to ensure the chatbot never reveals personally identifiable information (PII) and refuses to discuss the topic of 'employee salaries'. Which TWO Bedrock Guardrails features should they configure together? (Select TWO.)

A data scientist is designing a RAG pipeline using Amazon Bedrock Knowledge Bases. They need to store embeddings of document chunks and perform similarity searches. Which vector store is a serverless option that integrates directly with Bedrock Knowledge Bases?

A company uses a Bedrock Agent to handle customer support tickets. The agent needs to look up order status from a legacy API that requires authentication. The agent should also escalate to a human if the query is not supported. Which combination of components should the developer configure?

A financial services company uses Amazon Bedrock to generate investment report summaries. They have strict compliance requirements that the model must not discuss certain topics like insider trading or unapproved financial advice. Which Bedrock feature should they use to deny these topics?

A company is evaluating the output quality of a summarisation model using Amazon Bedrock Model Evaluation. They want to use both automated and human evaluation. Which THREE components can they configure as part of a model evaluation job? (Choose THREE.)

An organization wants to prototype a new generative AI application and allow multiple team members to collaborate on prompt engineering and model selection without writing code. Which tool should they use?

A developer is using Amazon Bedrock Agents to create an agent that can book meetings by interacting with a calendar API. They have defined an action group with an OpenAPI schema. What is required to execute the API call when the agent decides to use it?

A developer needs to evaluate the quality of a text summarization model by comparing its output to reference summaries. Which automated metric measures the overlap of n‑grams between the generated and reference summaries?

A developer is using Amazon Bedrock Agents to build a multi-step reasoning workflow. The agent needs to query an external REST API to fetch data. What must the developer define in the agent configuration?

A financial services company wants to deploy a chatbot using Amazon Bedrock that must never discuss investment advice. Which Bedrock feature should they configure to enforce this policy?

A developer wants to quickly prototype a generative AI application using Amazon Bedrock. They need to test different foundation models and prompts interactively. Which two services or features are designed for this purpose? (Choose TWO.)

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 Amazon Bedrock to build a generative AI application. The application must deny any user request that involves asking about the topic of 'mergers and acquisitions'. Which Bedrock feature should the developer use?

A developer is building a customer support chatbot using Amazon Bedrock Agents. The agent needs to retrieve order status by calling an external API. Which configuration enables the agent to call the API?

A developer is using Bedrock Agents to create an order management assistant. The agent needs to check inventory and process payments. Which TWO components are required to enable these capabilities?

A company is building a generative AI application using Amazon Bedrock. They need to ensure that the model does not generate responses containing personally identifiable information (PII) such as credit card numbers or social security numbers. Which Bedrock feature should they configure?

A company wants to evaluate the quality of a text generation model for a summarization task. They have reference summaries written by humans. Which automated metric compares the generated summary to the reference by measuring n-gram overlap?

A developer is building a chatbot that answers questions from a company's internal knowledge base. The knowledge base is updated frequently, and the chatbot must always provide the most current information without retraining the model. Which AWS service or feature is MOST suitable for this requirement?

A data scientist is prototyping a text summarisation application using Amazon Bedrock. They want to quickly test different foundation models and prompts without writing code. Which tool should they use?

A company is building a generative AI application for code generation. They want to minimize costs while maintaining acceptable performance for their workload, which has periodic spikes in demand. Which approach would be MOST cost-effective?

A company uses Amazon Bedrock Agents to automate a multi-step data processing workflow. The agent needs to call an external API to enrich customer records. How should the developer expose this API to the agent?

A company needs to select a vector store for their Amazon Bedrock Knowledge Base. Which TWO options are supported as vector stores? (Choose TWO.)

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 e-commerce company is building a product description generator using Amazon Bedrock. They want to ensure that the generated descriptions do not include any prohibited content (e.g., offensive language or competitor mentions). The company has a list of denied topics and keywords. Which feature should they use?

A company is optimizing costs for a Bedrock application that performs sentiment analysis on customer reviews. The workload is steady with occasional spikes. Which THREE strategies can help reduce costs without sacrificing accuracy? (Choose THREE)

A developer is building an application that translates customer support tickets from English to Spanish using Amazon Bedrock. They need to evaluate the quality of translations. Which automated metric is most appropriate for comparing the model's translations to professional human translations?

A healthcare startup is building a patient inquiry system using Amazon Bedrock. They must ensure the model does not generate responses containing medical advice or unverified treatment suggestions. The compliance team also requires that no personally identifiable information (PII) is output. Which Bedrock feature should the startup configure to meet both requirements?

A company uses Amazon Bedrock to generate product descriptions. They notice that the model sometimes produces factually incorrect information. They want to ensure responses are grounded in company-provided documents. Which Bedrock feature should they enable?

A developer wants to store and search vector embeddings for a RAG application. Which AWS-managed vector store option is serverless and can be used with Amazon Bedrock?

A financial services company uses Amazon Bedrock Knowledge Bases to power a Q&A bot for analysts. They notice that the bot sometimes gives outdated information because documents are updated weekly. They cannot retrain or rebuild the knowledge base weekly. What is the MOST efficient solution?

A company is building a generative AI application to answer questions from a large set of technical manuals. Which TWO services or features can be used together in a RAG architecture on AWS? (Choose TWO.)

A company is using Bedrock Agents to automate multi-step workflows that interact with external APIs and databases. They need to ensure the agent can perform actions like querying a database and calling an API. Which TWO components must be defined to enable these capabilities? (Choose TWO)

A financial services firm is deploying a generative AI chatbot using Amazon Bedrock. They must ensure that the chatbot does not generate investment advice and that it automatically redacts any personally identifiable information (PII) from user inputs before processing. Which TWO Bedrock features should they use?

A data scientist is building a RAG application using Amazon Bedrock Knowledge Bases. The team requires that responses only use information from the uploaded documents and reject queries that are not related to the documents. Which Bedrock feature should be used to enforce this?

A company uses Amazon Bedrock Agents to process user requests that involve multiple steps, such as checking inventory and placing an order. The Agent sometimes fails to complete the workflow because it makes incorrect assumptions about the order of steps. What is the MOST effective way to guide the Agent's reasoning?

An AI team is evaluating a text generation model for a clinical summarization task. They have a set of 100 sample summaries and corresponding expert-written reference summaries. The team wants both automated metrics and human evaluation. Which THREE metrics are appropriate for evaluating summarization quality? (Choose THREE)

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 deploying a generative AI application using Amazon Bedrock. The application must comply with data residency requirements, so all data processing must occur within a specific AWS Region. Additionally, the company wants to reduce latency for end users. Which TWO actions should the company take? (Choose TWO.)

A developer is building an agent using Amazon Bedrock Agents to automate a multi-step workflow that involves querying several databases and APIs. The agent needs to handle intermediate results and decide the next step based on previous outputs. Which capability of Bedrock Agents enables this?

A developer is building a RAG application using Amazon Aurora PostgreSQL with the pgvector extension. After ingesting documents, the vector search returns results that are not always the most relevant. What should the developer adjust to improve relevance?

A developer wants to create an agent using Amazon Bedrock Agents that can call an external API to check inventory levels. What must be defined in the agent configuration to enable this API call?

A data scientist is setting up a RAG pipeline using Amazon Bedrock Knowledge Bases. They need to ingest documents, split them into chunks, generate embeddings, and store them for retrieval. Which TWO steps are part of the ingestion process? (Choose TWO)

A team is evaluating two generative AI models for a summarization task. They have reference summaries and generated summaries. Which automated metric is BEST suited to measure the overlap of n-grams between the generated and reference summaries?

A data scientist is comparing two foundation models for a text classification task. They want to use automated metrics to evaluate performance on a labelled test set. Which metric is most appropriate for a multi-class classification problem?

A company is deploying a Bedrock application that handles sensitive customer data. They must ensure that personally identifiable information (PII) is not included in model responses. Which THREE features of Bedrock Guardrails can help with this requirement? (Choose THREE)

A financial services company is deploying a generative AI application using Amazon Bedrock. They need to ensure that the model does not generate responses containing personally identifiable information (PII) such as credit card numbers or Social Security numbers. The company also wants to block certain topics like investment advice. Which feature should they configure?

A developer implements a RAG pipeline with Amazon Bedrock and Amazon OpenSearch Serverless. Users report that the chatbot sometimes returns off-topic responses. Investigation shows the retrieved chunks are semantically unrelated to the queries. What is the MOST likely cause?

An organization wants to use Amazon Bedrock to generate personalized email content for marketing campaigns. They have a large dataset of customer profiles. Which approach would be MOST cost-effective for high-volume generation?

A company wants to build a GenAI application that translates customer emails from English to Spanish. They need to manage multiple versions of translation prompts and track which version performs best. Which TWO features should they use? (Select TWO.)

A developer is building an Amazon Bedrock Agent to automate multi‑step workflows like booking flights and hotels. The Agent needs to call an external flight reservation API. How should the developer expose this API to the Agent?

A data scientist is using Amazon Bedrock to build a text summarization application. Which component in Bedrock allows the user to experiment with different models and prompts interactively without writing code?

A data scientist needs to compare the performance of two foundation models on a text summarization task. They have reference summaries for 1000 text samples. Which evaluation approach would provide the MOST reliable comparison?

A company is building a generative AI application using Amazon Bedrock that requires low-latency responses for a global user base. They need to select a vector store for the knowledge base. Which two options are fully managed AWS services suitable for this requirement? (Choose TWO.)

A company is using Amazon Bedrock to offer a multi-tenant summarization service. They notice high latency during peak hours. The team wants to reduce per-request latency without degrading quality. Which combination of actions would be MOST effective?

A data scientist wants to quickly prototype different prompt variants for a summarization task using Amazon Bedrock. Which tool should they use for an interactive, no-code experimentation environment?

A company wants to build a generative AI application that can automatically classify customer feedback into positive, neutral, or negative sentiments. Which foundation model capability is BEST suited for this task?

A corporation needs to deploy a chatbot that must not output any personally identifiable information (PII) such as credit card numbers or social security numbers. Which TWO Bedrock features should they use together to achieve this? (Select TWO.)

A company is evaluating different foundation models for a text summarization task using Amazon Bedrock. They want to use automated metrics to compare model outputs against reference summaries. Which TWO metrics are commonly used for summarization evaluation?

A data scientist is prototyping a text generation application using Amazon Bedrock. They want to quickly test different foundation models with various prompts and parameters without writing any code. Which AWS service or feature should they use?

A developer is using Amazon Bedrock Agents to build a multi-step reasoning bot that can query a SQL database and summarize results. Which service should be integrated as the action group's Lambda function to execute SQL queries?

A company uses Amazon Bedrock Agents for customer support. The agent needs to perform multi-step reasoning: first identify the customer's account, then check order status, and finally provide a resolution. Which THREE components must be configured to enable this workflow? (Select THREE.)

A healthcare company needs to build a GenAI application that summarizes patient discharge notes. The compliance team requires that no medical record identifiers (MRIs) appear in the model's output. Which Bedrock Guardrails feature should be configured?

A company uses Amazon Bedrock Agents to automate order processing. The agent needs to call an internal database to check inventory. Which component should be used to integrate the database query?

A financial services company is building a generative AI application using Amazon Bedrock. They need to ensure the model does not generate responses that violate regulatory topics, such as specific prohibited financial advice. Which Bedrock feature should they use to block entire topics?

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 use Amazon Bedrock to translate customer emails from English to Spanish. The emails contain occasional personal names and addresses. Which Guardrail configuration should be applied to protect customer privacy?

A data scientist is prototyping a text summarization application using Amazon Bedrock. They want to quickly test different prompts and models without writing code. Which AWS service or feature should they use?

Which metric is commonly used to evaluate the quality of a text summarization model by comparing the generated summary with a reference summary, measuring the overlap of n-grams?

A team has built a Retrieval-Augmented Generation (RAG) pipeline using Amazon Bedrock Knowledge Bases. After deployment, they find that the model's answers often contain hallucinated details not present in the retrieved documents. What should they enable in Bedrock Guardrails to reduce this?

A developer is building an application using Amazon Bedrock and needs to ensure that the model's responses do not include any toxic or harmful language. Which Bedrock feature should they configure?

A developer wants to invoke a foundation model in Amazon Bedrock with a large number of similar requests for cost savings. Which feature can help reduce inference cost?

A company uses Amazon Bedrock to power a code generation assistant. They notice that the generated code sometimes contains security vulnerabilities. Which approach would BEST address this issue without sacrificing code quality?

A developer is using Bedrock Studio to prototype a summarization application. They want to quickly test different foundation models and prompts without writing code. What should they use?

Which vector store is a fully managed AWS service that can be used with Amazon Bedrock Knowledge Bases for semantic search?

A company is using Amazon Bedrock Knowledge Bases to power a legal document Q&A application. They need to ensure that the model only answers based on the retrieved documents and does not generate information not present in the documents. Which feature should they enable?

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 has created a knowledge base in Amazon Bedrock for a Q&A application. After updating the source documents, they notice that the model still returns old information. What is the MOST likely cause?

A company is deploying a generative AI application using Amazon Bedrock and needs to optimize costs for a high-volume, latency-tolerant workload. Which TWO strategies should they implement? (Select TWO.)

A company wants to use Amazon Bedrock to generate personalized marketing emails. They have thousands of customer profiles with demographic data. To generate tailored content efficiently, the application must dynamically insert customer-specific information into prompts. Which prompt management technique is BEST suited for this?

A company is evaluating the performance of a summarization model using Amazon Bedrock model evaluation. They want an automated metric that measures how well the generated summary captures the meaning of the reference summary. Which metric is MOST suitable?

An enterprise is building a RAG solution with Amazon Bedrock and needs to ensure that the retrieved documents are from authorised sources only. They also must prevent the model from generating responses that contain personally identifiable information (PII). Which two Bedrock features combined address these requirements?

A legal firm uses Amazon Bedrock to generate contract summaries. They want to evaluate the quality of summaries against human-written reference summaries. The evaluation should capture both the overlap of n-grams and the semantic similarity. Which combination of automated metrics is MOST appropriate?

A company is deploying a generative AI application using Amazon Bedrock and needs to optimize costs. They expect variable traffic with occasional high spikes. Which TWO strategies would help reduce costs while maintaining performance?

A data scientist is building a RAG application using Amazon Bedrock Knowledge Bases. They want to ensure that only the most semantically relevant documents are retrieved for each query. Which embedding model characteristic is MOST important for this requirement?

A financial institution uses Amazon Bedrock to generate investment summaries. They must prevent the model from discussing prohibited topics like insider trading. Which Bedrock feature should be applied to the model invocation?

A data scientist is evaluating two different foundation models for a summarization task. They want to compare the quality of summaries generated by each model against a set of human-written reference summaries. Which set of metrics is most appropriate for this automated evaluation?

A company wants to reduce the cost of running a large number of inference requests for a text classification task. The responses can tolerate a slight delay. Which cost optimization strategy should they implement?

A developer needs to reduce costs for a Bedrock application that processes high volumes of similar queries. The queries are repetitive and the model is invoked many times with the same prompt. Which cost optimization technique is MOST suitable?

A company is using Amazon Bedrock Agents to build a travel booking assistant that can search for flights, book hotels, and answer questions about travel policies. Which TWO components are required to enable the agent to call external services? (Select TWO.)

A developer wants to quickly test different prompts and models for a text summarization task without writing any code. Which AWS service should they use?

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 AWS service allows teams to collaborate on building generative AI applications with a visual interface, share prompts, and manage prompt versions?

A company wants to prevent an Amazon Bedrock chatbot from discussing specific prohibited topics like competitor pricing. Which Bedrock feature should they configure?

A data science team is evaluating the output quality of a text generation model. They want to use both automated metrics and human judgment. Which THREE approaches should they include in their evaluation strategy? (Select THREE.)

Which of the following is a primary benefit of using Bedrock Agents for building generative AI applications?

A financial services company uses Bedrock Agents to automate a multi-step loan approval process. The agent needs to call an external credit scoring API and a compliance database, then combine results. The agent currently fails when the API returns a 503 error. How should the practitioner address this?

A company uses Amazon Bedrock Agents to automate a multi-step customer support workflow. The agent needs to query a customer database and update a ticket system. Which TWO components are required to enable the agent to interact with these external systems?

An application needs to store and search vector embeddings of 10 million documents for a RAG system. Which Amazon vector store is a fully managed, serverless option that integrates natively with Amazon Bedrock Knowledge Bases?

A company is building a content generation application using Amazon Bedrock. They need to ensure that the model does not generate offensive content and also avoids discussing certain prohibited topics. Which TWO Bedrock features should be combined to achieve this?

A data scientist is using Amazon Bedrock to build a question-answering system over a large corpus of technical manuals. They want to ensure that the model's answers are grounded in the retrieved documents and that the model does not hallucinate. Which feature should they enable?

A company uses Amazon Bedrock with a Knowledge Base for RAG. Users report that the assistant gives incorrect answers for questions that require understanding of data tables. After reviewing, the team suspects the chunking strategy is breaking table structures. Which change would BEST preserve the integrity of tabular data?

A company is building a document summarization application using Amazon Bedrock. They want to prototype the application quickly by testing different models and prompts interactively. Which AWS service or feature should they use?

A financial services firm wants to deploy a generative AI application that answers customer questions about account balances and recent transactions. The firm has strict latency requirements (responses under 2 seconds) and wants to minimize costs. Which strategy for model selection and deployment is MOST appropriate?

A company is building a RAG application that indexes thousands of PDF documents. They notice that some documents are very long (hundreds of pages) and the vector search often returns irrelevant chunks. Which configuration change would MOST improve retrieval relevance?

A company has built a RAG application using Amazon Bedrock Knowledge Bases. Users report that answers are sometimes based on irrelevant or incorrect document chunks. The team has verified that the embedding model is appropriate and the documents are correctly indexed. What is the MOST likely cause of the poor retrieval quality?

A startup is building a code generation assistant using a large language model. They want to evaluate the quality of generated code compared to reference implementations. Which automated metric is MOST suitable for this task?

A company is evaluating the performance of their question-answering model using Amazon Bedrock's model evaluation feature. They want to assess both the factual accuracy and the fluency of the generated answers. Which THREE metrics should they choose? (Select THREE.)

A company uses Amazon Bedrock to generate marketing copy. They want to evaluate the quality of generated text against human-written reference texts using automated metrics. Which metric measures the overlap of n-grams between generated and reference text?

A company is building a RAG solution using Amazon Bedrock Knowledge Bases. Which TWO steps are essential in the document ingestion pipeline? (Select TWO.)

A developer is building an agent using Amazon Bedrock Agents. The agent needs to call an external API to retrieve weather data. What must the developer define to enable this capability?

A company is deploying a real-time chatbot using Amazon Bedrock and expects high traffic during business hours. They want to minimise inference costs while maintaining low latency. Which combination of strategies would be MOST effective?

A company is implementing a Retrieval-Augmented Generation (RAG) pipeline with Amazon Bedrock Knowledge Bases. They need to store vector embeddings for their documents. Which vector store options are natively supported by Bedrock Knowledge Bases?

A company is using Amazon Bedrock to run batch inference on millions of customer support transcripts for sentiment analysis. Which approach is MOST cost‑effective and fastest for this workload?

What is the primary purpose of chunking in a Retrieval-Augmented Generation (RAG) pipeline?

A developer is using Amazon Bedrock Knowledge Bases to build a Q&A chatbot. The knowledge base contains PDF documents that are ingested and chunked. After ingestion, the chatbot sometimes returns irrelevant answers. What is the most likely cause?

A data science team is evaluating a text classification model built using Amazon Bedrock. They want to compare its performance against a baseline using automated metrics. Which three metrics are appropriate for evaluating a text classification model? (Choose THREE.)

A company is deploying a generative AI application for customer support. They need to ensure that the model does not generate responses containing personally identifiable information (PII) even if it appears in the retrieved context. Which Bedrock feature should they configure?

A developer is building a multi-step reasoning agent using Amazon Bedrock Agents. The agent needs to first check inventory levels via a database query, then call a shipping API to calculate delivery dates, and finally compose a response. How should the developer define the tool integrations?

A developer is building a RAG application on Amazon Bedrock. They notice that the model sometimes generates answers that are not supported by the retrieved documents. To reduce this, they want to enforce that the model only uses the provided context. Which Bedrock feature should they use?

A company is building a generative AI application using Amazon Bedrock. They need to implement a RAG pipeline that ingests PDF documents, processes them, and stores embeddings for retrieval. Which THREE steps are essential in this pipeline?

A team is deploying a sentiment analysis application using Amazon Bedrock. They need to ensure the model returns only 'positive', 'negative', or 'neutral'. Which prompt engineering technique is BEST suited for this requirement?

A developer is evaluating generative AI models for a code generation task. Which THREE metrics are commonly used for automated evaluation of generated code? (Choose THREE.)

Which AWS service is used as a vector store in Amazon Bedrock Knowledge Bases for storing and retrieving embeddings?

A company is using Amazon Bedrock to build a sentiment analysis application for customer reviews. They need to evaluate the model's performance against a labeled test dataset. They want to use a metric that compares the model's predicted sentiment (positive, negative, neutral) to the ground truth labels. Which metric 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 developer is building an agent using Amazon Bedrock Agents to handle customer support inquiries. The agent needs to look up order status from a database and escalate complex issues to a human. Which THREE components are essential for this agent?

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 building a chatbot that must refuse to answer questions about internal financial data. They also need to filter out any offensive language from user inputs. Which TWO Bedrock features should they use? (Choose TWO.)

A company wants to use Amazon Bedrock to generate product descriptions for an e-commerce catalog. They need to process 100,000 product records efficiently and cost-effectively. Which inference option should they choose?

A company wants to build a multi-language customer support chatbot using Amazon Bedrock. The chatbot should support English, Spanish, and French. The team needs to translate user queries into English before processing and then translate responses back. Which TWO approaches could achieve this? (Choose TWO)

A developer is using Bedrock Agents to create a travel planning assistant. The agent needs to call a hotel booking API and a flight API. What is the correct way to define these external API calls in Bedrock Agents?

A company is using Amazon Bedrock Knowledge Bases with a RAG pipeline. They want to improve the relevance of retrieved chunks for user queries. Which TWO configuration changes are likely to help?