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Snowflake SnowPro® Specialty: Gen AI Certification Exam Sample Questions (Q293-Q298):

NEW QUESTION # 293
A Gen AI developer is using 'SNOWFLAKE.CORTEX.COMPLETE" to generate concise summaries of legal documents. Initially, the LLM sometimes provides overly creative or slightly off-topic responses, indicating potential 'hallucinations' or a lack of focus. To improve the factual accuracy and conciseness of the summaries, which combination of prompt engineering techniques and 'COMPLETE' function options should be prioritized?

Answer: B

Explanation:
To reduce 'hallucinations' and improve factual accuracy and conciseness, applying 'first principles thinking' by breaking prompts into logical steps helps the model respond from foundational concepts rather than assumptions. Setting 'temperature' to 0 yields the most consistent and deterministic results, which is crucial for factual accuracy and conciseness in summaries. Defining a 'creative writer' persona or using a high 'temperature' would increase diversity and potentially lead to more hallucinations (Option A). Instructing the model to 'think out loud' (Option C) enhances transparency of thought but does not directly enforce factual accuracy or conciseness in the way 'first principles' and low 'temperature' do. 'max_tokens' (Option C) affects output length, not necessarily accuracy or conciseness. A broad 'task description' (Option D) might not be specific enough, and 'top_p' also influences diversity. 'Stop sequences' (Option E) help with truncation but do not prevent factual errors or improve conciseness directly from the model's generation process.


NEW QUESTION # 294
A data science team is deploying a custom real-time inference service for a fine-tuned LLM using Snowpark Container Services (SPCS). They have a Docker image in their Snowflake image repository. They need to define the service using a YAML specification file. Which of the following are ''essential'' components or configurations that must be included in the 'spec.yaml' file for a long- running service that uses this image, custom environment variables, and requires external access?

Answer: C,D,E

Explanation:
Option A is correct because the 'container' block, specifying the 'name' of the container and the Docker 'image' path from the Snowflake registry, is fundamental for defining any containerized service in SPCS. Option B is correct as the 'endpoints' block, explicitly defining a 'name', -port', and setting 'public: true' , is essential for a long-running service that requires external access via a web browser or API. Option C is incorrect because the 'compute_poor is specified during the 'CREATE SERVICE SQL command, not within the 'spec.yaml' file itself. Option D is incorrect as a 'volumes' block, while potentially useful for persistent storage, is not listed as an essential component in the provided spec.yaml' examples for basic service deployment and is not explicitly mentioned as a required part of the specification file. Option E is correct as the 'env' block within a container definition is used to set custom environment variables, which is explicitly shown in the Jupyterlab example for configuring the application within the container.


NEW QUESTION # 295
A developer is building an interactive chat application in Snowflake leveraging the COMPLETE (SNOWFLAKE. CORTEX) LLM function to power multi-turn conversations. To ensure the LLM maintains conversational context and generates coherent responses based on prior interactions, which of the following methods correctly implements the passing of conversation history to the COMPLETE function?

Answer: A

Explanation:
To provide a stateful, conversational experience with the 'COMPLETE (SNOWFLAKE.CORTEX)' function, all previous user prompts and model responses in the conversation must be passed as part of the argument. This argument is an array of objects, with each object representing a turn in the conversation and containing a 'role' ('system', 'user', or 'assistant') and a 'content' key, presented in chronological order. Option A is less effective as it loses the structured conversational context that roles provide. Option C is incorrect because 'COMPLETE' does not retain any state from one call to the next; conversational history must be explicitly managed and passed. Option D describes a non-existent parameter for the 'COMPLETE function. Option E, while fine-tuning is a Snowflake Cortex capability, it is used to customize a model for a specific task over time, not for real-time maintenance of dynamic conversational context in a multi-turn chat.


NEW QUESTION # 296
A SnowPro-certified engineer is tasked with setting up AI Observability for a new generative AI application built using Snowpark Python. The application relies on external Python libraries (e.g., TruLens SDK components) and will process sensitive financial documents. Which of the following steps are crucial for the successful setup and secure operation of AI Observability within Snowflake, given these considerations?

Answer: A,B,E


NEW QUESTION # 297
An organization is implementing a two-tier LLM access control strategy in Snowflake. First, common models like 'mistral-7b' and 'llama3.1-8b' need to be broadly accessible to all users granted the 'SNOWFLAKE-CORTEX USER database role. Second, a specialized data science team, using the ANALYST ROLE', requires exclusive access to the higher-capability 'claude-3-5- sonnet' model, which should NOT be generally available through the broad access mechanism. Which set of SQL commands, executed by the 'ACCOUNTADMIN" role, correctly establishes this access control strategy?

Answer: C

Explanation:
Option A is correct. This sequence first uses 'ALTER ACCOUNT SET CORTEX MODELS_ALLOWLIST to make 'mistral-7b' and broadly available by their plain names to any user with The call ensures these changes are applied. Then, it grants the specific application role 'SNOWFLAKE."CORTEX-MODEL-ROLE-CLAUDE-3-5-SONNET"' directly to , providing exclusive access to that model without adding it to the general allowlist. Option B is incorrect because adding 'claude-3-5-sonnet' to the account-level would make it generally available, violating the requirement for exclusive access. Option C is incorrect because granting individual application roles to 'PUBLIC' for 'mistral-7b' and is not the method described for making them broadly accessible via an account parameter (allowlist). While it provides access, it doesn't align with the 'broadly accessible...via a Snowflake account parameter' part of the requirement. Option D is incorrect as 'ALTER ACCOUNT UNSET removes the broad access for 'mistral-7b' and Additionally, direct 'GRANT USAGE ON MODELS is not the primary mechanism for controlling access to base Cortex models; rather, application roles are used. Option E is incorrect because the 'ALTER ACCOUNT command for 'CORTEX MODELS_ALLOWLIST can only be executed by the 'ACCOUNTADMIN' role, not 'SECURITYADMIN'.


NEW QUESTION # 298
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