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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. An ML engineer is developing a RAG application in Python and wants to use the TruLens SDK to trace the distinct phases of its execution, specifically the context retrieval and answer generation steps. They aim to clearly differentiate the tracing of the function responsible for retrieving context.

A)

B)

C)

D)

E)

2. A data engineer is building an AI data pipeline to automatically extract specific sentiment categories from customer reviews using 'AI_COMPLETE. They want the output to be a structured JSON object containing 'food_quality', 'food_taste', 'wait_time', and 'food cost' with their respective sentiments (e.g., 'positive', 'negative', 'neutral'). The engineer aims for high accuracy and ensures that all these fields are present in the output. Which of the following statements correctly describe the approach to achieve this?

A) For optimal accuracy in structured output, it is always best to explicitly instruct the LLM within the prompt to 'Respond in JSON' and provide a detailed description of the schema, regardless of task complexity.
B) When using OpenAl (GPT) models for structured output, the 'additionalPropertieS field must be set to 'true' in every node of the schema to allow for flexibility in the generated JSON.
C) The 'response_format' argument in 'AI COMPLETE should specify a JSON schema, and to ensure all fields are present, the 'required' field must be explicitly set for all desired properties in the schema.
D) The 'temperature' option should be set to a high value (e.g., 0.9) in the 'CompleteOptionS to encourage the model to strictly adhere to the specified JSON schema and reduce non-deterministic responses.
E) To improve accuracy, the JSON schema should include detailed descriptions for each field (e.g., 'food_quality', 'food_taste') to guide the model more precisely in identifying and extracting the sentiments.

3. 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?

A) Option A
B) Option D
C) Option B
D) Option E
E) Option C

4. A data scientist is tasked with improving the accuracy of an LLM-powered chatbot that answers user questions based on internal company documents stored in Snowflake. They decide to implement a Retrieval Augmented Generation (RAG) architecture using Snowflake Cortex Search. Which of the following statements correctly describe the features and considerations when leveraging Snowflake Cortex Search for this RAG application?

A) Enabling change tracking on the source table for the Cortex Search Service is optional; the service will still refresh automatically even if change tracking is disabled.
B) The
C) Cortex Search automatically handles text chunking and embedding generation for the source data, eliminating the need for manual ETL processes for these steps.
D) To create a Cortex Search Service, one must explicitly specify an embedding model and manually manage its underlying infrastructure, similar to deploying a custom model via Snowpark Container Services.
E) For optimal search results with Cortex Search, source text should be pre-split into chunks of no more than 512 tokens, even when using models with larger context windows like

5. A Gen AI Specialist is responsible for maintaining a Cortex Analyst-powered application. They have defined a semantic model that includes a Verified Query Repository (VQR) to guide user interactions. The application front-end uses the Suggested Questions feature to help users get started. The specialist wants to ensure that a specific set of critical, verified business questions are always displayed to users, regardless of their prior input or the semantic similarity to their current query. Which of the following configuration steps in the semantic model YAML will achieve this requirement?

A)

B)

C)

D)

E)

Solutions: