SnowPro Specialty Gen AI Practice Questions & Answers • ExamPrepare

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Question 1

A Gen AI Specialist is setting up a CoCo CLI on a new development machine. The organization already uses Snowflake CLI for managing Snowflake Objects.

How does CoCo CLI handle Snowflake connection configuration during initial setup?

It generates a dedicated configuration file stored in the CoCo installation directory.
It establishes connections exclusively through environment variables set at the operating system level.
It requires a new API key to be created through the Snowflake web interface.
It uses existing connection profiles from the shared connections file.

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Question 2

A product team is building an enterprise search application over a product catalog that is stored in Snowflake. The catalog has three columns:

1. product_sku which has short product codes requiring exact matching

2. product_description which has long free-text content requiring semantic understanding

3. category which has short text terminology that needs both exact and semantic matching

The team notices that enabling semantic reranking is increasing query latency.

Which architecture will support the column indexing requirements while optimizing query performance?

Create a single vector index using SPLIT_TEXT_RECURSIVE_CHARACTER to chunk all three columns uniformly for semantic matching.
Create three Cortex Search services (one for each column with the required index types) and merge the results using reciprocal rank fusion in the application code.
Create a single-column Cortex Search service with a vector index on product_description , then use AI_SIMILARITY to re-score the results from product_sku and category .
Create a multi-index Cortex Search service with product_sku as a text index, product_description as a vector index, and category as both index types; then set scoring_config.reranker = 'none' .

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Question 3

A Gen AI Specialist is building a Streamlit chatbot that leverages AI_COMPLETE to answer user questions with this script:

import streamlit as st

import snowflake.cortex

from snowflake.cortex import CompleteOptions

if prompt := st.chat_input("How can I help you?"):

with st.chat_message(name="User"):

st.write(prompt)

with st.chat_message("assistant"):

response = snowflake.cortex.complete(

"claude-3-5-sonnet",

[dict(role='user', content=prompt)],

Which parameter should be added to the script so that responses appear incrementally in small chunks, as the responses are generated?

deadline=5
stream=True
options=CompleteOptions(max_tokens=5)
options=CompleteOptions(response_format="incremental")

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Question 4

A team repeatedly requests that one filter be applied on the same two product grouping columns to run data analyses.

Which field can be configured in Snowflake Cortex Analyst to apply the filter on column X whenever there is a filter applied on column Y?

relationship_type
relationship_columns
custom_instructions
cortex_search_service

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Question 5

A company uses a Cortex Agent to analyze internal documents. An indirect prompt injection causes a stored procedure running with owner privileges to access Personally Identifiable Information (PII) beyond the user's permissions, and the team finds that prompt details in the audit logs are redacted. The fix must prevent the unauthorized access, protect against prompt injection, and allow auditors to view unredacted logs.

What approach should the team use?

Configure the stored procedure as EXECUTE AS OWNER , isolate untrusted document context, and grant READ UNREDACTED AI OBSERVABILITY EVENTS TABLE to the auditor role.
Configure the stored procedure as EXECUTE AS CALLER , isolate untrusted document context, and grant READ UNREDACTED AI OBSERVABILITY EVENTS TABLE to the auditor role.
Configure the stored procedure as EXECUTE AS CALLER , isolate untrusted document context, and grant AI_OBSERVABILITY_READER to the auditor role.
Configure the stored procedure as EXECUTE AS CALLER , sanitize the document text and keep trusting it in prompts, and grant READ UNREDACTED AI OBSERVABILITY EVENTS TABLE to the auditor role.

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Question 6

A Data Engineer is running a pipeline to transcribe a set of audio files stored on an internal stage. The pipeline calls the AI_TRANSCRIBE function. The pipeline execution failed with the error message No response from server.

What is the MOST likely cause of this error?

The audio file was not recognized and the function timed out while Snowflake attempted to identify the format.
The audio files are too large and the function timed out while the files were being transcribed.
The audio files contain a language that is not supported by AI_TRANSCRIBE .
The audio file could not be retrieved due to an expired scoped URL.

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