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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A data engineer is setting up an automated pipeline to process incoming documents using Snowflake's AI_PARSE DOCUMENT function. To ensure the pipeline functions without errors, which of the following input requirements or limitations must be strictly adhered to?

A) For HTML and TXT files, billing for AI_PARSE_DOCUMENT is based on each chunk of 3,000 characters, with the last chunk also being billed even if shorter.
B) All documents must be stored in an internal or external stage, but only internal stages support server-side encryption with the SNOWFLAKE_SSE type.
C) Supported file formats for processing include PDF, PPTX, DOCX, JPEG, JPG, PNG, TIFF, TIF, HTML, and TX T, covering a wide range of common document and image types.
D) The maximum file size for any document processed by is AI_PARSE_DOCUMENT 100 MB, and it can handle up to 300 pages per document.
E) To optimize performance, queries calling the Cortex AI_PARSE_DOCUMENT function should be executed in a large warehouse (e.g., XL or larger), as bigger warehouses increase processing speed for this function.

2. A Gen AI Specialist needs to extract the 'invoice number' and 'total_amount' from a specific invoice PDF, 'invoice_001 .pdf, located in an internal stage named They want to use the default (latest) model build version for a model named 'invoice_processor'. Which SQL query correctly uses the '!PREDICT method to extract the required information, and what key fields would be present in the JSON output for a successful extraction of 'invoice_number' and 'total_amount'?

A)

B)

C)

D)

E)

3. A Streamlit application developer wants to use AI_COMPLETE (the latest version of COMPLETE (SNOWFLAKE. CORTEX)) to process customer feedback. The goal is to extract structured information, such as the customer's sentiment, product mentioned, and any specific issues, into a predictable JSON format for immediate database ingestion. Which configuration of the AI COMPLETE function call is essential for achieving this structured output requirement?

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

4. An administrator has configured the 'CORTEX MODELS ALLOWLIST' parameter to only permit the 'mistral-large? model at the account level. A user with the 'PUBLIC' role, which has been granted 'SNOWFLAKE.CORTEX USER and 'SNOWFLAKE."CORTEX- MODEL-ROLE-LLAMA3.1-70B"' , attempts to execute several 'AI_COMPLETE queries. Which of the following queries will successfully execute?

A)

B)

C)

D)

E)

5. 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?

A) Rely solely on a comprehensive list of 'stop sequences' to end generation when the summary is complete.
B) Provide a 'task description' focusing on broad themes and set 'top_p' to 0.5 to balance creativity and relevance.
C) Instruct the model to 'think out loud' with an inner monologue in the prompt, and set 'max_tokens' to a large value to allow full reasoning.
D) Use a system prompt defining a persona like 'creative writer' and set 'temperature' to 0.9 to encourage diverse summaries.
E) Implement 'first principles thinking' in the prompt, clearly outlining logical steps for summarization, and set 'temperature' to 0 for deterministic output.

Solutions: