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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A company is developing a Streamlit application leveraging Snowflake Cortex Analyst for natural language querying over sales data.
They want to implement a robust multi-turn conversational experience where users can ask follow-up questions. Which of the following statements accurately describe the design and cost implications of supporting multi-turn conversations in Cortex Analyst? (Select all that apply)

A) The cost for Cortex Analyst's multi-turn conversational support is primarily based on the number of messages processed, and the number of tokens within each message does not directly affect the per-message cost.
B) When an LLM judge is used to evaluate the summarization quality for multi-turn conversations, a smaller model like Llama 3.1 8B is generally preferred over Llama 3.1 70B to minimise latency, even if it leads to a slightly higher error rate in rewritten questions.
C) Developers can manually implement multi-turn conversations in their applications by using the
D) An internal LLM summarization agent is automatically employed by Cortex Analyst before its original workflow to reframe follow-up questions based on conversation history, optimising LLM processing for each agent.
E) Cortex Analyst supports multi-turn conversations by simply passing the entire conversation history directly to every LLM call within its agentic workflow, which is the most efficient method for maintaining context.

2.

A)

B) Cross-region inference is automatically managed by Snowflake for allowed models, implying that a new, larger virtual warehouse is required to handle the cross- region data transfer overhead.
C)

D)

E)

3. A data scientist is optimising a Cortex Analyst application to improve the accuracy of literal searches within user queries, especially for high-cardinality dimension values. They decide to integrate Cortex Search for this purpose. Which of the following statements are true about this integration and the underlying data types in Snowflake? (Select all that apply)

A) Cortex Search Services, when configured as a source for Snowflake dynamic tables, automatically refresh their search index with continuous data updates, maintaining low-latency search results.
B) The cost for embedding data into a Cortex Search Service is primarily incurred per output token generated by the embedding model, as these represent the final vector embeddings, rather than input tokens.
C) To integrate Cortex Search with a logical dimension, the semantic model YAML must include a block within the dimension's definition, specifying the service name and optionally a 'literal_column' .
D) The "VECTOR data type in Snowflake, used to store embeddings generated for Cortex Search, is fully supported as a clustering key in standard tables and as a primary key in hybrid tables to accelerate vector similarity searches.
E) For optimal RAG retrieval performance with Cortex Search, it is generally recommended to split text into chunks of no more than 512 tokens, even when using embedding models with larger context windows such as 'snowflake-arctic-embed-l-v2.0-8k'.

4. A data scientist has fine-tuned a Hugging Face sentence transformer model for semantic search and intends to deploy it to Snowpark Container Services (SPCS) via the Snowflake Model Registry. The model requires GPU acceleration and specific Python packages ('sentence-transformerS, 'torch', 'transformers'). A GPU compute pool named 'my_gpu_pool' is available. Which of the following code snippets correctly logs the model and deploys it as a service to SPCS, ensuring it utilizes the GPU compute pool and has the necessary Python dependencies for the Hugging Face model and PyTorch?

A)

B)

C)

D)

E)

5. A data engineering team needs to configure their Snowflake environment to process documents using AI_PARSE_DOCUMENT and generate text embeddings using EMBED_TEXT_1024 with the voyage-multilingual-2 model. Their Snowflake account is in a region where these specific capabilities or models are only available via cross-region inference. The team needs to ensure these functions work correctly without constant region-specific model selection. Which of the following is the correct configuration action and an important consideration?

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

Solutions: