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A developer is instrumenting a RAG application using the TruLens SDK within Snowflake AI Observability. The application has distinct functions for retrieving context and generating a completion. To ensure clear tracing and readability, which span_type should ideally be used for the function responsible for retrieving relevant text from the vector store?
A.
B.
C.
D.
E. No specific span_type is needed; the default instrumentation is sufficient for all functions.
Answer: A
Explanation:
The TruLens SDK allows for specifying span_type to improve the readability and understanding of traces. For a RAG application, RETRIEVAL the span type is explicitly recommended for search services or retrievers (functions that retrieve context). GENERATION is used for LLM inference calls that generate answers, and RECORD_ROOT identifies the entry point method of the application.
NEW QUESTION # 291
A legal department uses Snowflake to manage and review large volumes of contracts. They need to automate the process of finding specific pieces of information, such as the effective_date or involved_parties, from these unstructured contract texts. They are considering using SNOWFLAKE. CORTEX. EXTRACT_ANSWER. Which characteristic correctly describes the primary intent or behavior of SNOWFLAKE. CORTEX. EXTRACT_ANSWER, distinguishing it from other LLM functions?
A. It transforms an input document into a summarized version, reducing its length while preserving key information.
B. It is primarily designed to generate entirely new text based on a given prompt, much like a conversational AI.
C. It classifies an input text into one of several predefined categories provided by the user.
D. It evaluates a text and returns a numeric score indicating the overall positive or negative sentiment.
E. It focuses on identifying and returning a direct answer to a specific question contained within the provided source document.
Answer: E
Explanation:
Option D is correct. The 'SNOWFLAKE.CORTEX.EXTRACT_ANSWER function is specifically designed to extract an answer to a given question from a text document. Option A describes the 'COMPLETE function. Option B describes the 'SENTIMENT function. Option C describes the 'CLASSIFY_TEXT function. Option E describes the 'SUMMARIZE function.
NEW QUESTION # 292
An enterprise is deploying a new RAG application using Snowflake Cortex Search on a large dataset of customer support tickets. The operations team is concerned about managing compute costs and ensuring efficient index refreshes for the Cortex Search Service, which needs to be updated hourly. Which of the following considerations and configurations are relevant for optimizing cost and performance of the Cortex Search Service in this scenario?
A. CHANGE_TRACKING
B. For embedding text, selecting a model like
C. The
D. For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
E. The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GB/month) having a minimal impact on overall billing.
Answer: A,B,C,D
Explanation:
Option A is correct because a Cortex Search Service requires a virtual warehouse to refresh the service, which runs queries against base objects when they are initialized and refreshed, incurring compute costs. Option B is correct because the cost of embedding models varies. For example, 'snowflake-arctic-embed-m-v1.5 costs 0.03 credits per million tokens, while 'voyage-multilingual-2 costs 0.07 credits per million tokens. Choosing a more cost-effective model like 'snowflake-arctic-embed-m-v1.5' for English-only data can reduce token costs. Option C is correct because Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service to achieve optimal performance. Option D is correct because change tracking is required for the Cortex Search Service to be able to detect and process updates to the base table, enabling incremental refreshes that are more efficient than full re-indexing. Option E is incorrect because Cortex Search Services incur costs based on virtual warehouse compute for refreshes, 'EMBED_TEXT_TOKENS' cost per input token, and a charge of 6.3 Credits per GB/mo of indexed data. The volume of indexed data has a significant impact, not minimal.
NEW QUESTION # 293
A security architect is configuring access controls for a new custom role, 'document_processor_role' , which will manage Document AI operations within a designated database 'doc_processing_db' and schema 'doc_workflow_schema'. The goal is to grant only the minimum essential database-level role required to begin working with Document AI features.
A.
B.
C.
D.
E.
Answer: D
Explanation:
To work with Document AI, the database role must be granted to the account role. This role specifically enables creating Document AI model builds and working on document processing pipelines. Option A grants a more general Cortex user role, which is not the specific foundational role for Document AI. Option B grants access to all Cortex models, but not the foundational Document AI database role itself. Options D and E grant schema-level or warehouse-level privileges, which are also necessary but are not the database-level 'role' specifically for DocumentAI capabilities.
NEW QUESTION # 294
A data engineering team is building an automated pipeline in Snowflake to process customer reviews. They need to use AI_COMPLETE to extract specific details like product, sentiment, and issue type, and store them in a strictly defined JSON format for seamless downstream integration. They aim to maximize the accuracy of the structured output and manage potential model limitations. Which statements accurately reflect the best practices and characteristics when using AI_COMPLETE with structured outputs for this scenario?
A. Option E
B. Option B
C. Option A
D. Option D
E. Option C
Answer: A,B,E
Explanation:
Option A is incorrect because Structured Outputs do not incur additional compute cost for the overhead of verifying each AI_COMPLETE token against the supplied JSON schema, though the number of tokens processed (and thus billed) can increase with schema complexity. Option B is correct because for complex reasoning tasks, it is recommended to use the most powerful models and explicitly add 'Respond in JSON' to the prompt to optimize accuracy. Option C is correct as for OpenAI (GPT) models, the schema has specific requirements: response_format must be set to in every node, and the field must include the names of every property in the schema. Option D additionalProperties false required is incorrect because verifies each generated token against the JSON schema to ensure conformity, and if the model cannot generate a AI_COMPLETE response that matches the schema, it will result in a validation error. Option E is correct as setting the option to e is recommended for temperature the most consistent results, regardless of the task or model, especially for structured outputs.
NEW QUESTION # 295
......
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