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Snowflake Agent Guide

Access Snowflake cloud data warehouse with natural language or direct SQL.

Overview

  • SnowflakeAgent - AI-powered natural language to SQL
  • SnowflakePassthroughAgent - Direct SQL execution

Usage Examples

# AI-assisted analytics queries
lui("Show me daily revenue trends for the last quarter", agent="SnowflakeAgent")

# Semi-structured data analysis
lui("Extract user behavior patterns from our JSON event logs", agent="SnowflakeAgent")

# Direct SQL with Snowflake features
lui("SELECT * FROM customers AT(TIMESTAMP => '2024-01-15 10:00:00'::timestamp)", 
    agent="SnowflakePassthroughAgent")

# JSON operations
lui("SELECT raw_json:user_id::string, raw_json:event_type::string FROM events", 
    agent="SnowflakePassthroughAgent")

Common Patterns

  • Time series analytics
  • Semi-structured data processing
  • Cost optimization analysis
  • Time travel queries

Integration

Extract data with SnowflakeAgent, then create features with CodeAgent or visualize with PerspectiveAgent.