Class: Strata::CLI::AI::Services::TableGenerator

Inherits:
Object
  • Object
show all
Defined in:
lib/strata/cli/ai/services/table_generator.rb

Overview

Generates semantic model fields from database table metadata using AI. Returns structured JSON for use in the field editor.

Constant Summary collapse

SYSTEM_PROMPT = 
<<~PROMPT
  You are a semantic modeling expert for analytics and BI systems.
  Analyze database columns and generate semantic field definitions.

  For each column, determine:
  - name: Human-friendly field name (e.g., "customer_id" → "Customer ID")
  - description: Brief description of what this field represents
  - schema_type: "dimension" for categorical/text, "measure" for numeric aggregations
  - data_type: string, integer, bigint, decimal, date, date_time, boolean
  - expression: SQL expression (for measures include aggregation like "sum(amount)")
  - synonyms: Array of 2-4 alternative names users might use to refer to this field.
    These help AI search and natural language queries find the right field.
    Example: "Customer ID" → ["cust id", "client id", "buyer id"]

  Output ONLY valid JSON array, no explanations.
PROMPT

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(client: Client.new) ⇒ TableGenerator

Returns a new instance of TableGenerator.



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# File 'lib/strata/cli/ai/services/table_generator.rb', line 32

def initialize(client: Client.new)
  @client = client
end

Instance Attribute Details

#client ⇒ Object (readonly)

Returns the value of attribute client.



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# File 'lib/strata/cli/ai/services/table_generator.rb', line 30

def client
  @client
end

Instance Method Details

#ai_available? ⇒ Boolean

Check if AI is available

Returns:

  • (Boolean) 


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# File 'lib/strata/cli/ai/services/table_generator.rb', line 96

def ai_available?
  @client.enabled?
end

#call(table_name:, columns:, datasource:, user_context: nil) ⇒ Hash?

Generate field definitions from table metadata

Parameters:

  • table_name (String) —

    Full table name (schema.table)

  • columns (Array<Hash>) —

    Column metadata with :name, :type

  • datasource (String) —

    Datasource key

  • user_context (Hash, nil) (defaults to: nil) —

    Optional user-provided context with :description

Returns:

  • (Hash, nil) —

    Generated model data or nil if AI disabled



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# File 'lib/strata/cli/ai/services/table_generator.rb', line 42

def call(table_name:, columns:, datasource:, user_context: nil)
  unless ai_available?
    warn "AI not available - using rule-based fallback"
    return fallback_fields(columns)
  end

  existing_models = load_existing_models_context
  prompt = build_prompt(
    table_name: table_name,
    columns: columns,
    existing_models_context: existing_models,
    user_context: user_context
  )

  begin
    response = @client.complete(prompt, system_prompt: SYSTEM_PROMPT)
    parse_response(response, columns)
  rescue => e
    # Fallback to basic field generation on AI error
    warn "AI failed to generate fields: #{e.message} - performing basic field generation"
    fallback_fields(columns)
  end
end

#call_with_prompt(table_name:, columns:, datasource:, user_prompt:, current_fields:) ⇒ Array<Hash>

Generate fields with user prompt for modification/regeneration

Parameters:

  • table_name (String) —

    Full table name

  • columns (Array<Hash>) —

    Column metadata

  • datasource (String) —

    Datasource key

  • user_prompt (String) —

    User’s natural language prompt

  • current_fields (Array<Hash>) —

    Current field definitions

Returns:

  • (Array<Hash>) —

    Regenerated fields



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# File 'lib/strata/cli/ai/services/table_generator.rb', line 73

def call_with_prompt(table_name:, columns:, datasource:, user_prompt:, current_fields:)
  unless ai_available?
    warn "AI not available - could not use prompt mode"
    return nil
  end

  prompt = build_prompt_with_user_input(
    table_name: table_name,
    columns: columns,
    user_prompt: user_prompt,
    current_fields: current_fields
  )

  begin
    response = @client.complete(prompt, system_prompt: SYSTEM_PROMPT)
    parse_response(response, columns)
  rescue => e
    warn "AI failed to generate fields: #{e.message}"
    nil
  end
end