The Param class represents a parameter placeholder that allows you to create dynamic queries where values are provided during execution rather than at query definition time. This enables reusable query templates with runtime customization.

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Constructor

Create a new parameter with the specified configuration. 
Param(name, description=None, default=None, options=None)

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Parameters

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name
str
required
The unique name of the parameter. This identifier is used when providing values during query execution.
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description
str | None
default:"None"
Description of the parameter. Used for natural language query processing to help understand the parameter’s purpose.
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default
ParamInputType | None
default:"None"
Default value to use if not overridden by query parameters. Natural language queries will use default values when specific values aren’t provided.
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options
Sequence[ParamInputType | None] | None
default:"None"
Allowed values for this parameter. If provided, only these values will be accepted during query execution.

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Static Methods

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init_default()

Create a parameter with only a default value specified. 
@staticmethod
init_default(default: ParamInputType | None = None) -> Param
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default
ParamInputType | None
default:"None"
The default value for the parameter.
Returns: Param - A new parameter instance with the specified default value.

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Attributes

The Param class stores the following attributes:
  • name (str): The unique name of the parameter
  • description (str | None): Optional description for natural language query support
  • default (ParamInputType | None): Default value if not overridden
  • options (Sequence[ParamInputType | None] | None): Constrained list of allowed values

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Parameter Usage

Parameters serve as placeholders in query definitions and are resolved with actual values during query execution. They enable:
  • Dynamic Queries: Create reusable query templates
  • Runtime Flexibility: Change search criteria without rebuilding queries
  • Natural Language Integration: Support AI-powered query parameter filling
  • Validation: Constrain parameter values to specific options
  • Default Handling: Provide fallback values for optional parameters

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Value Types

Parameters can accept various input types depending on the context:
  • Strings: For text search terms, field names, categories
  • Numbers: For weights, limits, numerical filters
  • Booleans: For binary flags and switches
  • Lists: For multi-value parameters like categories or tags
  • Complex Types: Schema-specific types for advanced use cases

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Best Practices

Descriptive Names: Use clear, descriptive parameter names that indicate their purpose and expected value type.
Default Values: Provide sensible defaults for optional parameters to ensure queries work even when some parameters aren’t specified.
Option Validation: When using the options parameter, ensure all possible values are included to prevent runtime validation errors.
Natural Language: Parameter descriptions are particularly important for natural language query processing, as they help the AI understand parameter intent.