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Parameter System Overview

The no_llm parameter system provides a robust way to configure, validate, and manage model parameters across different LLM providers.

Core Components

Parameter Types

  • Variable: Modifiable values with validation rules
  • Fixed: Immutable values
  • Unsupported: Parameters not supported by the model

Learn more about parameter variants Learn more about parameter classes

Validation

  • Range constraints
  • Enum values
  • Capability requirements
  • Fixed value protection

Learn more about validation

Quick Example

from no_llm.config.model import ModelConfiguration
from no_llm.config.enums import ModelCapability

# Configure model parameters
model = ModelConfiguration(
    parameters=ConfigurableModelParameters(
        temperature=0.7,           # Variable parameter
        top_p={'fixed': 0.9},     # Fixed parameter
        include_reasoning=True     # Capability-dependent parameter
    )
)

# Validate and get runtime parameters
params = model.parameters.validate_parameters(
    capabilities={ModelCapability.REASONING},
    temperature=0.8  # Will be validated
)

Best Practices

  • Use ConfigurableModelParameters for model definitions
  • Use ModelParameters for runtime parameter passing
  • Always validate parameters against model capabilities

See the specific documentation sections for detailed information about each aspect of the parameter system.