G.O.D. Framework

Introduction

The ai_configuration_loader.py script provides dynamic configuration management for the G.O.D. Framework. It simplifies the process of loading, validating, and managing configurations for various AI modules. This script uses structured formats like JSON or YAML to ensure flexibility and consistency across components.

Purpose

• Centralized Configuration: Streamlines configuration management for modular systems.
• Validation: Ensures configurations are complete, correct, and adhere to the required schema.
• Dynamic Updates: Supports runtime updates to configurations for adaptive systems.
• Interoperability: Facilitates integration with external libraries or APIs using configurable templates.

Key Features

• Multi-format Support: Handles configurations in JSON, YAML, or environment variables.
• Schema Validation: Validates configurations using tools like jsonschema.
• Error Resilience: Provides detailed error reporting for configuration issues.
• Secure Access: Protects sensitive configuration elements (e.g., credentials) using encryption.

Logic and Implementation

The script uses the following approach:

1. Reads configuration files in JSON or YAML format.
2. Validates configurations using a predefined schema.
3. Enables runtime updates via signals or API hooks.

            import json
            import yaml
            from jsonschema import validate, ValidationError

            def load_config(file_path):
                """
                Loads and validates a configuration file.
                :param file_path: Path to the JSON or YAML configuration.
                :return: Parsed configuration dictionary.
                """
                with open(file_path, 'r') as file:
                    if file_path.endswith(".yaml") or file_path.endswith(".yml"):
                        config = yaml.safe_load(file)
                    elif file_path.endswith(".json"):
                        config = json.load(file)
                    else:
                        raise ValueError("Unsupported file format. Use JSON or YAML.")
                return config

            def validate_config(config, schema):
                """
                Validates configuration against a schema.
                :param config: Configuration dictionary.
                :param schema: Schema dictionary.
                :return: None (raises ValidationError if invalid).
                """
                try:
                    validate(instance=config, schema=schema)
                except ValidationError as e:
                    raise ValueError(f"Configuration validation failed: {e.message}")

            if __name__ == "__main__":
                # Example schema
                schema = {
                    "type": "object",
                    "properties": {
                        "database": {"type": "string"},
                        "retries": {"type": "integer"},
                        "use_cache": {"type": "boolean"}
                    },
                    "required": ["database", "retries", "use_cache"]
                }

                # Load and validate example configuration
                config_file = "config.json"
                config = load_config(config_file)
                validate_config(config, schema)
                print("Configuration loaded and validated successfully.")
            

Dependencies

• jsonschema: For validating JSON configurations against schemas.
• yaml: Parses YAML configuration files.

How to Use This Script

1. Create a JSON or YAML configuration file with required settings.
2. Define a schema to validate the configuration’s structure.
3. Load the configuration using load_config().
4. Validate it using the validate_config() function to ensure correctness.

            # Example runtime usage
            config = load_config("settings.yaml")
            validate_config(config, schema)

            # Access configurations dynamically
            database_url = config.get("database")
            retries = config.get("retries")