plan.md

Implementation Guide: Single Function with Comprehensive Argument Types

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Table of Contents

1. Introduction
2. Function Overview
3. OpenAI Tool JSON Definition
4. Function Implementation
5. Testing and Error Handling
6. Conclusion

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Introduction

This guide provides a detailed walkthrough for implementing a single function that utilizes a variety of argument types as defined in the OpenAI Tool JSON schema. The function will demonstrate handling of different data types including strings, integers, booleans, arrays, and objects.

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Function Overview

• Function Name: comprehensive_function
• Description: Demonstrates the use of various argument types in a single function.

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OpenAI Tool JSON Definition

{
  "name": "comprehensive_function",
  "description": "Demonstrates the use of various argument types in a single function.",
  "parameters": {
    "type": "object",
    "properties": {
      "string_arg": {
        "type": "string",
        "description": "A simple string argument."
      },
      "integer_arg": {
        "type": "integer",
        "description": "An integer argument."
      },
      "boolean_arg": {
        "type": "boolean",
        "description": "A boolean argument."
      },
      "array_arg": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "An array of strings."
      },
      "object_arg": {
        "type": "object",
        "properties": {
          "nested_string": {
            "type": "string",
            "description": "A nested string within an object."
          },
          "nested_integer": {
            "type": "integer",
            "description": "A nested integer within an object."
          }
        },
        "required": ["nested_string", "nested_integer"],
        "description": "An object containing nested properties."
      }
    },
    "required": ["string_arg", "integer_arg", "boolean_arg", "array_arg", "object_arg"]
  }
}

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Function Implementation

def comprehensive_function(string_arg, integer_arg, boolean_arg, array_arg, object_arg):
    # Process string argument
    print(f"String Argument: {string_arg}")

    # Process integer argument
    print(f"Integer Argument: {integer_arg}")

    # Process boolean argument
    print(f"Boolean Argument: {boolean_arg}")

    # Process array argument
    print("Array Argument:")
    for item in array_arg:
        print(f" - {item}")

    # Process object argument
    print("Object Argument:")
    print(f"Nested String: {object_arg['nested_string']}")
    print(f"Nested Integer: {object_arg['nested_integer']}")

    # Return a summary
    return {
        "response": "Function executed successfully with all argument types."
    }

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Testing and Error Handling

Testing

• Unit Tests: Create tests for each argument type to ensure correct handling.
• Integration Tests: Test the function in a simulated environment to verify end-to-end functionality.

Error Handling

• Type Validation: Ensure each argument is of the expected type.
• Missing Arguments: Handle cases where required arguments are not provided.
• Invalid Data: Provide meaningful error messages for invalid data inputs.

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Conclusion

This guide demonstrates the implementation of a function that handles a comprehensive set of argument types as defined in the OpenAI Tool JSON schema. By following this guide, developers can ensure robust handling of diverse data types in their applications.

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