Function aggregate_functions

integuru/util/print.py:268–314

(txt_path, output_path)

    return code

def aggregate_functions(txt_path, output_path):
    # Read the content of the file
    with open(txt_path, 'r') as file:
        content = file.read()

    # Initialize ChatGPT

    # Prepare the prompt for ChatGPT
    prompt = f"""
    The following text contains multiple Python functions:

    {content}

    Please generate Python code that does the following:    
    1. Fix up the functions if needed in the order they appear in the text.
    2. Leave everything that is hardcoded as is.
    3. Call each function in the order they appear in the text.
    4. The cookies will be hard coded in the file in a string format of key=value;key=value. You will need to convert them to a dict to retrieve values from them.
    5. Pass the return value of each function as an argument to the next function, if applicable.
    6. Ensure that the last function in the text is called last.
    7. Output the entire directly runnable code



    Only provide the Python code, without any explanations or markdown formatting.
    DO NOT include any backticks or markdown syntax AT ALL
    """

    # Get the response from ChatGPT

    llm_model = llm.switch_to_alternate_model()
    try:
        response = llm_model.invoke(prompt)
    except Exception as e:
        print("Switching to default model")
        llm.revert_to_default_model()
        response = llm.switch_to_alternate_model().invoke(prompt)
    # Extract the generated code
    generated_code = response.content.strip()

    # Save the generated code to the specified output file
    with open(output_path, 'w') as file:
        file.write(generated_code)

    print(f"Aggregated function calls have been saved to '{output_path}'")

    return output_path

def generate_obfuscation_map(dynamic_parts_list: List[str]) -> Dict[str, str]:
    obfuscation_map = {}