input: Write a function to create an AI-powered Python script that optimizes any given code. The function should accept an example code snippet as input and output the optimized version of the provided code. If no optimization is possible, the function should return the original code. The function should also include a main block that initializes parameters, optimizes the function, and prints the optimized result.
  assert optimize_code("function getResult(a, b, c) { return a + b + c; }")=='''# Import the required libraries
  from dataclasses import dataclass
  
  @dataclass
  class Params:
   a: int
   b: int
   c: int
  
  def get_result(params: Params) -> int:
   """Returns the sum of the three given numbers"""
   return params.a + params.b + params.c
  
  # Optimize the code
  def optimize(fn, params):
   best_score = 0
   best_params = None
   for a in range(params.a - 10, params.a + 10):
   for b in range(params.b - 10, params.b + 10):
   for c in range(params.c - 10, params.c + 10):
   score = fn(Params(a, b , c))
   if score > best_score:
   best_score = score
   best_params = {
   'a': a,
   'b': b,
   'c': c
   }
   return best_params
  
  if __name__ == '__main__':
   # Initialize the parameters
   params = Params(a=1, b=2, c=3)
   # Get the optimized params
   best_params = optimize(get_result, params)
   # Print the optimized result
   print("Optimized result: %d" % get_result(Params(best_params['a'], best_params['b'], best_params['c'])))'''
  assert optimize_code("function add(a, b) { return a + b; }")=='function add(a, b) { return a + b; }'
  assert optimize_code("")==''
  assert optimize_code("def double(x): return x * 2")=='''def double(x):
   return x * 2'''
  assert optimize_code("def triple(x): return x * 3")=='''def triple(x):
   return x * 3'''
output: def optimize_code(code):
      return code