|
|
| import os |
|
|
| class SelfCodingAI: |
| def __init__(self, name="SelfCoder", code_folder="generated_code"): |
| self.name = name |
| self.code_folder = code_folder |
| os.makedirs(self.code_folder, exist_ok=True) |
|
|
| def generate_code(self, task_description): |
| """ |
| Very basic code generation logic: generates code for some predefined tasks. |
| You can extend this to integrate GPT-like models or complex code synthesis. |
| """ |
| if "hello world" in task_description.lower(): |
| code = 'print("Hello, world!")' |
| elif "factorial" in task_description.lower(): |
| code = ( |
| "def factorial(n):\n" |
| " return 1 if n==0 else n * factorial(n-1)\n\n" |
| "print(factorial(5))" |
| ) |
| else: |
| code = "# Code generation for this task is not implemented yet.\n" |
|
|
| return code |
|
|
| def save_code(self, code, filename="generated_code.py"): |
| filepath = os.path.join(self.code_folder, filename) |
| with open(filepath, "w", encoding="utf-8") as f: |
| f.write(code) |
| print(f"Code saved to {filepath}") |
| return filepath |
|
|
| def self_improve(self, feedback): |
| """ |
| Placeholder for self-improvement method. |
| In future, AI could modify its own code based on feedback or test results. |
| """ |
| print(f"{self.name} received feedback: {feedback}") |
| print("Self-improvement not yet implemented.") |
|
|
| def run_code(self, filepath): |
| print(f"Running code from {filepath}:\n") |
| try: |
| with open(filepath, "r", encoding="utf-8") as f: |
| code = f.read() |
| exec(code, {}) |
| except Exception as e: |
| print(f"Error during code execution: {e}") |
|
|
| |
| ai = SelfCodingAI() |
|
|
| task = "Write a factorial function in Python" |
| generated = ai.generate_code(task) |
|
|
| file_path = ai.save_code(generated, "factorial.py") |
| ai.run_code(file_path) |
|
|
| |
| ai.self_improve("The factorial function passed all test cases.") |
