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