Spaces:
Sleeping
Sleeping
| import inspect | |
| import os | |
| import re | |
| import threading | |
| from dotenv import load_dotenv | |
| from swarms_memory import DictInternalMemory, DictSharedMemory | |
| from scripts.auto_tests_docs.docs import TEST_WRITER_SOP_PROMPT | |
| from swarm_models import OpenAIChat | |
| load_dotenv() | |
| api_key = os.getenv("OPENAI_API_KEY") | |
| model = OpenAIChat( | |
| openai_api_key=api_key, | |
| max_tokens=4000, | |
| ) | |
| # agent = Agent( | |
| # llm=model, | |
| # agent_name="Unit Testing Agent", | |
| # agent_description=( | |
| # "This agent is responsible for generating unit tests for" | |
| # " the swarms package." | |
| # ), | |
| # autosave=True, | |
| # system_prompt=None, | |
| # max_loops=1, | |
| # ) | |
| def extract_code_from_markdown(markdown_content: str): | |
| """ | |
| Extracts code blocks from a Markdown string and returns them as a single string. | |
| Args: | |
| - markdown_content (str): The Markdown content as a string. | |
| Returns: | |
| - str: A single string containing all the code blocks separated by newlines. | |
| """ | |
| # Regular expression for fenced code blocks | |
| pattern = r"```(?:\w+\n)?(.*?)```" | |
| matches = re.findall(pattern, markdown_content, re.DOTALL) | |
| # Concatenate all code blocks separated by newlines | |
| return "\n".join(code.strip() for code in matches) | |
| def create_test(cls): | |
| """ | |
| Process the documentation for a given class using OpenAI model and save it in a Python file. | |
| """ | |
| doc = inspect.getdoc(cls) | |
| source = inspect.getsource(cls) | |
| input_content = ( | |
| "Class Name:" | |
| f" {cls.__name__}\n\nDocumentation:\n{doc}\n\nSource" | |
| f" Code:\n{source}" | |
| ) | |
| # Process with OpenAI model (assuming the model's __call__ method takes this input and returns processed content) | |
| processed_content = model( | |
| TEST_WRITER_SOP_PROMPT( | |
| input_content, "swarms", "swarms.memory" | |
| ) | |
| ) | |
| processed_content = extract_code_from_markdown(processed_content) | |
| doc_content = f"# {cls.__name__}\n\n{processed_content}\n" | |
| # Create the directory if it doesn't exist | |
| dir_path = "tests/memory" | |
| os.makedirs(dir_path, exist_ok=True) | |
| # Write the processed documentation to a Python file | |
| file_path = os.path.join(dir_path, f"{cls.__name__.lower()}.py") | |
| with open(file_path, "w") as file: | |
| file.write(doc_content) | |
| def main(): | |
| classes = [ | |
| DictInternalMemory, | |
| DictSharedMemory, | |
| ] | |
| threads = [] | |
| for cls in classes: | |
| thread = threading.Thread(target=create_test, args=(cls,)) | |
| threads.append(thread) | |
| thread.start() | |
| # Wait for all threads to complete | |
| for thread in threads: | |
| thread.join() | |
| print("Tests generated in 'tests/memory' directory.") | |
| if __name__ == "__main__": | |
| main() | |