Description

During the testing phase of our groundbreaking Python program aimed at transforming the AI industry in agentic workflows, we encountered several critical errors. The project, a collaboration between our team's agentic workflow developers, AI software engineers, and a DevOps engineer, aims to set new standards in the field. However, the execution of our test suite failed to run due to a ModuleNotFoundError, and further optimization efforts led to an attribute error in the 'enchant' module. Additionally, Git-related errors suggest issues with repository detection.

Steps to Reproduce

Initiating the test suite for our Python program.
Encountering a ModuleNotFoundError for the 'add' module upon execution.
Observing an attribute error during optimization efforts and Git repository errors.

Expected Behavior

Successful execution of the test suite without import errors.
Correct recognition and utilization of the 'enchant' module's attributes during optimization.
Proper detection and interaction with the Git repository, if applicable.

Actual Behavior

No tests were executed due to a ModuleNotFoundError.
An optimization error regarding the 'enchant' module attribute was observed.
Git commands indicated the current directory is not recognized as a git repository.

Error Messages and Performance Data

ModuleNotFoundError: No module named 'add' Error during optimization: module 'enchant' has no attribute 'Broker' fatal: not a git repository (or any of the parent directories): .git

Performance data and function call statistics were generated, indicating the program's execution path and time spent on various calls.

Environment

Operating System: Windows 11
Python Version: Python 3.11
Collaboration Context: The issue was encountered during the testing phase of our agentic workflow project, involving roles and tasks distributed among team members focused on AI software engineering, agentic workflow development, and DevOps.

Additional Context

The program in question is part of a larger effort to innovate within the AI industry, emphasizing the creation of efficient, robust, and transformative agentic workflows. Our team, consisting of senior agentic workflow developers, AI software engineers, and a DevOps engineer, collaborates closely to address these technical challenges.

Given the complexity of our project and the specialized roles involved, resolving these errors is crucial for progressing towards our goal of setting new industry standards. Any insights or suggestions on addressing the import error, the optimization issue, and the Git repository detection problem would be highly appreciated.

Attached Files and Documentation

Program files and error logs have been included as attachments to this issue for further examination. import os import subprocess import tempfile import logging import cProfile import pstats import io import ast import astroid import pylint.lint import traceback class CodeExecutionManager: def init(self): self.logger = logging.getLogger(name) self.workspace_folder = "workspace" os.makedirs(self.workspace_folder, exist_ok=True)

def save_file(self, filepath, content): filepath = os.path.join(self.workspace_folder, filepath) try: with open(filepath, 'w', encoding='utf-8') as file: file.write(content) self.logger.info(f"File '{filepath}' saved successfully.") return True except Exception as e: self.logger.error(f"Error saving file '{filepath}': {str(e)}") return False

def read_file(self, filepath): filepath = os.path.join(self.workspace_folder, filepath) try: with open(filepath, 'r', encoding='utf-8') as file: content = file.read() self.logger.info(f"File '{filepath}' read successfully.") return content except FileNotFoundError: self.logger.error(f"File '{filepath}' not found.") return None except Exception as e: self.logger.error(f"Error reading file '{filepath}': {str(e)}") return None

def test_code(self, code): if not code: return None, None
```
with tempfile.TemporaryDirectory(dir=self.workspace_folder) as temp_dir:
    script_path = os.path.join(temp_dir, 'temp_script.py')
    with open(script_path, 'w') as f:
        f.write(code)

    try:
        output = subprocess.check_output(['python', '-m', 'unittest', 'discover', temp_dir], universal_newlines=True, stderr=subprocess.STDOUT, timeout=30)
        self.logger.info("Tests execution successful.")
        return output, None
    except subprocess.CalledProcessError as e:
        self.logger.error(f"Tests execution error: {e.output}")
        return None, e.output
    except subprocess.TimeoutExpired:
        self.logger.error("Tests execution timed out after 30 seconds.")
        return None, "Execution timed out after 30 seconds"
    except Exception as e:
        self.logger.error(f"Tests execution error: {str(e)}")
        return None, str(e)
```
def execute_command(self, command): try: result = subprocess.run(command, capture_output=True, text=True, shell=True) self.logger.info(f"Command executed: {command}") return result.stdout, result.stderr except Exception as e: self.logger.error(f"Error executing command: {str(e)}") return None, str(e)

def format_error_message(error): return f"Error: {str(error)}\nTraceback: {traceback.format_exc()}"

def run_tests(code): code_execution_manager = CodeExecutionManager() test_code_output, test_code_error = code_execution_manager.test_code(code) if test_code_output: print(f"\n[TEST CODE OUTPUT]\n{test_code_output}") if test_code_error: print(f"\n[TEST CODE ERROR]\n{test_code_error}")

def monitor_performance(code): with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False, dir="workspace") as temp_file: temp_file.write(code) temp_file_path = temp_file.name

profiler = cProfile.Profile()
profiler.enable()

try:
    subprocess.run(['python', temp_file_path], check=True)
except subprocess.CalledProcessError as e:
    print(f"Error executing code: {e}")
finally:
    profiler.disable()
    os.unlink(temp_file_path)

stream = io.StringIO()
stats = pstats.Stats(profiler, stream=stream).sort_stats('cumulative')
stats.print_stats()

performance_data = stream.getvalue()
print(f"\n[PERFORMANCE DATA]\n{performance_data}")

return performance_data

def optimize_code(code): try:

Save the code to a temporary file

    with tempfile.NamedTemporaryFile(delete=False, suffix=".py") as tmp:
        tmp.write(code.encode('utf-8'))
        tmp_file_path = tmp.name

    # Setup Pylint to use the temporary file
    pylint_output = io.StringIO()

    # Define a custom reporter class based on BaseReporter
    class CustomReporter(pylint.reporters.BaseReporter):
        def _display(self, layout):
            pylint_output.write(str(layout))

    pylint_args = [tmp_file_path]
    pylint_reporter = pylint.lint.Run(pylint_args, reporter=CustomReporter())

    # Retrieve optimization suggestions
    optimization_suggestions = pylint_output.getvalue()
    print(f"\n[OPTIMIZATION SUGGESTIONS]\n{optimization_suggestions}")

    # Cleanup temporary file
    os.remove(tmp_file_path)

    return optimization_suggestions
except SyntaxError as e:
    print(f"SyntaxError: {e}")
    return None
except Exception as e:
    print(f"Error during optimization: {str(e)}")
    return None

def pass_code_to_alex(code, alex_memory): alex_memory.append({"role": "system", "content": f"Code from Mike and Annie: {code}"})

def send_status_update(mike_memory, annie_memory, alex_memory, project_status): mike_memory.append({"role": "system", "content": f"Project Status Update: {project_status}"}) annie_memory.append({"role": "system", "content": f"Project Status Update: {project_status}"}) alex_memory.append({"role": "system", "content": f"Project Status Update: {project_status}"})

def generate_documentation(code): try: module = ast.parse(code) docstrings = []

    for node in ast.walk(module):
        if isinstance(node, (ast.FunctionDef, ast.ClassDef, ast.Module)):
            docstring = ast.get_docstring(node)
            if docstring:
                docstrings.append(f"{node.name}:\n{docstring}")

    documentation = "\n".join(docstrings)
    print(f"\n[GENERATED DOCUMENTATION]\n{documentation}")

    return documentation
except SyntaxError as e:
    print(f"SyntaxError: {e}")
    return None

def commit_changes(code): subprocess.run(["git", "add", "workspace"]) subprocess.run(["git", "commit", "-m", "Automated code commit"])

Drlordbasil / GroqAgenticWorkflow

Import and Optimization Errors in Agentic Workflow Development Project #4