import difflib import json import os import shutil import subprocess import sys import fire import openai from dotenv import load_dotenv from termcolor import cprint # Set up the OpenAI API load_dotenv() openai.api_key = os.getenv("OPENAI_API_KEY") DEFAULT_MODEL = os.environ.get("DEFAULT_MODEL", "gpt-4") with open("prompt.txt", encoding="utf-8") as file: SYSTEM_PROMPT = file.read() def run_script(script_name, script_args): """ If script_name.endswith(".py") then run with python else run with node """ script_args = [str(arg) for arg in script_args] subprocess_args = ( [sys.executable, script_name, *script_args] if script_name.endswith(".py") else ["node", script_name, *script_args] ) try: result = subprocess.check_output( subprocess_args, stderr=subprocess.STDOUT ) except subprocess.CalledProcessError as error: return error.output.decode("utf-8"), error.returncode return result.decode("utf-8"), 0 def json_validated_response(model, messages): """ This function is needed because the API can return a non-json response. This will run recursively until a valid json response is returned. todo: might want to stop after a certain number of retries """ response = openai.ChatCompletion.create( model=model, messages=messages, temperature=0.5, ) messages.append(response.choices[0].message) content = response.choices[0].message.content # see if json can be parsed try: json_start_index = content.index( "[" ) # find the starting position of the JSON data json_data = content[ json_start_index: ] # extract the JSON data from the response string json_response = json.loads(json_data) except (json.decoder.JSONDecodeError, ValueError) as error: cprint(f"{error}. Re-running the query.", "red") # debug cprint(f"\nGPT RESPONSE:\n\n{content}\n\n", "yellow") # append a user message that says the json is invalid messages.append( { "role": "user", "content": """Your response could not be parsed by json.loads. Please restate your last message as pure JSON.""", } ) # rerun the api call return json_validated_response(model, messages) except Exception as error: cprint(f"Unknown error: {error}", "red") cprint(f"\nGPT RESPONSE:\n\n{content}\n\n", "yellow") raise error return json_response def send_error_to_gpt(file_path, args, error_message, model=DEFAULT_MODEL): with open(file_path) as f: file_lines = f.readlines() file_with_lines = [] for i, line in enumerate(file_lines): file_with_lines.append(str(i + 1) + ": " + line) file_with_lines = "".join(file_with_lines) prompt = ( "Here is the script that needs fixing:\n\n" f"{file_with_lines}\n\n" "Here are the arguments it was provided:\n\n" f"{args}\n\n" "Here is the error message:\n\n" f"{error_message}\n" "Please provide your suggested changes, and remember to stick to the " "exact format as described above." ) # print(prompt) messages = [ { "role": "system", "content": SYSTEM_PROMPT, }, { "role": "user", "content": prompt, }, ] return json_validated_response(model, messages) def apply_changes(file_path, changes: list, confirm=False): """ Pass changes as loaded json (list of dicts) """ with open(file_path) as f: original_file_lines = f.readlines() # Filter out explanation elements operation_changes = [change for change in changes if "operation" in change] explanations = [ change["explanation"] for change in changes if "explanation" in change ] # Sort the changes in reverse line order operation_changes.sort(key=lambda x: x["line"], reverse=True) file_lines = original_file_lines.copy() for change in operation_changes: operation = change["operation"] line = change["line"] content = change["content"] if operation == "Replace": file_lines[line - 1] = content + "\n" elif operation == "Delete": del file_lines[line - 1] elif operation == "InsertAfter": file_lines.insert(line, content + "\n") # Ask for user confirmation before writing changes print("\nChanges to be made:") diff = difflib.unified_diff(original_file_lines, file_lines, lineterm="") for line in diff: if line.startswith("+"): cprint(line, "green", end="") elif line.startswith("-"): cprint(line, "red", end="") else: print(line, end="") # Checking if user used confirm flag if confirm: confirmation = input("Do you want to apply these changes? (y/n): ") if confirmation.lower() != "y": print("Changes not applied") sys.exit(0) with open(file_path, "w") as f: f.writelines(file_lines) # Print explanations cprint("Explanations:", "blue") for explanation in explanations: cprint(f"- {explanation}", "blue") # Show the diff print("\nChanges:") diff = difflib.unified_diff( original_file_lines, file_lines, lineterm="") for line in diff: if line.startswith("+"): cprint(line, "green", end="") elif line.startswith("-"): cprint(line, "red", end="") else: print(line, end="") print("Changes applied.") def main(script_name, *script_args, revert=False, model=DEFAULT_MODEL, confirm=False): if revert: backup_file = script_name + ".bak" if os.path.exists(backup_file): shutil.copy(backup_file, script_name) print(f"Reverted changes to {script_name}") sys.exit(0) else: print(f"No backup file found for {script_name}") sys.exit(1) # Make a backup of the original script shutil.copy(script_name, script_name + ".bak") while True: output, returncode = run_script(script_name, script_args) if returncode == 0: cprint("Script ran successfully.", "blue") print("Output:", output) break else: cprint("Script crashed. Trying to fix...", "blue") print("Output:", output) json_response = send_error_to_gpt( file_path=script_name, args=script_args, error_message=output, model=model, ) apply_changes(script_name, json_response, confirm=confirm) cprint("Changes applied. Rerunning...", "blue") if __name__ == "__main__": fire.Fire(main)