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# Acknowledgement: Modified from AFlow (https://github.com/geekan/MetaGPT/blob/main/metagpt/ext/aflow/scripts/optimizer_utils/graph_utils.py) under MIT License
import os
import re
import time
import traceback
from typing import List
from pathlib import Path
from ...core.logging import logger
from ...prompts.optimizers.aflow_optimizer import (
WORKFLOW_INPUT,
WORKFLOW_OPTIMIZE_PROMPT,
WORKFLOW_CUSTOM_USE,
WORKFLOW_TEMPLATE
)
from ...models.base_model import BaseLLM
from ...workflow.operators import (
Operator, Custom, CustomCodeGenerate,
ScEnsemble, Test, AnswerGenerate, QAScEnsemble, Programmer
)
OPERATOR_MAP = {
"Custom": Custom,
"CustomCodeGenerate": CustomCodeGenerate,
"ScEnsemble": ScEnsemble,
"Test": Test,
"AnswerGenerate": AnswerGenerate,
"QAScEnsemble": QAScEnsemble,
"Programmer": Programmer
}
class GraphUtils:
def __init__(self, root_path: str):
self.root_path = root_path
def create_round_directory(self, graph_path: str, round_number: int) -> str:
directory = os.path.join(graph_path, f"round_{round_number}")
os.makedirs(directory, exist_ok=True)
return directory
def load_graph(self, round_number: int, workflows_path: str):
workflows_path = workflows_path.replace("\\", ".").replace("/", ".")
graph_module_name = f"{workflows_path}.round_{round_number}.graph"
try:
graph_module = __import__(graph_module_name, fromlist=[""])
graph_class = getattr(graph_module, "Workflow")
return graph_class
except ImportError as e:
logger.info(f"Error loading graph for round {round_number}: {e}")
raise
def read_graph_files(self, round_number: int, workflows_path: str):
prompt_file_path = os.path.join(workflows_path, f"round_{round_number}", "prompt.py")
graph_file_path = os.path.join(workflows_path, f"round_{round_number}", "graph.py")
try:
with open(prompt_file_path, "r", encoding="utf-8") as file:
prompt_content = file.read()
with open(graph_file_path, "r", encoding="utf-8") as file:
graph_content = file.read()
except FileNotFoundError as e:
logger.info(f"Error: File not found for round {round_number}: {e}")
raise
except Exception as e:
logger.info(f"Error loading prompt for round {round_number}: {e}")
raise
return prompt_content, graph_content
def extract_solve_graph(self, graph_load: str) -> List[str]:
pattern = r"class Workflow:.+"
return re.findall(pattern, graph_load, re.DOTALL)
def load_operators_description(self, operators: List[str], llm: BaseLLM) -> str:
operators_description = ""
for id, operator in enumerate(operators):
operator_description = self._load_operator_description(id + 1, operator, llm)
operators_description += f"{operator_description}\n"
return operators_description
def _load_operator_description(self, id: int, operator_name: str, llm: BaseLLM) -> str:
if operator_name not in OPERATOR_MAP:
raise ValueError(f"Operator {operator_name} not Found in OPERATOR_MAP! Available operators: {OPERATOR_MAP.keys()}")
operator: Operator = OPERATOR_MAP[operator_name](llm=llm)
return f"{id}. {operator_name}: {operator.description}, with interface {operator.interface})."
def create_graph_optimize_prompt(
self,
experience: str,
score: float,
graph: str,
prompt: str,
operator_description: str,
type: str,
log_data: str,
) -> str:
graph_input = WORKFLOW_INPUT.format(
experience=experience,
score=score,
graph=graph,
prompt=prompt,
operator_description=operator_description,
type=type,
log=log_data,
)
graph_system = WORKFLOW_OPTIMIZE_PROMPT.format(type=type)
return graph_input + WORKFLOW_CUSTOM_USE + graph_system
def get_graph_optimize_response(self, graph_optimize_node):
max_retries = 5
retries = 0
while retries < max_retries:
try:
response = graph_optimize_node.instruct_content.model_dump()
return response
except Exception as e:
retries += 1
logger.info(f"Error generating prediction: {e}. Retrying... ({retries}/{max_retries})")
if retries == max_retries:
logger.info("Maximum retries reached. Skipping this sample.")
break
traceback.print_exc()
time.sleep(5)
return None
def write_graph_files(self, directory: str, response: dict):
graph = WORKFLOW_TEMPLATE.format(graph=response["graph"])
with open(os.path.join(directory, "graph.py"), "w", encoding="utf-8") as file:
file.write(graph)
with open(os.path.join(directory, "prompt.py"), "w", encoding="utf-8") as file:
prompt = response["prompt"].replace("prompt_custom.", "")
file.write(prompt)
with open(os.path.join(directory, "__init__.py"), "w", encoding="utf-8") as file:
file.write("")
self.update_prompt_import(os.path.join(directory, "graph.py"), directory)
def update_prompt_import(self, graph_file: str, prompt_folder: str):
project_root = Path(os.getcwd())
prompt_folder_path = Path(prompt_folder)
if not prompt_folder_path.is_absolute():
prompt_folder_full_path = Path(os.path.join(project_root, prompt_folder))
if not prompt_folder_full_path.exists():
raise ValueError(f"Prompt folder {prompt_folder_full_path} does not exist!")
prompt_folder_path = prompt_folder_full_path
try:
relative_path = prompt_folder_path.relative_to(project_root)
except ValueError:
raise ValueError(f"Prompt folder {prompt_folder} must be within the project directory")
import_path = str(relative_path).replace(os.sep, ".")
if import_path.startswith("."):
import_path = import_path[1:]
with open(graph_file, "r", encoding="utf-8") as file:
graph_content = file.read()
# 在graph_content中找到import语句
pattern = r'import .*?\.prompt as prompt_custom'
replacement = f'import {import_path}.prompt as prompt_custom'
new_content = re.sub(pattern, replacement, graph_content)
with open(graph_file, "w", encoding="utf-8") as file:
file.write(new_content)
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