Source code for autorag.node_line

import os
import pathlib
from typing import Dict, List, Optional

import pandas as pd

from autorag.schema import Node
from autorag.utils.util import load_summary_file


[docs] def make_node_lines(node_line_dict: Dict) -> List[Node]: """ This method makes a list of nodes from node line dictionary. :param node_line_dict: Node_line_dict loaded from yaml file, or get from user input. :return: List of Nodes inside this node line. """ nodes = node_line_dict.get("nodes") if nodes is None: raise ValueError("Node line must have 'nodes' key.") node_objects = list(map(lambda x: Node.from_dict(x), nodes)) return node_objects
[docs] def run_node_line( nodes: List[Node], node_line_dir: str, previous_result: Optional[pd.DataFrame] = None, ): """ Run the whole node line by running each node. :param nodes: A list of nodes. :param node_line_dir: This node line's directory. :param previous_result: A result of the previous node line. If None, it loads qa data from data/qa.parquet. :return: The final result of the node line. """ if previous_result is None: project_dir = pathlib.PurePath(node_line_dir).parent.parent qa_path = os.path.join(project_dir, "data", "qa.parquet") if not os.path.exists(qa_path): raise ValueError(f"qa.parquet does not exist in {qa_path}.") previous_result = pd.read_parquet(qa_path, engine="pyarrow") summary_lst = [] for node in nodes: previous_result = node.run(previous_result, node_line_dir) node_summary_df = load_summary_file( os.path.join(node_line_dir, node.node_type, "summary.csv") ) best_node_row = node_summary_df.loc[node_summary_df["is_best"]] summary_lst.append( { "node_type": node.node_type, "best_module_filename": best_node_row["filename"].values[0], "best_module_name": best_node_row["module_name"].values[0], "best_module_params": best_node_row["module_params"].values[0], "best_execution_time": best_node_row["execution_time"].values[0], } ) pd.DataFrame(summary_lst).to_csv( os.path.join(node_line_dir, "summary.csv"), index=False ) return previous_result