""" Copyright (c) 2023, salesforce.com, inc. All rights reserved. SPDX-License-Identifier: Apache License 2.0 For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0 """ #!/usr/bin/env python3 # import sys, os, pdb import json import shutil, errno from tqdm import tqdm import pandas as pd from utils.constant import * class PreProcessData(object): """docstring for PreProcessData""" def __init__(self): super(PreProcessData, self).__init__() self.data_dir = "/path/to/where/the/raw/dataset/is" self.save_dir = "/path/to/store/the/processed/dataset/" # e.g. ./data/processed/Knowledge-Grounded def _load_json(self, path=None): if path is None or not os.path.exists(path): raise IOError('File does not exist: %s' % path) # return None with open(path) as df: data = json.loads(df.read()) return data def _load_txt(self, path=None, split_tok="\n"): if path is None or not os.path.exists(path): raise IOError('File does not exist: %s' % path) with open(path) as df: data = df.read().strip().split(split_tok) return data def _load_csv(self, path=None, sep="\t"): if path is None or not os.path.exists(path): raise IOError('File does not exist: %s' % path) with open(path) as df: data = pd.read_csv(df, sep=sep) return data def _load_jsonl(self, path=None): if path is None or not os.path.exists(path): raise IOError('File does not exist: %s' % path) data = [] with open(path) as df: for line in df.readlines(): data.append(json.loads(line)) return data def _load_dir_json(self, dir_path=None): if dir_path is None or not os.path.exists(dir_path): return None total_data = [] # assume data is a list of dialogs for filename in sorted(os.listdir(dir_path)): if filename in ["schema.json"]: continue if not filename.endswith(".json"): continue file_path = os.path.join(dir_path, filename) data = self._load_json(path=file_path) if type(data) == list: total_data.extend(data) else: total_data.append(data) return total_data def _load_dir_txt(self, dir_path=None, file_type="txt"): if dir_path is None or not os.path.exists(dir_path): return None total_data = [] # assume data is a list of dialogs for filename in sorted(os.listdir(dir_path)): if not filename.endswith(file_type): continue file_path = os.path.join(dir_path, filename) data = self._load_txt(path=file_path) if type(data) == list: total_data.extend(data) else: total_data.append(data) return total_data def _load_dir_tsv(self, dir_path=None, sep="\t"): if dir_path is None or not os.path.exists(dir_path): return None total_data = None for filename in sorted(os.listdir(dir_path)): file_path = os.path.join(dir_path, filename) data = self._load_csv(path=file_path, sep=sep) total_data = pd.concat([total_data, data], ignore_index=True) return total_data def _save_json(self, data, path): with open(path, "w") as tf: json.dump(data, tf, indent=4) def init_dial(self, dial_idx=0, ori_dial_id=""): dial = { ORI_DIAL_ID: "", DIAL_IDX: dial_idx, ORI_DIAL_INFO: {}, LOG: [], # EK_ORI: { # TOD_EK:{}, # }, # EK: "", PROMPT: [], } return dial def init_turn(self, turn_id=0, dial_hist=[]): turn = { TURN_ID: int(turn_id), USR_UTT: "", SYS_UTT: "", DIAL_HIST: " ".join(dial_hist), ORI_USR_ANN: {}, ORI_SYS_ANN: {}, EK_ORI: { TOD_EK:{}, }, EK: "", } return turn def save_dial(self, data, data_name="", file_idx=0, mode="train"): save_name = f"dialogues_{file_idx}.json" folder_path = os.path.join(self.save_dir, data_name, mode) if not os.path.exists(folder_path): os.makedirs(folder_path) path = os.path.join(folder_path, save_name) self._save_json(data, path) def save_original_examples(self, examples, data_name): """ save 5 original data points just for reference and check data would be a list of length 5, each entry is a dialog in the form of dictionary """ path = os.path.join(self.save_dir, data_name, "original_examples.json") self._save_json(examples, path) print("original examples saved") def save_converted_examples(self, data_name): """ extract the first 5 examples from the train set of the already processed data, just for reference and check """ data = self._load_json(os.path.join(self.save_dir, data_name, "train/dialogues_1.json")) examples = {key: data[key] for key in list(data.keys())[:5]} self._save_json(examples, os.path.join(self.save_dir, data_name, "converted_examples.json")) print("converted examples saved") def dict_to_str(self, ek_ori): """ turn non-flat external knowledge into string original format: "metadata":{ domain: [ { attr1: value1, attr2: value2, ... }, ... ] } output format: ( metadata : ( domain : ( attr1 : value1 | attr2 : value2 | ... ) | ( ... ) | ... )) """ ek = str(ek_ori).replace("'"," ").replace(", "," | ") ek = ek.replace("{","(").replace("}",")").replace("[","(").replace("]",")") ek = ek.replace(" ", " ") return ek def wow(self): """ Speakers: Apprentice (always starts a turn), Wizard (ends a turn) turn-level EK only checked facts: """ data_name = "wizard_of_wikipedia" for mode in ["train", "val", "test"]: if mode == "train": filename = "train.json" elif mode == "val": filename = "valid_topic_split.json" else: filename = "test_topic_split.json" data = self._load_json(os.path.join(self.data_dir, data_name, filename)) new_data, file_idx = {}, 1 for dial_idx, dial in tqdm(enumerate(data)): new_dial = self.init_dial(dial_idx=dial_idx+1) new_dial_id = f"{data_name}--{mode}--{dial_idx+1}" new_dial[ORI_DIAL_INFO]["chosen_topic"] = dial["chosen_topic"] new_dial[ORI_DIAL_INFO]["persona"] = dial["persona"] new_dial[ORI_DIAL_INFO]["wizard_eval"] = dial["wizard_eval"] new_dial[ORI_DIAL_INFO]["chosen_topic_passage"] = dial["chosen_topic_passage"] turn_idx, dial_hist = 1, [] new_turn = self.init_turn(turn_id=turn_idx) for turn in (dial["dialog"]): if turn["speaker"].split("_")[-1] == "Apprentice": new_turn = self.init_turn(turn_id=turn_idx) new_turn[DIAL_HIST] = " ".join(dial_hist) for key_ in turn: if key_ == "text": new_turn[USR_UTT] = turn["text"] else: new_turn[ORI_USR_ANN][key_] = turn[key_] dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT]) elif turn["speaker"].split("_")[-1] == "Wizard": for key_ in turn: if key_ == "text": new_turn[SYS_UTT] = turn["text"] else: new_turn[ORI_SYS_ANN][key_] = turn[key_] dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT]) if not turn["checked_passage"]: turn["checked_passage"] = {"none": dial["chosen_topic"]} if not turn["checked_sentence"]: turn["checked_sentence"] = {"no_passages_used": "no_passages_used"} if len(turn["checked_passage"]) == 2 and "no_passages_used" in turn["checked_passage"]: # for case turn["checked_passage"] = {'chosen_topic_0_Aquarium': 'Aquarium', 'no_passages_used': 'no_passages_used'} del turn["checked_passage"]["no_passages_used"] # if len(turn["checked_passage"].values()) != 1 or len(turn["checked_sentence"].values()) != 1: pdb.set_trace() title = list(turn["checked_passage"].values())[0] sent = list(turn["checked_sentence"].values())[0] new_turn[EK_ORI][TOD_EK][title] = sent new_turn[EK] = self.dict_to_str(new_turn[EK_ORI][TOD_EK]) new_dial[LOG].append(new_turn) turn_idx += 1 else: print(turn["speaker"]) raise ValueError("Unknown speaker") if not new_turn[SYS_UTT]: new_dial[LOG].append(new_turn) new_data[new_dial_id] = new_dial if new_dial[DIAL_IDX] % 10000 == 0: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode) new_data = {} # reset file_idx += 1 if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode) if mode == "train": self.save_original_examples(data[:5], data_name) print(f"finishing processing {dial_idx+1} dialogs for {mode} set ...") self.save_converted_examples(data_name) print("*"*10, f"finishing processing dataset {data_name}", "*"*10) def woi(self): """ actions: Apprentice => Wizard Wizard => SearchAgent SearchAgent => Wizard Wizard => Apprentice """ data_name = "wizard_of_internet" for mode in ["test", "train"]: data = self._load_jsonl(os.path.join(self.data_dir, data_name, f"{mode}.jsonl")) data = {k:v for dial in data for k,v in dial.items()} new_data, file_idx, dial_idx = {}, 1, 1 for dial_id, dial in tqdm(data.items()): # new_dial = dial new_dial = self.init_dial(dial_idx=dial_idx) new_dial_id = f"{data_name}--{mode}--{dial_idx}" new_dial[ORI_DIAL_ID] = dial_id new_dial[ORI_DIAL_INFO]["apprentice_persona"] = dial["apprentice_persona"] new_dial[ORI_DIAL_INFO]["start_timestamp"] = dial["start_timestamp"] turn_idx, dial_hist = 1, [] new_turn = self.init_turn(turn_id=turn_idx) for turn in dial["dialog_history"]: if turn["action"] == "Apprentice => Wizard": new_turn = self.init_turn(turn_id=turn_idx) new_turn[DIAL_HIST] = " ".join(dial_hist) new_turn[USR_UTT] = turn["text"] new_turn[ORI_USR_ANN]["timestamp"] = turn["timestamp"] dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT]) elif turn["action"] == "Wizard => SearchAgent": if "query" not in new_turn[ORI_SYS_ANN]: new_turn[ORI_SYS_ANN]["query"] = [] new_turn[ORI_SYS_ANN]["query"].append({ "query": turn["text"], "query_result": "", "timestamp_query": turn["timestamp"], }) elif turn["action"] == "SearchAgent => Wizard": # checked, each query corresponds to one query result # if new_turn[ORI_SYS_ANN]["query"][-1]["query_result"]: pdb.set_trace() new_turn[ORI_SYS_ANN]["query"][-1]["query_result"] = turn["context"] elif turn["action"] == "Wizard => Apprentice": new_turn[SYS_UTT] = turn["text"] for doc_id, doc in enumerate(turn["context"]["selected_contents"][1:]): for sent_id, choose in enumerate(doc): if choose: title = turn["context"]["contents"][doc_id]["title"] sent = turn["context"]["contents"][doc_id]["content"][sent_id] if title not in new_turn[EK_ORI][TOD_EK]: new_turn[EK_ORI][TOD_EK][title] = [] new_turn[EK_ORI][TOD_EK][title].append(sent) new_turn[EK] = self.dict_to_str(new_turn[EK_ORI][TOD_EK]) new_turn[ORI_SYS_ANN]["context"] = turn["context"] new_turn[ORI_SYS_ANN]["timestamp"] = turn["timestamp"] dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT]) new_dial[LOG].append(new_turn) turn_idx += 1 else: # checked, no such turns print(turn["action"]) raise ValueError("The fifth case") if not new_turn[SYS_UTT]: new_dial[LOG].append(new_turn) # new_dial[EK_ORI][TOD_EK]["apprentice_persona"] = dial["apprentice_persona"] # new_dial[EK] = self.dict_to_str(new_dial[EK_ORI][TOD_EK]) new_data[new_dial_id] = new_dial if dial_idx % 10000 == 0: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode) new_data = {} # reset file_idx += 1 dial_idx += 1 if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode) if mode == "train": self.save_original_examples({k:data[k] for k in list(data.keys())[:5]}, data_name) print(f"finishing processing {dial_idx-1} dialogs for {mode} set ...") self.save_converted_examples(data_name) print("*"*10, f"finishing processing dataset {data_name}", "*"*10) def run_all(self): self.wow() self.woi() def copy_example(self): source_dir = self.save_dir for target_dir in [ "/home/qkun/projs/TOD-Project/Datasets/Knowledge-Grounded_PROCESSED/", "/home/qkun/projs/DialogStudio-Release/knowledge-grounded-dialogues/"]: # target_dir = "/home/qkun/projs/TOD-Project/Datasets/Knowledge-Grounded_PROCESSED/" file_list = ["converted_examples.json", "original_examples.json", "readme.txt", "LICENSE"] for dir_name in sorted(os.listdir(source_dir)): if os.path.isfile(os.path.join(source_dir, dir_name)): continue if not os.path.exists(os.path.join(target_dir, dir_name)): os.makedirs(os.path.join(target_dir, dir_name)) for filename in file_list: source_path = os.path.join(source_dir, dir_name, filename) target_path = os.path.join(target_dir, dir_name, filename) if not os.path.exists(source_path): continue shutil.copy(source_path, target_path) def main(): preprocess = PreProcessData() preprocess.run_all() preprocess.copy_example() if __name__ == '__main__': main()