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import json |
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import os |
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import copy |
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import re |
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from os import listdir |
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from os.path import isfile, join |
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import argparse |
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import sys |
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INSTRUCT_CHUNKED_PROMPT = """你是一个擅长翻译科技新闻的翻译专家。请将以下内容翻译为中文，使用相同格式输出，并保留时间戳。不要漏掉任何信息。合并多行文本时，保留第一个和最后一个时间戳。 |
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""" |
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def break_line(line: str): |
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pattern = re.compile(r"^\[(\d+.\d+)\](.*)\[(\d+.\d+)\]$") |
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match = pattern.match(line) |
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start_time = match.group(1) |
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text = match.group(2) |
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end_time = match.group(3) |
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return start_time, text.strip(), end_time, float(start_time), float(end_time) |
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def get_total_chars(cn_lines: list[str], en_lines: list[str]): |
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cn_total_chars = 0 |
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en_total_chars = 0 |
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for line in cn_lines: |
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cn_total_chars += len(line) |
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for line in en_lines: |
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en_total_chars += len(line) |
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return cn_total_chars + en_total_chars |
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def chunk_messages(cn_lines: list[str], en_lines: list[str], MAX_LEN: int = 2000): |
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cn_lines_copy = copy.deepcopy(cn_lines) |
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en_lines_copy = copy.deepcopy(en_lines) |
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final_chunks: list[tuple[list[str], list[str]]] = [] |
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while True: |
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en_current_chunk = [] |
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cn_current_chunk = [] |
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while True: |
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curr_total_len = get_total_chars(cn_current_chunk, en_current_chunk) |
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if len(cn_lines_copy) == 0 or len(en_lines_copy) == 0: |
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final_chunks.append((cn_current_chunk, en_current_chunk)) |
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return final_chunks |
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elif curr_total_len > MAX_LEN: |
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final_chunks.append((cn_current_chunk, en_current_chunk)) |
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break |
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else: |
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latest_cn_line = cn_lines_copy.pop(0) |
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cn_start, cn_text, cn_end, cn_start_f, cn_end_f = break_line(latest_cn_line) |
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cn_current_chunk.append(latest_cn_line) |
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while True: |
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latest_en_line = en_lines_copy.pop(0) |
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en_start, en_text, en_end, en_start_f, en_end_f = break_line(latest_en_line) |
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en_current_chunk.append(latest_en_line) |
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if en_end == cn_end: |
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break |
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else: |
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if en_start_f > cn_end_f: |
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raise Exception("ERROR: English and Chinese lines are not in sync. Offensing line: " + latest_cn_line) |
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def new_message(eng_in, chs_out, prev_in = None, prev_out = None): |
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if(prev_in == None or prev_out == None): |
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return {"messages": [ |
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{"role": "system", "content": INSTRUCT_CHUNKED_PROMPT}, |
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{"role": "user", "content": eng_in}, |
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{"role": "assistant", "content": chs_out}] |
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} |
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else: |
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return {"messages": [ |
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{"role": "system", "content": INSTRUCT_CHUNKED_PROMPT}, |
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{"role": "user", "content": prev_in}, |
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{"role": "assistant", "content": prev_out}, |
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{"role": "user", "content": eng_in}, |
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{"role": "assistant", "content": chs_out}] |
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} |
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def write_jsonl(message_groups, filename): |
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json_lines = [] |
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with open(filename, "w", encoding='utf-8-sig') as fout: |
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for i in range(len(message_groups)): |
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if(i>0): |
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msg_obj = new_message( |
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message_groups[i][0].strip(), |
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message_groups[i][1].strip(), |
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message_groups[i-1][0].strip(), |
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message_groups[i-1][1].strip() |
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) |
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else: |
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msg_obj = new_message( |
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message_groups[i][0].strip(), |
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message_groups[i][1].strip() |
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) |
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json.dump(msg_obj, fout) |
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fout.write("\n") |
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json_lines.append(json.dumps(msg_obj)) |
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return json_lines |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser(description='Generate ChatGPT training data from a directory of subtitle files.') |
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parser.add_argument('data_dir', type=str, help='The directory containing the subtitle files.', default="data") |
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parser.add_argument('--maxlen', type=int, help='The maximum length of a combined message. \nNote that this limit will be exceeded a little bit, so leave some headroom. \nRecommended value is max context length / 4.', default=2000) |
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parser.add_argument('--test-ratio', type=float, help='The ratio of test data to training data.', default=0.2) |
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args = parser.parse_args() |
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message_groups = [] |
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DOCUMENT_ROOT = args.data_dir |
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files = listdir(DOCUMENT_ROOT) |
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files = list(filter(lambda x: x.endswith(".en.txt"), files)) |
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files.sort() |
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for f in files: |
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en_fname = join(DOCUMENT_ROOT, f) |
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if en_fname.endswith(".en.txt") and isfile(en_fname): |
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cn_fname = join(DOCUMENT_ROOT, f.replace(".en.txt", ".cn.txt")) |
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if os.path.exists(cn_fname) and isfile(cn_fname): |
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print(f"Found data pair: {en_fname} and {cn_fname}") |
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with open(en_fname, "r", encoding='utf-8-sig') as enfin: |
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en_messages = enfin.read() |
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with open(cn_fname, "r", encoding='utf-8-sig') as cnfin: |
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cn_messages = cnfin.read() |
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en_messages = [part.strip() for part in en_messages.split("\n") if part.strip() != ""] |
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cn_messages = [part.strip() for part in cn_messages.split("\n") if part.strip() != ""] |
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try: |
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chunks = chunk_messages(cn_messages, en_messages, MAX_LEN=args.maxlen) |
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en_messages = [] |
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cn_messages = [] |
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for chunk in chunks: |
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cn_chunk, en_chunk = chunk |
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en_messages.append("\n".join(en_chunk)) |
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cn_messages.append("\n".join(cn_chunk)) |
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except Exception as e: |
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print(f"Error: {e}") |
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continue |
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if(len(en_messages) != len(cn_messages)): |
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print(f"English and Chinese version mismatch. Discarding {en_fname} pair.") |
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messages = zip(en_messages, cn_messages) |
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message_groups.extend(messages) |
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jsonl_lines = write_jsonl(message_groups, f"combined-{args.maxlen}.jsonl") |
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import random |
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random.shuffle(jsonl_lines) |
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TEST_RATIO = args.test_ratio |
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split_index = int(len(jsonl_lines) * TEST_RATIO) |
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test = jsonl_lines[:split_index] |
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train = jsonl_lines[split_index:] |
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with open (f"chatgpt-train-{args.maxlen}.jsonl", "w", encoding='utf-8-sig') as fout: |
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for line in train: |
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fout.write(line + "\n") |
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with open (f"chatgpt-test-{args.maxlen}.jsonl", "w", encoding='utf-8-sig') as fout: |
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for line in test: |
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fout.write(line + "\n") |
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