import json
import os
import copy
import re
from os import listdir
from os.path import isfile, join
import argparse
import sys

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。
"""

def break_line(line: str):
    pattern = re.compile(r"^\[(\d+.\d+)\](.*)\[(\d+.\d+)\]$")
    match = pattern.match(line)
    start_time = match.group(1)
    text = match.group(2)
    end_time = match.group(3)
    return start_time, text.strip(), end_time, float(start_time), float(end_time)

def get_total_chars(cn_lines: list[str], en_lines: list[str]):
    cn_total_chars = 0
    en_total_chars = 0

    for line in cn_lines:
        cn_total_chars += len(line)
    
    for line in en_lines:
        en_total_chars += len(line)
    
    return cn_total_chars + en_total_chars

def chunk_messages(cn_lines: list[str], en_lines: list[str], MAX_LEN: int = 2000):
    cn_lines_copy = copy.deepcopy(cn_lines)
    en_lines_copy = copy.deepcopy(en_lines)

    final_chunks: list[tuple[list[str], list[str]]] = []
    
    while True:
        en_current_chunk = []
        cn_current_chunk = []
        while True:
            curr_total_len = get_total_chars(cn_current_chunk, en_current_chunk)
            if len(cn_lines_copy) == 0 or len(en_lines_copy) == 0:
                final_chunks.append((cn_current_chunk, en_current_chunk))
                return final_chunks
            elif curr_total_len > MAX_LEN:
                final_chunks.append((cn_current_chunk, en_current_chunk))
                break
            else:
                # Try append a new line to current chunk
                latest_cn_line = cn_lines_copy.pop(0)
                cn_start, cn_text, cn_end, cn_start_f, cn_end_f = break_line(latest_cn_line)
                cn_current_chunk.append(latest_cn_line)
                while True:
                    latest_en_line = en_lines_copy.pop(0)
                    en_start, en_text, en_end, en_start_f, en_end_f = break_line(latest_en_line)
                    en_current_chunk.append(latest_en_line)
                    if en_end == cn_end:
                        break
                    else:
                        if en_start_f > cn_end_f:
                            raise Exception("English and Chinese lines are not in sync. Offensing line: " + latest_cn_line)
                
def new_message(eng_in, chs_out, prev_in = None, prev_out = None):
    if(prev_in == None or prev_out == None):
        return {"messages": [
            {"role": "system", "content": INSTRUCT_CHUNKED_PROMPT}, 
            {"role": "user", "content": eng_in}, 
            {"role": "assistant", "content": chs_out}]
        }
    else:
        return {"messages": [
            {"role": "system", "content": INSTRUCT_CHUNKED_PROMPT}, 
            {"role": "user", "content": prev_in}, 
            {"role": "assistant", "content": prev_out},
            {"role": "user", "content": eng_in}, 
            {"role": "assistant", "content": chs_out}]
        }

def write_jsonl(message_groups, filename):
    json_lines = []
    with open(filename, "w", encoding='utf-8-sig') as fout:
        for i in range(len(message_groups)):
            if(i>0):
                msg_obj = new_message(
                    message_groups[i][0].strip(),
                    message_groups[i][1].strip(),
                    message_groups[i-1][0].strip(),
                    message_groups[i-1][1].strip()
                )
            else:
                msg_obj = new_message(
                    message_groups[i][0].strip(),
                    message_groups[i][1].strip()
                )
            json.dump(msg_obj, fout)
            fout.write("\n")
            json_lines.append(json.dumps(msg_obj))
    return json_lines

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Generate ChatGPT training data from a directory of subtitle files.')
    parser.add_argument('data_dir', type=str, help='The directory containing the subtitle files.', default="data")
    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)
    parser.add_argument('--test-ratio', type=float, help='The ratio of test data to training data.', default=0.2)

    args = parser.parse_args()

    message_groups = []

    DOCUMENT_ROOT = args.data_dir
    files = listdir(DOCUMENT_ROOT)
    files = list(filter(lambda x: x.endswith(".en.txt"), files))
    files.sort()

    print(files)

    for f in files:
        en_fname = join(DOCUMENT_ROOT, f)
        if en_fname.endswith(".en.txt") and isfile(en_fname):
            cn_fname = join(DOCUMENT_ROOT, f.replace(".en.txt", ".cn.txt"))
            if os.path.exists(cn_fname) and isfile(cn_fname):
                print(f"Found data pair: {en_fname} and {cn_fname}")

                with open(en_fname, "r", encoding='utf-8-sig') as enfin:
                    en_messages = enfin.read()

                with open(cn_fname, "r", encoding='utf-8-sig') as cnfin:
                    cn_messages = cnfin.read()
                
                en_messages = [part.strip() for part in en_messages.split("\n") if part.strip() != ""]
                cn_messages = [part.strip() for part in cn_messages.split("\n") if part.strip() != ""]

                try:
                    chunks = chunk_messages(cn_messages, en_messages, MAX_LEN=args.maxlen)
                    en_messages = []
                    cn_messages = []
                    for chunk in chunks:
                        cn_chunk, en_chunk = chunk
                        en_messages.append("\n".join(en_chunk))
                        cn_messages.append("\n".join(cn_chunk))
                        print("\n".join(en_chunk))
                        print("---")
                        print("\n".join(cn_chunk))
                        print("\n")
                except Exception as e:
                    print(f"Error: {e}")
                    continue
                
                if(len(en_messages) != len(cn_messages)):
                    print(f"English and Chinese version mismatch. Discarding {en_fname} pair.")
                
                messages = zip(en_messages, cn_messages)

                message_groups.extend(messages)

    jsonl_lines = write_jsonl(message_groups, f"combined-{args.maxlen}.jsonl")

    import random
    random.shuffle(jsonl_lines)

    TEST_RATIO = args.test_ratio

    split_index = int(len(jsonl_lines) * TEST_RATIO)

    test = jsonl_lines[:split_index]
    train = jsonl_lines[split_index:]

    with open (f"chatgpt-train-{args.maxlen}.jsonl", "w", encoding='utf-8-sig') as fout:
        for line in train:
            fout.write(line + "\n")

    with open (f"chatgpt-test-{args.maxlen}.jsonl", "w", encoding='utf-8-sig') as fout:
        for line in test:
            fout.write(line + "\n")

    # recent_files = files[-5:]
    # recent_messages = []

    # for f in recent_files:
    #     en_fname = join(DOCUMENT_ROOT, f)
    #     if en_fname.endswith(".en.txt") and isfile(en_fname):
    #         cn_fname = join(DOCUMENT_ROOT, f.replace(".en.txt", ".cn.txt"))
    #         if os.path.exists(cn_fname) and isfile(cn_fname):
    #             print(f"Found data pair: {en_fname} and {cn_fname}")

    #             with open(en_fname, "r", encoding='utf-8-sig') as enfin:
    #                 en_messages = enfin.read()

    #             with open(cn_fname, "r", encoding='utf-8-sig') as cnfin:
    #                 cn_messages = cnfin.read()
                
    #             en_messages = [part.strip() for part in en_messages.split("\n") if part.strip() != ""]
    #             cn_messages = [part.strip() for part in cn_messages.split("\n") if part.strip() != ""] 

    #             if(len(en_messages) != len(cn_messages)):
    #                 print(f"English and Chinese version mismatch. Discarding {en_fname} pair.")
                
    #             messages = zip(en_messages, cn_messages)

    #             recent_messages.extend(messages)

    # write_jsonl(recent_messages, "recent-combined.jsonl")

    # TEST_RATIO = 0.2

    # split_index = int(len(recent_messages) * TEST_RATIO)

    # test = recent_messages[:split_index]
    # train = recent_messages[split_index:]

    # write_jsonl(train, "chatgpt-recent-train.jsonl")
    # write_jsonl(test, "chatgpt-recent-test.jsonl")