# import gradio as gr
import gradio
# import lmdb
# import base64
# import io
import random
import time
import os
import re
import sys
import json
import copy
# import sqlite3
import hashlib
import uuid
from urllib.parse import urljoin
import openai


def get_random_sleep(base_time, random_range):
    return (base_time + random.randint(-random_range, random_range))*0.001


def js_load(txt):
    try:
        return json.loads(txt)
    except Exception as error:
        print('')
        print('js_load:')
        print(str(error))
        print('')
        return None


def js_dump(thing):
    try:
        return json.dumps(thing)
    except Exception as error:
        print('')
        print('js_dump:')
        print(str(error))
        print('')
        return None


def filtered_history(history, num=0):
    if num > 0:
        filtered = list(filter(lambda it:(it['type'] in ['request', 'response']), history))
        return filtered[-num:]
    return []


def filtered_history_messages(history, num=0):
    filtered = filtered_history(history, num)
    return list(map(lambda it:{'role': it.get('role'), 'content': it.get('content')}, filtered))


def make_md_line(role, content):
    return f"""\n##### `{role}`\n\n{content}\n"""


def make_md_by_history(history):
    md = ""
    for item in history:
        md += make_md_line(item.get('role'), item.get('content'))
    return md


def make_history_file_fn(history):

    uuid4 = str(uuid.uuid4())
    json_file_path = None
    md_file_path = None

    save_history = []
    for item in history:
        if item["role"] == "assistant":
            info = {
                "content": str(item["content"]).replace("\n", "")
            }
            save_history.append(info)

    try:
        # 如果目录不存在，则创建目录
        os.makedirs('temp_files', exist_ok=True)

        json_file_content = json.dumps(save_history, ensure_ascii=False)
        json_file_path = os.path.join('temp_files', f'save_history[{uuid4}].json')
        with open(json_file_path, 'w') as f:
            f.write(json_file_content)

        md_file_content = make_md_by_history(save_history)
        md_file_path = os.path.join('temp_files', f'save_history[{uuid4}].md')
        with open(md_file_path, 'w') as f:
            f.write(md_file_content)

        return json_file_path, md_file_path, gradio.update(visible=True)

    except Exception as error:
        print(f"\n{error}\n")

    return json_file_path, md_file_path, gradio.update(visible=True)


def make_history_file_fn__(history):
    uuid4 = str(uuid.uuid4())
    try:
        json_file_content = json.dumps(history, ensure_ascii=False)
        json_file_path = os.path.join('temp_files', f'history[{uuid4}].json')
        with open(json_file_path, 'w') as f:
            f.write(json_file_content)
    except Exception as error:
        print(f"\n{error}\n")
        json_file_path = None
    try:
        md_file_content = make_md_by_history(history)
        md_file_path = os.path.join('temp_files', f'history[{uuid4}].md')
        with open(md_file_path, 'w') as f:
            f.write(md_file_content)
    except Exception as error:
        print(f"\n{error}\n")
        md_file_path = None

    return json_file_path, md_file_path, gradio.update(visible=True)


def make_user_message_list_fn__(
        user_message_template,  # 模板，套用到每一条消息上
        user_message_template_mask,  # 模板中要被替换的部分
        user_message_template_mask_is_regex,  # 决定如何构造用于替换的正则表达式
        user_message_list_text,  # 一段文本，包含了每一条用户消息
        user_message_list_text_splitter,  # 描述了应该以什么为线索来切分 user_message_list_text
        user_message_list_text_splitter_is_regex,  # 决定如何进行切分
    ) -> list:
    # 返回套用了模板的用户信息列表
    # 这个实现首先根据是否使用正则表达式来切分用户消息列表文本，并将切分后的消息存储在一个列表中。
    # 然后，针对每个消息，根据user_message_template_mask及user_message_template_mask_is_regex替换模板中的部分内容，
    # 并将替换后的结果添加到结果列表中。
    # 最后，返回结果列表。

    # 切分用户消息列表文本
    if user_message_list_text_splitter_is_regex:
        user_messages = re.split(user_message_list_text_splitter, user_message_list_text)
    else:
        user_messages = user_message_list_text.split(user_message_list_text_splitter)

    # 生成套用模板的用户信息列表
    user_message_result_list = []
    for message in user_messages:
        # 替换模板内容
        if user_message_template_mask_is_regex:
            transformed_message = re.sub(user_message_template_mask, message, user_message_template)
        else:
            transformed_message = user_message_template.replace(user_message_template_mask, message)

        user_message_result_list.append(transformed_message)

    return user_message_result_list


def make_user_message_list_fn(
        user_message_template,  
        user_message_template_mask, 
        user_message_template_mask_is_regex,  
        user_message_list_text, 
        user_message_list_text_splitter,  
        user_message_list_text_splitter_is_regex,  
    ) -> list:

    # 实际上，只要保证在使用正则表达式进行替换或切分操作之前，已经将其编译为正则表达式对象即可。
    # 在我的修改中，针对 xxx_is_regex 参数为 True 的情况，将这些参数编译成正则表达式。
    # 对于替换操作和切分操作，只需检查是否已经编译为正则表达式，并使用相应的方法即可。

    # 编译正则表达式
    if user_message_template_mask_is_regex:
        user_message_template_mask = re.compile(user_message_template_mask)

    if user_message_list_text_splitter_is_regex:
        user_message_list_text_splitter = re.compile(user_message_list_text_splitter)

    # 切分用户消息列表文本
    if user_message_list_text_splitter_is_regex:
        user_messages = user_message_list_text_splitter.split(user_message_list_text)
    else:
        user_messages = user_message_list_text.split(user_message_list_text_splitter)

    # 生成套用模板的用户信息列表
    user_message_result_list = []
    for message in user_messages:
        # 替换模板内容
        if user_message_template_mask_is_regex:
            transformed_message = user_message_template_mask.sub(message, user_message_template)
        else:
            transformed_message = user_message_template.replace(user_message_template_mask, message)

        user_message_result_list.append(transformed_message)

    return user_message_result_list


def sequential_chat_once_fn(payload, api_key_text, history, history_md_stable, history_md_stream, tips):
    # print("\n\n")

    assistant_message = ""
    tips = ""

    try:
        openai.api_key = api_key_text
        completion = openai.ChatCompletion.create(**payload)

        if payload.get('stream'):
            print('assistant:')
            # print('->>>')
            is_first=True
            for chunk in completion:
                if is_first:
                    is_first = False
                    continue
                if chunk.choices[0].finish_reason is None:
                    # sys.stdout.write("\r")
                    print(chunk.choices[0].delta.content or '', end="")
                    assistant_message += chunk.choices[0].delta.content or ''
                    # print(f"\033[2K{assistant_message}", end="")
                    history_md_stream = make_md_line('assistant', assistant_message)
                    tips = 'streaming'
                    yield assistant_message, history_md_stream, tips, history
                else:
                    pass
                pass
            # print('=>>>')
            print('')
            pass
        else:
            assistant_message = completion.choices[0].message.content
            history_md_stream = make_md_line('assistant', assistant_message)
            tips = 'got'
            print('assistant:')
            print(assistant_message)
            yield assistant_message, history_md_stream, tips, history
        pass

    except Exception as error:
        tips = str(error)
        history.append({"role": "app", "content": tips})
        print(f"\n{tips}\n")
        yield assistant_message, history_md_stream, tips, history
        pass

    # print("\n\n")


def sequential_chat_fn(
        history,

        system_prompt_enabled,
        system_prompt,
        user_message_template,
        user_message_template_mask,
        user_message_template_mask_is_regex,
        user_message_list_text,
        user_message_list_text_splitter,
        user_message_list_text_splitter_is_regex,
        history_prompt_num,

        api_key_text, token_text,

        sleep_base, sleep_rand,

        prop_stream, prop_model, prop_temperature, prop_top_p, prop_choices_num, prop_max_tokens, prop_presence_penalty, prop_frequency_penalty, prop_logit_bias,
    ):
    # outputs=[
    #     history,
    #     history_md_stable,
    #     history_md_stream,
    #     tips,
    #     file_row,
    # ],

    history_md_stable = ""
    history_md_stream = ""
    tips = ""

    try:

        user_message_list = make_user_message_list_fn(
            user_message_template,
            user_message_template_mask,
            user_message_template_mask_is_regex,
            user_message_list_text,
            user_message_list_text_splitter,
            user_message_list_text_splitter_is_regex,
        )

        payload = {
            'model': prop_model,
            'temperature': prop_temperature,
            'top_p': prop_top_p,
            'n': prop_choices_num,
            'stream': prop_stream,
            'presence_penalty': prop_presence_penalty,
            'frequency_penalty': prop_frequency_penalty,
            'user': token_text,
        }
        if prop_max_tokens>0:
            payload['max_tokens'] = prop_max_tokens
        # if prop_logit_bias is not None:
        #     payload['logit_bias'] = prop_logit_bias
        # headers = {
        #     "Content-Type": "application/json",
        #     "Authorization": f"Bearer {api_key_text}"
        # }

        for user_message in user_message_list:
            print('')
            print(f'user({token_text}):')
            print(user_message)
            print('')
            # make the_messages to sent
            the_messages = []
            if system_prompt_enabled:
                the_messages.append({"role": "system", "content": system_prompt})
            for msg in filtered_history_messages(history, num=history_prompt_num):
                the_messages.append(msg)
            the_messages.append({"role": "user", "content": user_message})
            payload['messages'] = the_messages

            history.append({"role": "user", "content": user_message, "type": "request", "payload": payload})

            history_md_stable = make_md_by_history(history)
            history_md_stream = ""
            tips = ""
            yield history, history_md_stable, history_md_stream, tips, gradio.update(visible=False)

            try:
                for (assistant_message, history_md_stream, tips, history) in sequential_chat_once_fn(payload, api_key_text, history, history_md_stable, history_md_stream, tips):

                    yield history, history_md_stable, history_md_stream, tips, gradio.update()

                history.append({"role": "assistant", "content": assistant_message, "type": "request"})
                history_md_stable += history_md_stream
                history_md_stream = ""
                tips = "fine"
                yield history, history_md_stable, history_md_stream, tips, gradio.update(visible=False)

            except Exception as error:
                tips = f'error: {str(error)}'
                history.append({"role": "app", "content": tips})
                print(f"\n{tips}\n")
                yield history, history_md_stable, history_md_stream, tips, gradio.update(visible=False)

            time.sleep(get_random_sleep(sleep_base, sleep_rand))
        pass



    except Exception as error:
        tips = str(error)
        history.append({"role": "app", "content": tips})
        print(f"\n{tips}\n")
        yield history, history_md_stable, history_md_stream, tips, gradio.update(visible=False)
        pass




def on_click_send_btn(
        global_state_json, api_key_text, chat_input_role, chat_input, prompt_table, chat_use_prompt, chat_use_history, chat_log,
        chat_model, temperature, top_p, choices_num, stream, max_tokens, presence_penalty, frequency_penalty, logit_bias,
    ):

    old_state = json.loads(global_state_json or "{}")

    print('\n\n\n\n\n')
    print(prompt_table)
    prompt_table = prompt_table or []

    chat_log = chat_log or []

    chat_log_md = ''
    if chat_use_prompt:
        chat_log_md += '<center>(prompt)</center>\n\n'
        chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)])
        chat_log_md += '\n---\n'
    if True:
        chat_log_md += '<center>(history)</center>\n\n' if chat_use_history else '<center>(not used history)</center>\n\n'
        chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", chat_log)])
        chat_log_md += '\n---\n'

    # if chat_input=='':
    #     return json.dumps(old_state), chat_log, chat_log_md, chat_log_md, None, None, chat_input

    print('\n')
    print(chat_input)
    print('')

    try:
        logit_bias_json = json.dumps(logit_bias) if logit_bias else None
    except:
        return json.dumps(old_state), chat_log, chat_log_md, chat_log_md, None, None, chat_input

    new_state = copy.deepcopy(old_state) or {}



    req_hist = copy.deepcopy(prompt_table) if chat_use_prompt else []

    if chat_use_history:
        for hh in (chat_log or []):
            req_hist.append(hh)

    if chat_input and chat_input!="":
        req_hist.append([(chat_input_role or 'user'), chat_input])

    openai.api_key = api_key_text

    props = {
        'model': chat_model,
        'messages': [xx for xx in map(lambda it: {'role':it[0], 'content':it[1]}, req_hist)],
        'temperature': temperature,
        'top_p': top_p,
        'n': choices_num,
        'stream': stream,
        'presence_penalty': presence_penalty,
        'frequency_penalty': frequency_penalty,
    }
    if max_tokens>0:
        props['max_tokens'] = max_tokens
    if logit_bias_json is not None:
        props['logit_bias'] = logit_bias_json

    props_json = json.dumps(props)

    try:
        completion = openai.ChatCompletion.create(**props)
        print('')

        # print(completion.choices)
        # the_response_role = completion.choices[0].message.role
        # the_response = completion.choices[0].message.content
        # print(the_response)
        # print('')
        # chat_last_resp = json.dumps(completion.__dict__)
        # chat_last_resp_dict = json.loads(chat_last_resp)
        # chat_last_resp_dict['api_key'] = "hidden by UI"
        # chat_last_resp_dict['organization'] = "hidden by UI"
        # chat_last_resp = json.dumps(chat_last_resp_dict)


        chat_log_md = ''
        if chat_use_prompt:
            chat_log_md += '<center>(prompt)</center>\n\n'
            chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)])
            chat_log_md += '\n---\n'
        if True:
            chat_log_md += '<center>(history)</center>\n\n' if chat_use_history else '<center>(not used history)</center>\n\n'
            chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", chat_log)])
            chat_log_md += '\n---\n'

        if chat_input and chat_input!="":
            chat_log.append([(chat_input_role or 'user'), chat_input])
            chat_log_md += f"##### `{(chat_input_role or 'user')}`\n\n{chat_input}\n\n"

        partial_words = ""
        counter=0

        if stream:
            the_response = ''
            the_response_role = ''
            for chunk in completion:
                #Skipping first chunk
                if counter == 0:
                    the_response_role = chunk.choices[0].delta.role
                    chat_log_md += f"##### `{the_response_role}`\n\n"
                    counter += 1
                    continue
                # print(('chunk', chunk))
                if chunk.choices[0].finish_reason is None:
                    the_response_chunk = chunk.choices[0].delta.content
                    the_response += the_response_chunk
                    chat_log_md += f"{the_response_chunk}"
                    yield json.dumps(new_state), chat_log, chat_log_md, chat_log_md, "{}", props_json, ''
                else:
                    chat_log.append([the_response_role, the_response])
                    chat_log_md += f"\n\n"
                    yield json.dumps(new_state), chat_log, chat_log_md, chat_log_md, '{"msg": "stream模式不支持显示"}', props_json, ''
                # chat_last_resp = json.dumps(completion.__dict__)
                # chat_last_resp_dict = json.loads(chat_last_resp)
                # chat_last_resp_dict['api_key'] = "hidden by UI"
                # chat_last_resp_dict['organization'] = "hidden by UI"
                # chat_last_resp = json.dumps(chat_last_resp_dict)
        else:
            the_response_role = completion.choices[0].message.role
            the_response = completion.choices[0].message.content
            print(the_response)
            print('')

            chat_log.append([the_response_role, the_response])
            chat_log_md += f"##### `{the_response_role}`\n\n{the_response}\n\n"

            chat_last_resp = json.dumps(completion.__dict__)
            chat_last_resp_dict = json.loads(chat_last_resp)
            chat_last_resp_dict['api_key'] = "hidden by UI"
            chat_last_resp_dict['organization'] = "hidden by UI"
            chat_last_resp = json.dumps(chat_last_resp_dict)
    
            return json.dumps(new_state), chat_log, chat_log_md, chat_log_md, chat_last_resp, props_json, ''

        # chat_log.append([the_response_role, the_response])
        # chat_log_md += f"##### `{the_response_role}`\n\n{the_response}\n\n"
        # return json.dumps(new_state), chat_log, chat_log_md, chat_log_md, chat_last_resp, props_json, ''
    except Exception as error:
        print(error)
        print('error!!!!!!')

        chat_log_md = ''
        if chat_use_prompt:
            chat_log_md += '<center>(prompt)</center>\n\n'
            chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)])
            chat_log_md += '\n---\n'
        if True:
            chat_log_md += '<center>(history)</center>\n\n' if chat_use_history else '<center>(not used history)</center>\n\n'
            chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", chat_log)])
            chat_log_md += '\n---\n'

        # chat_log_md = ''
        # chat_log_md = "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)]) if chat_use_prompt else ''
        # chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", hist)])

        chat_log_md += "\n"
        chat_log_md += str(error)
        return json.dumps(new_state), chat_log, chat_log_md, chat_log_md, None, props_json, chat_input


def clear_history():
    return [], ""


def copy_history(txt):
    # print('\n\n copying')
    # print(txt)
    # print('\n\n')
    pass


def update_saved_prompt_titles(global_state_json, selected_saved_prompt_title):
    print('')
    global_state = json.loads(global_state_json or "{}")
    print(global_state)
    print(selected_saved_prompt_title)
    saved_prompts = global_state.get('saved_prompts') or []
    print(saved_prompts)
    the_choices = [(it.get('title') or '[untitled]') for it in saved_prompts]
    print(the_choices)
    print('')
    return gradio.Dropdown.update(choices=the_choices)


def save_prompt(global_state_json, saved_prompts, prompt_title, prompt_table):
    the_choices = []
    global_state = json.loads(global_state_json or "{}")
    saved_prompts = global_state.get('saved_prompts') or []
    if len(saved_prompts):
        the_choices = [it.get('title') or '[untitled]' for it in saved_prompts]
        pass
    return global_state_json, gradio.Dropdown.update(choices=the_choices, value=prompt_title), prompt_title, prompt_table


def load_saved_prompt(title):
    pass