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from predict import predict_no_ui
from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
fast_debug = False


def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
    import time, glob, os
    print('begin analysis on:', file_manifest)
    for index, fp in enumerate(file_manifest):
        with open(fp, 'r', encoding='utf-8') as f:
            file_content = f.read()

        prefix = "接下来请你逐文件分析下面的论文文件,概括其内容" if index==0 else ""
        i_say = prefix + f'请对下面的文章片段用中文做一个概述,文件名是{os.path.relpath(fp, project_folder)},文章内容是 ```{file_content}```'
        i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}'
        chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
        print('[1] yield chatbot, history')
        yield chatbot, history, '正常'

        if not fast_debug: 
            msg = '正常'
            # ** gpt request **
            gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[])   # 带超时倒计时

            print('[2] end gpt req')
            chatbot[-1] = (i_say_show_user, gpt_say)
            history.append(i_say_show_user); history.append(gpt_say)
            print('[3] yield chatbot, history')
            yield chatbot, history, msg
            print('[4] next')
            if not fast_debug: time.sleep(2)

    all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
    i_say = f'根据以上你自己的分析,对全文进行概括,用学术性语言写一段中文摘要,然后再写一段英文摘要(包括{all_file})。'
    chatbot.append((i_say, "[Local Message] waiting gpt response."))
    yield chatbot, history, '正常'

    if not fast_debug: 
        msg = '正常'
        # ** gpt request **
        gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history)   # 带超时倒计时

        chatbot[-1] = (i_say, gpt_say)
        history.append(i_say); history.append(gpt_say)
        yield chatbot, history, msg
        res = write_results_to_file(history)
        chatbot.append(("完成了吗?", res))
        yield chatbot, history, msg


def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
    import time, glob, os, codecs, fitz
    print('begin analysis on:', file_manifest)
    for index, fp in enumerate(file_manifest):
        with fitz.open(fp) as doc:
            file_content = ""
            for page in doc:
                file_content += page.getText()
            print(file_content)

        prefix = "接下来请你逐文件分析下面的论文文件,概括其内容" if index==0 else ""
        i_say = prefix + f'请对下面的文章片段用中文做一个概述,文件名是{os.path.relpath(fp, project_folder)},文章内容是 ```{file_content}```'
        i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}'
        chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
        print('[1] yield chatbot, history')
        yield chatbot, history, '正常'

        if not fast_debug: 
            msg = '正常'
            # ** gpt request **
            gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[])   # 带超时倒计时

            print('[2] end gpt req')
            chatbot[-1] = (i_say_show_user, gpt_say)
            history.append(i_say_show_user); history.append(gpt_say)
            print('[3] yield chatbot, history')
            yield chatbot, history, msg
            print('[4] next')
            if not fast_debug: time.sleep(2)

    all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
    i_say = f'根据以上你自己的分析,对全文进行概括,用学术性语言写一段中文摘要,然后再写一段英文摘要(包括{all_file})。'
    chatbot.append((i_say, "[Local Message] waiting gpt response."))
    yield chatbot, history, '正常'

    if not fast_debug: 
        msg = '正常'
        # ** gpt request **
        gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history)   # 带超时倒计时

        chatbot[-1] = (i_say, gpt_say)
        history.append(i_say); history.append(gpt_say)
        yield chatbot, history, msg
        res = write_results_to_file(history)
        chatbot.append(("完成了吗?", res))
        yield chatbot, history, msg


def 读文章写摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
    history = []    # 清空历史,以免输入溢出
    import glob, os
    if os.path.exists(txt):
        project_folder = txt
    else:
        if txt == "": txt = '空空如也的输入栏'
        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
        yield chatbot, history, '正常'
        return
    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] + \
                    [f for f in glob.glob(f'{project_folder}/**/*.pdf', recursive=True)] # + \
                    # [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
                    # [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
    if len(file_manifest) == 0:
        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或.pdf文件: {txt}")
        yield chatbot, history, '正常'
        return
    if '.pdf' in file_manifest[0]:
        yield from 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
    else:
        yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)