File size: 11,508 Bytes
7947c96
2712d99
 
 
 
 
 
 
 
 
 
 
 
b0409b9
 
dd648bd
2712d99
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7947c96
 
 
 
 
 
 
 
e7df3a5
7947c96
 
 
 
2712d99
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5d23420
2712d99
 
7947c96
2712d99
 
 
 
 
 
 
 
 
 
7947c96
 
 
 
 
2712d99
 
 
 
 
 
 
 
b2fba01
2712d99
 
7947c96
 
 
 
 
 
 
 
2712d99
 
 
 
 
 
 
 
 
9a4b562
 
2712d99
9a4b562
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2712d99
 
 
 
 
 
 
 
 
 
 
 
 
5eea959
2712d99
 
 
 
 
 
 
5eea959
9a4b562
4783fd6
9a4b562
5eea959
2712d99
 
 
 
5eea959
2712d99
 
 
 
5eea959
2712d99
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4783fd6
2712d99
 
 
 
 
 
 
4783fd6
 
 
2712d99
 
 
 
 
 
 
 
7947c96
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
from toolbox import update_ui, trimmed_format_exc, gen_time_str
from toolbox import CatchException, report_execption, write_results_to_file
fast_debug = False

class PaperFileGroup():
    def __init__(self):
        self.file_paths = []
        self.file_contents = []
        self.sp_file_contents = []
        self.sp_file_index = []
        self.sp_file_tag = []

        # count_token
        from request_llm.bridge_all import model_info
        enc = model_info["gpt-3.5-turbo"]['tokenizer']
        def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
        self.get_token_num = get_token_num

    def run_file_split(self, max_token_limit=1900):
        """
        将长文本分离开来
        """
        for index, file_content in enumerate(self.file_contents):
            if self.get_token_num(file_content) < max_token_limit:
                self.sp_file_contents.append(file_content)
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
                    self.sp_file_index.append(index)
                    self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.md")
        print('Segmentation: done')

    def merge_result(self):
        self.file_result = ["" for _ in range(len(self.file_paths))]
        for r, k in zip(self.sp_file_result, self.sp_file_index):
            self.file_result[k] += r

    def write_result(self):
        manifest = []
        for path, res in zip(self.file_paths, self.file_result):
            with open(path + f'.{gen_time_str()}.trans.md', 'w', encoding='utf8') as f:
                manifest.append(path + '.trans.md')
                f.write(res)
        return manifest

def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'):
    import time, os, re
    from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency

    #  <-------- 读取Markdown文件,删除其中的所有注释 ----------> 
    pfg = PaperFileGroup()

    for index, fp in enumerate(file_manifest):
        with open(fp, 'r', encoding='utf-8', errors='replace') as f:
            file_content = f.read()
            # 记录删除注释后的文本
            pfg.file_paths.append(fp)
            pfg.file_contents.append(file_content)

    #  <-------- 拆分过长的Markdown文件 ----------> 
    pfg.run_file_split(max_token_limit=1500)
    n_split = len(pfg.sp_file_contents)

    #  <-------- 多线程翻译开始 ----------> 
    if language == 'en->zh':
        inputs_array = ["This is a Markdown file, translate it into Chinese, do not modify any existing Markdown commands:" + 
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
    elif language == 'zh->en':
        inputs_array = [f"This is a Markdown file, translate it into English, do not modify any existing Markdown commands:" + 
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
    else:
        inputs_array = [f"This is a Markdown file, translate it into {language}, do not modify any existing Markdown commands, only answer me with translated results:" + 
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]

    gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
        inputs_array=inputs_array,
        inputs_show_user_array=inputs_show_user_array,
        llm_kwargs=llm_kwargs,
        chatbot=chatbot,
        history_array=[[""] for _ in range(n_split)],
        sys_prompt_array=sys_prompt_array,
        # max_workers=5,  # OpenAI所允许的最大并行过载
        scroller_max_len = 80
    )
    try:
        pfg.sp_file_result = []
        for i_say, gpt_say in zip(gpt_response_collection[0::2], gpt_response_collection[1::2]):
            pfg.sp_file_result.append(gpt_say)
        pfg.merge_result()
        pfg.write_result()
    except:
        print(trimmed_format_exc())

    #  <-------- 整理结果,退出 ----------> 
    create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
    res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name)
    history = gpt_response_collection
    chatbot.append((f"{fp}完成了吗?", res))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面


def get_files_from_everything(txt):
    import glob, os

    success = True
    if txt.startswith('http'):
        # 网络的远程文件
        txt = txt.replace("https://github.com/", "https://raw.githubusercontent.com/")
        txt = txt.replace("/blob/", "/")
        import requests
        from toolbox import get_conf
        proxies, = get_conf('proxies')
        r = requests.get(txt, proxies=proxies)
        with open('./gpt_log/temp.md', 'wb+') as f: f.write(r.content)
        project_folder = './gpt_log/'
        file_manifest = ['./gpt_log/temp.md']
    elif txt.endswith('.md'):
        # 直接给定文件
        file_manifest = [txt]
        project_folder = os.path.dirname(txt)
    elif os.path.exists(txt):
        # 本地路径,递归搜索
        project_folder = txt
        file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)]
    else:
        success = False

    return success, file_manifest, project_folder


@CatchException
def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
    # 基本信息:功能、贡献者
    chatbot.append([
        "函数插件功能?",
        "对整个Markdown项目进行翻译。函数插件贡献者: Binary-Husky"])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

    # 尝试导入依赖,如果缺少依赖,则给出安装建议
    try:
        import tiktoken
        import glob, os
    except:
        report_execption(chatbot, history,
                         a=f"解析项目: {txt}",
                         b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade tiktoken```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    history = []    # 清空历史,以免输入溢出

    success, file_manifest, project_folder = get_files_from_everything(txt)

    if not success:
        # 什么都没有
        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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return

    if len(file_manifest) == 0:
        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return

    yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en->zh')





@CatchException
def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
    # 基本信息:功能、贡献者
    chatbot.append([
        "函数插件功能?",
        "对整个Markdown项目进行翻译。函数插件贡献者: Binary-Husky"])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

    # 尝试导入依赖,如果缺少依赖,则给出安装建议
    try:
        import tiktoken
        import glob, os
    except:
        report_execption(chatbot, history,
                         a=f"解析项目: {txt}",
                         b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade tiktoken```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    history = []    # 清空历史,以免输入溢出
    success, file_manifest, project_folder = get_files_from_everything(txt)
    if not success:
        # 什么都没有
        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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    if len(file_manifest) == 0:
        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh->en')


@CatchException
def Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
    # 基本信息:功能、贡献者
    chatbot.append([
        "函数插件功能?",
        "对整个Markdown项目进行翻译。函数插件贡献者: Binary-Husky"])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

    # 尝试导入依赖,如果缺少依赖,则给出安装建议
    try:
        import tiktoken
        import glob, os
    except:
        report_execption(chatbot, history,
                         a=f"解析项目: {txt}",
                         b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade tiktoken```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    history = []    # 清空历史,以免输入溢出
    success, file_manifest, project_folder = get_files_from_everything(txt)
    if not success:
        # 什么都没有
        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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    if len(file_manifest) == 0:
        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
    
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    language = plugin_kwargs.get("advanced_arg", 'Chinese')
    yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language=language)