File size: 15,021 Bytes
9593b0d
93c13aa
2c963cc
93c13aa
5e8eb62
9593b0d
 
 
 
5e8eb62
 
9593b0d
 
 
5e8eb62
9593b0d
5e8eb62
9593b0d
5e8eb62
7186d9b
8b4b30a
9593b0d
 
 
 
 
 
 
7186d9b
 
9593b0d
2bf30d8
 
f04d975
 
8b4b30a
f04d975
1805f08
8b4b30a
 
9593b0d
 
 
 
8b4b30a
9593b0d
 
5e8eb62
8b4b30a
9593b0d
8b4b30a
9593b0d
5e8eb62
8b4b30a
5e8eb62
61b4ea6
9593b0d
5e8eb62
 
f04d975
8b4b30a
f04d975
7186d9b
 
 
b017a3d
7186d9b
 
f04d975
7186d9b
61b4ea6
7186d9b
 
32f36a6
fedc748
 
 
32f36a6
 
043a9ea
 
32f36a6
b9f2792
32f36a6
 
d58802a
 
 
 
32f36a6
 
 
77408f7
32f36a6
 
93c13aa
 
fedc748
 
 
93c13aa
 
 
 
 
 
fedc748
 
 
93c13aa
 
 
 
 
 
2bf30d8
 
5b9de09
 
 
93c13aa
 
 
363e455
 
 
 
 
 
 
 
 
 
 
93c13aa
fedc748
 
 
93c13aa
 
 
 
fedc748
 
 
93c13aa
 
 
 
 
 
 
6dd83fb
 
93c13aa
 
 
fedc748
 
 
7b8de78
 
93c13aa
7b8de78
93c13aa
7b8de78
93c13aa
5b9de09
 
 
 
 
 
 
 
 
 
 
9719306
5b9de09
 
 
 
 
93c13aa
 
fedc748
 
 
1805f08
93c13aa
 
5b9de09
93c13aa
 
 
 
 
 
 
 
fedc748
 
 
93c13aa
 
 
 
 
81741bc
1805f08
81741bc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a360cd7
44e77dc
 
a360cd7
 
 
 
 
 
 
44e77dc
a098d08
e470ee1
44e77dc
a360cd7
 
 
 
 
e470ee1
a360cd7
44e77dc
a098d08
81741bc
a098d08
 
1805f08
81741bc
 
 
 
 
 
 
 
 
 
 
 
 
da19fa1
81741bc
 
17d9a06
81741bc
 
51bde97
 
 
 
 
 
 
 
 
 
 
a098d08
51bde97
 
 
a098d08
51bde97
 
 
 
a360cd7
a098d08
 
 
51bde97
 
 
 
 
 
c330fa6
51bde97
5e8eb62
51bde97
2bf30d8
1533c4b
2c963cc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2bf30d8
 
 
 
2c963cc
2bf30d8
 
44155bc
 
 
 
 
ab879ca
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
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
import markdown, mdtex2html, threading, importlib, traceback, importlib, inspect, re
from show_math import convert as convert_math
from functools import wraps, lru_cache

def get_reduce_token_percent(text):
    try:
        # text = "maximum context length is 4097 tokens. However, your messages resulted in 4870 tokens"
        pattern = r"(\d+)\s+tokens\b"
        match = re.findall(pattern, text)
        EXCEED_ALLO = 500 # 稍微留一点余地,否则在回复时会因余量太少出问题
        max_limit = float(match[0]) - EXCEED_ALLO
        current_tokens = float(match[1])
        ratio = max_limit/current_tokens
        assert ratio > 0 and ratio < 1
        return ratio, str(int(current_tokens-max_limit))
    except:
        return 0.5, '不详'

def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], sys_prompt='', long_connection=True):
    """
        调用简单的predict_no_ui接口,但是依然保留了些许界面心跳功能,当对话太长时,会自动采用二分法截断
        i_say: 当前输入
        i_say_show_user: 显示到对话界面上的当前输入,例如,输入整个文件时,你绝对不想把文件的内容都糊到对话界面上
        chatbot: 对话界面句柄
        top_p, temperature: gpt参数
        history: gpt参数 对话历史
        sys_prompt: gpt参数 sys_prompt
        long_connection: 是否采用更稳定的连接方式(推荐)
    """
    import time
    from predict import predict_no_ui, predict_no_ui_long_connection
    from toolbox import get_conf
    TIMEOUT_SECONDS, MAX_RETRY = get_conf('TIMEOUT_SECONDS', 'MAX_RETRY')
    # 多线程的时候,需要一个mutable结构在不同线程之间传递信息
    # list就是最简单的mutable结构,我们第一个位置放gpt输出,第二个位置传递报错信息
    mutable = [None, '']
    # multi-threading worker
    def mt(i_say, history):
        while True:
            try:
                if long_connection:
                    mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
                else:
                    mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
                break
            except ConnectionAbortedError as token_exceeded_error:
                # 尝试计算比例,尽可能多地保留文本
                p_ratio, n_exceed = get_reduce_token_percent(str(token_exceeded_error))
                if len(history) > 0:
                    history = [his[     int(len(his)    *p_ratio):      ] for his in history if his is not None]
                else:
                    i_say = i_say[:     int(len(i_say)  *p_ratio)     ]
                mutable[1] = f'警告,文本过长将进行截断,Token溢出数:{n_exceed},截断比例:{(1-p_ratio):.0%}。'
            except TimeoutError as e:
                mutable[0] = '[Local Message] 请求超时。'
                raise TimeoutError
            except Exception as e:
                mutable[0] = f'[Local Message] 异常:{str(e)}.'
                raise RuntimeError(f'[Local Message] 异常:{str(e)}.')
    # 创建新线程发出http请求
    thread_name = threading.Thread(target=mt, args=(i_say, history)); thread_name.start()
    # 原来的线程则负责持续更新UI,实现一个超时倒计时,并等待新线程的任务完成
    cnt = 0
    while thread_name.is_alive():
        cnt += 1
        chatbot[-1] = (i_say_show_user, f"[Local Message] {mutable[1]}waiting gpt response {cnt}/{TIMEOUT_SECONDS*2*(MAX_RETRY+1)}"+''.join(['.']*(cnt%4)))
        yield chatbot, history, '正常'
        time.sleep(1)
    # 把gpt的输出从mutable中取出来
    gpt_say = mutable[0]
    if gpt_say=='[Local Message] Failed with timeout.': raise TimeoutError
    return gpt_say

def write_results_to_file(history, file_name=None):
    """
        将对话记录history以Markdown格式写入文件中。如果没有指定文件名,则使用当前时间生成文件名。
    """
    import os, time
    if file_name is None:
        # file_name = time.strftime("chatGPT分析报告%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
        file_name = 'chatGPT分析报告' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
    os.makedirs('./gpt_log/', exist_ok=True)
    with open(f'./gpt_log/{file_name}', 'w', encoding = 'utf8') as f:
        f.write('# chatGPT 分析报告\n')
        for i, content in enumerate(history):
            try:    # 这个bug没找到触发条件,暂时先这样顶一下
                if type(content) != str: content = str(content)
            except:
                continue
            if i%2==0: f.write('## ')
            f.write(content)
            f.write('\n\n')
    res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}')
    print(res)
    return res

def regular_txt_to_markdown(text):
    """
        将普通文本转换为Markdown格式的文本。
    """
    text = text.replace('\n', '\n\n')
    text = text.replace('\n\n\n', '\n\n')
    text = text.replace('\n\n\n', '\n\n')
    return text

def CatchException(f):
    """
        装饰器函数,捕捉函数f中的异常并封装到一个生成器中返回,并显示到聊天当中。
    """
    @wraps(f)
    def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
        try:
            yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
        except Exception as e:
            from check_proxy import check_proxy
            from toolbox import get_conf
            proxies, = get_conf('proxies')
            tb_str = '```\n' + traceback.format_exc() + '```'
            if len(chatbot) == 0: chatbot.append(["插件调度异常","异常原因"])
            chatbot[-1] = (chatbot[-1][0], f"[Local Message] 实验性函数调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
            yield chatbot, history, f'异常 {e}'
    return decorated

def HotReload(f):
    """
        装饰器函数,实现函数插件热更新
    """
    @wraps(f)
    def decorated(*args, **kwargs):
        fn_name = f.__name__
        f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name)
        yield from f_hot_reload(*args, **kwargs)
    return decorated

def report_execption(chatbot, history, a, b):
    """
        向chatbot中添加错误信息
    """
    chatbot.append((a, b))
    history.append(a); history.append(b)

def text_divide_paragraph(text):
    """
        将文本按照段落分隔符分割开,生成带有段落标签的HTML代码。
    """
    if '```' in text:
        # careful input
        return text
    else:
        # wtf input
        lines = text.split("\n")
        for i, line in enumerate(lines):
            lines[i] = lines[i].replace(" ", "&nbsp;")
        text = "</br>".join(lines)
        return text

def markdown_convertion(txt):
    """
        将Markdown格式的文本转换为HTML格式。如果包含数学公式,则先将公式转换为HTML格式。
    """
    pre = '<div class="markdown-body">'
    suf = '</div>'
    if ('$' in txt) and ('```' not in txt):
        return pre + markdown.markdown(txt,extensions=['fenced_code','tables']) + '<br><br>' + markdown.markdown(convert_math(txt, splitParagraphs=False),extensions=['fenced_code','tables']) + suf
    else:
        return pre + markdown.markdown(txt,extensions=['fenced_code','tables']) + suf

def close_up_code_segment_during_stream(gpt_reply):
    """
        在gpt输出代码的中途(输出了前面的```,但还没输出完后面的```),补上后面的```
    """
    if '```' not in gpt_reply: return gpt_reply
    if gpt_reply.endswith('```'): return gpt_reply

    # 排除了以上两个情况,我们
    segments = gpt_reply.split('```')
    n_mark = len(segments) - 1
    if n_mark % 2 == 1:
        # print('输出代码片段中!')
        return gpt_reply+'\n```'
    else:
        return gpt_reply
 


def format_io(self, y):
    """
        将输入和输出解析为HTML格式。将y中最后一项的输入部分段落化,并将输出部分的Markdown和数学公式转换为HTML格式。
    """
    if y is None or y == []: return []
    i_ask, gpt_reply = y[-1]
    i_ask = text_divide_paragraph(i_ask) # 输入部分太自由,预处理一波
    gpt_reply = close_up_code_segment_during_stream(gpt_reply)  # 当代码输出半截的时候,试着补上后个```
    y[-1] = (
        None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code','tables']),
        None if gpt_reply is None else markdown_convertion(gpt_reply)
    )
    return y


def find_free_port():
    """
        返回当前系统中可用的未使用端口。
    """
    import socket
    from contextlib import closing
    with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:
        s.bind(('', 0))
        s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
        return s.getsockname()[1]


def extract_archive(file_path, dest_dir):
    import zipfile
    import tarfile
    import os
    # Get the file extension of the input file
    file_extension = os.path.splitext(file_path)[1]

    # Extract the archive based on its extension
    if file_extension == '.zip':
        with zipfile.ZipFile(file_path, 'r') as zipobj:
            zipobj.extractall(path=dest_dir)
            print("Successfully extracted zip archive to {}".format(dest_dir))

    elif file_extension in ['.tar', '.gz', '.bz2']:
        with tarfile.open(file_path, 'r:*') as tarobj:
            tarobj.extractall(path=dest_dir)
            print("Successfully extracted tar archive to {}".format(dest_dir))

    # 第三方库,需要预先pip install rarfile
    # 此外,Windows上还需要安装winrar软件,配置其Path环境变量,如"C:\Program Files\WinRAR"才可以
    elif file_extension == '.rar':
        try:
            import rarfile
            with rarfile.RarFile(file_path) as rf:
                rf.extractall(path=dest_dir)
                print("Successfully extracted rar archive to {}".format(dest_dir))
        except:
            print("Rar format requires additional dependencies to install")
            return '\n\n需要安装pip install rarfile来解压rar文件'

    # 第三方库,需要预先pip install py7zr
    elif file_extension == '.7z':
        try:
            import py7zr
            with py7zr.SevenZipFile(file_path, mode='r') as f:
                f.extractall(path=dest_dir)
                print("Successfully extracted 7z archive to {}".format(dest_dir))
        except:
            print("7z format requires additional dependencies to install")
            return '\n\n需要安装pip install py7zr来解压7z文件'
    else:
        return ''
    return ''

def find_recent_files(directory):
    """
        me: find files that is created with in one minutes under a directory with python, write a function
        gpt: here it is!
    """
    import os
    import time
    current_time = time.time()
    one_minute_ago = current_time - 60
    recent_files = []

    for filename in os.listdir(directory):
        file_path = os.path.join(directory, filename)
        if file_path.endswith('.log'): continue
        created_time = os.path.getctime(file_path)
        if created_time >= one_minute_ago:
            if os.path.isdir(file_path): continue
            recent_files.append(file_path)

    return recent_files


def on_file_uploaded(files, chatbot, txt):
    if len(files) == 0: return chatbot, txt
    import shutil, os, time, glob
    from toolbox import extract_archive
    try: shutil.rmtree('./private_upload/')
    except: pass
    time_tag = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
    os.makedirs(f'private_upload/{time_tag}', exist_ok=True)
    err_msg = ''
    for file in files:
        file_origin_name = os.path.basename(file.orig_name)
        shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}')
        err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}',
                        dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract')
    moved_files = [fp for fp in glob.glob('private_upload/**/*', recursive=True)]
    txt = f'private_upload/{time_tag}'
    moved_files_str = '\t\n\n'.join(moved_files)
    chatbot.append(['我上传了文件,请查收',
                    f'[Local Message] 收到以下文件: \n\n{moved_files_str}'+
                    f'\n\n调用路径参数已自动修正到: \n\n{txt}'+
                    f'\n\n现在您点击任意实验功能时,以上文件将被作为输入参数'+err_msg])
    return chatbot, txt


def on_report_generated(files, chatbot):
    from toolbox import find_recent_files
    report_files = find_recent_files('gpt_log')
    if len(report_files) == 0: return files, chatbot
    # files.extend(report_files)
    chatbot.append(['汇总报告如何远程获取?', '汇总报告已经添加到右侧“文件上传区”(可能处于折叠状态),请查收。'])
    return report_files, chatbot

@lru_cache(maxsize=128)
def read_single_conf_with_lru_cache(arg):
    try: r = getattr(importlib.import_module('config_private'), arg)
    except: r = getattr(importlib.import_module('config'), arg)
    # 在读取API_KEY时,检查一下是不是忘了改config
    if arg=='API_KEY':
        # 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
        API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
        if API_MATCH:
            print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
        else:
            assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合,请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
                        "(如果您刚更新过代码,请确保旧版config_private文件中没有遗留任何新增键值)"
    if arg=='proxies':
        if r is None: 
            print('[PROXY] 网络代理状态:未配置。无代理状态下很可能无法访问。建议:检查USE_PROXY选项是否修改。')
        else: 
            print('[PROXY] 网络代理状态:已配置。配置信息如下:', r)
            assert isinstance(r, dict), 'proxies格式错误,请注意proxies选项的格式,不要遗漏括号。'
    return r

def get_conf(*args):
    # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
    res = []
    for arg in args:
        r = read_single_conf_with_lru_cache(arg)
        res.append(r)
    return res

def clear_line_break(txt):
    txt = txt.replace('\n', ' ')
    txt = txt.replace('  ', ' ')
    txt = txt.replace('  ', ' ')
    return txt