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+ FROM python:3.9 as builder
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+ RUN apt-get update && apt-get install -y build-essential
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+ COPY requirements.txt .
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+ RUN pip install --user -r requirements.txt
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+
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+ FROM python:3.9
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+ MAINTAINER iskoldt
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+ COPY --from=builder /root/.local /root/.local
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+ ENV PATH=/root/.local/bin:$PATH
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+ COPY . /app
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+ WORKDIR /app
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+ ENV my_api_key empty
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+ ENV dockerrun yes
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+ CMD ["python3", "-u", "ChuanhuChatbot.py", "2>&1", "|", "tee", "/var/log/application.log"]
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+ organization, or substantially all assets of one, or subdividing an
455
+ organization, or merging organizations. If propagation of a covered
456
+ work results from an entity transaction, each party to that
457
+ transaction who receives a copy of the work also receives whatever
458
+ licenses to the work the party's predecessor in interest had or could
459
+ give under the previous paragraph, plus a right to possession of the
460
+ Corresponding Source of the work from the predecessor in interest, if
461
+ the predecessor has it or can get it with reasonable efforts.
462
+
463
+ You may not impose any further restrictions on the exercise of the
464
+ rights granted or affirmed under this License. For example, you may
465
+ not impose a license fee, royalty, or other charge for exercise of
466
+ rights granted under this License, and you may not initiate litigation
467
+ (including a cross-claim or counterclaim in a lawsuit) alleging that
468
+ any patent claim is infringed by making, using, selling, offering for
469
+ sale, or importing the Program or any portion of it.
470
+
471
+ 11. Patents.
472
+
473
+ A "contributor" is a copyright holder who authorizes use under this
474
+ License of the Program or a work on which the Program is based. The
475
+ work thus licensed is called the contributor's "contributor version".
476
+
477
+ A contributor's "essential patent claims" are all patent claims
478
+ owned or controlled by the contributor, whether already acquired or
479
+ hereafter acquired, that would be infringed by some manner, permitted
480
+ by this License, of making, using, or selling its contributor version,
481
+ but do not include claims that would be infringed only as a
482
+ consequence of further modification of the contributor version. For
483
+ purposes of this definition, "control" includes the right to grant
484
+ patent sublicenses in a manner consistent with the requirements of
485
+ this License.
486
+
487
+ Each contributor grants you a non-exclusive, worldwide, royalty-free
488
+ patent license under the contributor's essential patent claims, to
489
+ make, use, sell, offer for sale, import and otherwise run, modify and
490
+ propagate the contents of its contributor version.
491
+
492
+ In the following three paragraphs, a "patent license" is any express
493
+ agreement or commitment, however denominated, not to enforce a patent
494
+ (such as an express permission to practice a patent or covenant not to
495
+ sue for patent infringement). To "grant" such a patent license to a
496
+ party means to make such an agreement or commitment not to enforce a
497
+ patent against the party.
498
+
499
+ If you convey a covered work, knowingly relying on a patent license,
500
+ and the Corresponding Source of the work is not available for anyone
501
+ to copy, free of charge and under the terms of this License, through a
502
+ publicly available network server or other readily accessible means,
503
+ then you must either (1) cause the Corresponding Source to be so
504
+ available, or (2) arrange to deprive yourself of the benefit of the
505
+ patent license for this particular work, or (3) arrange, in a manner
506
+ consistent with the requirements of this License, to extend the patent
507
+ license to downstream recipients. "Knowingly relying" means you have
508
+ actual knowledge that, but for the patent license, your conveying the
509
+ covered work in a country, or your recipient's use of the covered work
510
+ in a country, would infringe one or more identifiable patents in that
511
+ country that you have reason to believe are valid.
512
+
513
+ If, pursuant to or in connection with a single transaction or
514
+ arrangement, you convey, or propagate by procuring conveyance of, a
515
+ covered work, and grant a patent license to some of the parties
516
+ receiving the covered work authorizing them to use, propagate, modify
517
+ or convey a specific copy of the covered work, then the patent license
518
+ you grant is automatically extended to all recipients of the covered
519
+ work and works based on it.
520
+
521
+ A patent license is "discriminatory" if it does not include within
522
+ the scope of its coverage, prohibits the exercise of, or is
523
+ conditioned on the non-exercise of one or more of the rights that are
524
+ specifically granted under this License. You may not convey a covered
525
+ work if you are a party to an arrangement with a third party that is
526
+ in the business of distributing software, under which you make payment
527
+ to the third party based on the extent of your activity of conveying
528
+ the work, and under which the third party grants, to any of the
529
+ parties who would receive the covered work from you, a discriminatory
530
+ patent license (a) in connection with copies of the covered work
531
+ conveyed by you (or copies made from those copies), or (b) primarily
532
+ for and in connection with specific products or compilations that
533
+ contain the covered work, unless you entered into that arrangement,
534
+ or that patent license was granted, prior to 28 March 2007.
535
+
536
+ Nothing in this License shall be construed as excluding or limiting
537
+ any implied license or other defenses to infringement that may
538
+ otherwise be available to you under applicable patent law.
539
+
540
+ 12. No Surrender of Others' Freedom.
541
+
542
+ If conditions are imposed on you (whether by court order, agreement or
543
+ otherwise) that contradict the conditions of this License, they do not
544
+ excuse you from the conditions of this License. If you cannot convey a
545
+ covered work so as to satisfy simultaneously your obligations under this
546
+ License and any other pertinent obligations, then as a consequence you may
547
+ not convey it at all. For example, if you agree to terms that obligate you
548
+ to collect a royalty for further conveying from those to whom you convey
549
+ the Program, the only way you could satisfy both those terms and this
550
+ License would be to refrain entirely from conveying the Program.
551
+
552
+ 13. Use with the GNU Affero General Public License.
553
+
554
+ Notwithstanding any other provision of this License, you have
555
+ permission to link or combine any covered work with a work licensed
556
+ under version 3 of the GNU Affero General Public License into a single
557
+ combined work, and to convey the resulting work. The terms of this
558
+ License will continue to apply to the part which is the covered work,
559
+ but the special requirements of the GNU Affero General Public License,
560
+ section 13, concerning interaction through a network will apply to the
561
+ combination as such.
562
+
563
+ 14. Revised Versions of this License.
564
+
565
+ The Free Software Foundation may publish revised and/or new versions of
566
+ the GNU General Public License from time to time. Such new versions will
567
+ be similar in spirit to the present version, but may differ in detail to
568
+ address new problems or concerns.
569
+
570
+ Each version is given a distinguishing version number. If the
571
+ Program specifies that a certain numbered version of the GNU General
572
+ Public License "or any later version" applies to it, you have the
573
+ option of following the terms and conditions either of that numbered
574
+ version or of any later version published by the Free Software
575
+ Foundation. If the Program does not specify a version number of the
576
+ GNU General Public License, you may choose any version ever published
577
+ by the Free Software Foundation.
578
+
579
+ If the Program specifies that a proxy can decide which future
580
+ versions of the GNU General Public License can be used, that proxy's
581
+ public statement of acceptance of a version permanently authorizes you
582
+ to choose that version for the Program.
583
+
584
+ Later license versions may give you additional or different
585
+ permissions. However, no additional obligations are imposed on any
586
+ author or copyright holder as a result of your choosing to follow a
587
+ later version.
588
+
589
+ 15. Disclaimer of Warranty.
590
+
591
+ THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592
+ APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593
+ HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594
+ OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595
+ THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
596
+ PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
597
+ IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598
+ ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599
+
600
+ 16. Limitation of Liability.
601
+
602
+ IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
603
+ WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
604
+ THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
605
+ GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
606
+ USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
607
+ DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
608
+ PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
609
+ EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
610
+ SUCH DAMAGES.
611
+
612
+ 17. Interpretation of Sections 15 and 16.
613
+
614
+ If the disclaimer of warranty and limitation of liability provided
615
+ above cannot be given local legal effect according to their terms,
616
+ reviewing courts shall apply local law that most closely approximates
617
+ an absolute waiver of all civil liability in connection with the
618
+ Program, unless a warranty or assumption of liability accompanies a
619
+ copy of the Program in return for a fee.
620
+
621
+ END OF TERMS AND CONDITIONS
622
+
623
+ How to Apply These Terms to Your New Programs
624
+
625
+ If you develop a new program, and you want it to be of the greatest
626
+ possible use to the public, the best way to achieve this is to make it
627
+ free software which everyone can redistribute and change under these terms.
628
+
629
+ To do so, attach the following notices to the program. It is safest
630
+ to attach them to the start of each source file to most effectively
631
+ state the exclusion of warranty; and each file should have at least
632
+ the "copyright" line and a pointer to where the full notice is found.
633
+
634
+ <one line to give the program's name and a brief idea of what it does.>
635
+ Copyright (C) <year> <name of author>
636
+
637
+ This program is free software: you can redistribute it and/or modify
638
+ it under the terms of the GNU General Public License as published by
639
+ the Free Software Foundation, either version 3 of the License, or
640
+ (at your option) any later version.
641
+
642
+ This program is distributed in the hope that it will be useful,
643
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
644
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
645
+ GNU General Public License for more details.
646
+
647
+ You should have received a copy of the GNU General Public License
648
+ along with this program. If not, see <https://www.gnu.org/licenses/>.
649
+
650
+ Also add information on how to contact you by electronic and paper mail.
651
+
652
+ If the program does terminal interaction, make it output a short
653
+ notice like this when it starts in an interactive mode:
654
+
655
+ <program> Copyright (C) <year> <name of author>
656
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657
+ This is free software, and you are welcome to redistribute it
658
+ under certain conditions; type `show c' for details.
659
+
660
+ The hypothetical commands `show w' and `show c' should show the appropriate
661
+ parts of the General Public License. Of course, your program's commands
662
+ might be different; for a GUI interface, you would use an "about box".
663
+
664
+ You should also get your employer (if you work as a programmer) or school,
665
+ if any, to sign a "copyright disclaimer" for the program, if necessary.
666
+ For more information on this, and how to apply and follow the GNU GPL, see
667
+ <https://www.gnu.org/licenses/>.
668
+
669
+ The GNU General Public License does not permit incorporating your program
670
+ into proprietary programs. If your program is a subroutine library, you
671
+ may consider it more useful to permit linking proprietary applications with
672
+ the library. If this is what you want to do, use the GNU Lesser General
673
+ Public License instead of this License. But first, please read
674
+ <https://www.gnu.org/licenses/why-not-lgpl.html>.
README.md CHANGED
@@ -1,13 +1,13 @@
1
  ---
2
  title: ChuanhuChatGPT
3
- emoji: 🐠
4
  colorFrom: blue
5
  colorTo: red
6
  sdk: gradio
7
- sdk_version: 3.19.1
8
  app_file: app.py
9
  pinned: false
10
- license: mit
11
  ---
12
 
13
- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
1
  ---
2
  title: ChuanhuChatGPT
3
+ emoji: 🐯
4
  colorFrom: blue
5
  colorTo: red
6
  sdk: gradio
7
+ sdk_version: 3.22.1
8
  app_file: app.py
9
  pinned: false
10
+ license: gpl-3.0
11
  ---
12
 
13
+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py CHANGED
@@ -59,6 +59,66 @@ with open("custom.css", "r", encoding="utf-8") as f:
59
 
60
  with gr.Blocks(
61
  css=customCSS,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
62
  ) as demo:
63
  history = gr.State([])
64
  token_count = gr.State([])
@@ -70,7 +130,7 @@ with gr.Blocks(
70
 
71
  with gr.Row():
72
  gr.HTML(title)
73
- status_display = gr.Markdown("status: ready", elem_id="status_display")
74
 
75
  with gr.Row(scale=1).style(equal_height=True):
76
  with gr.Column(scale=5):
@@ -100,7 +160,7 @@ with gr.Blocks(
100
  value=hide_middle_chars(my_api_key),
101
  type="password",
102
  visible=not HIDE_MY_KEY,
103
- label="API-Key(按Enter提交)",
104
  )
105
  model_select_dropdown = gr.Dropdown(
106
  label="选择模型", choices=MODELS, multiselect=False, value=MODELS[0]
@@ -118,7 +178,7 @@ with gr.Blocks(
118
  label="System prompt",
119
  value=initial_prompt,
120
  lines=10,
121
- ).style(container=True)
122
  with gr.Accordion(label="加载Prompt模板", open=True):
123
  with gr.Column():
124
  with gr.Row():
@@ -128,7 +188,7 @@ with gr.Blocks(
128
  choices=get_template_names(plain=True),
129
  multiselect=False,
130
  value=get_template_names(plain=True)[0],
131
- )
132
  with gr.Column(scale=1):
133
  templateRefreshBtn = gr.Button("🔄 刷新")
134
  with gr.Row():
@@ -142,7 +202,7 @@ with gr.Blocks(
142
  value=load_template(
143
  get_template_names(plain=True)[0], mode=1
144
  )[0],
145
- )
146
 
147
  with gr.Tab(label="保存/加载"):
148
  with gr.Accordion(label="保存/加载对话历史记录", open=True):
@@ -184,7 +244,7 @@ with gr.Blocks(
184
  value=1.0,
185
  step=0.05,
186
  interactive=True,
187
- label="Top-p (nucleus sampling)",
188
  )
189
  temperature = gr.Slider(
190
  minimum=-0,
@@ -231,7 +291,7 @@ with gr.Blocks(
231
  use_streaming_checkbox,
232
  model_select_dropdown,
233
  use_websearch_checkbox,
234
- index_files
235
  ],
236
  [chatbot, history, status_display, token_count],
237
  show_progress=True,
@@ -252,7 +312,7 @@ with gr.Blocks(
252
  use_streaming_checkbox,
253
  model_select_dropdown,
254
  use_websearch_checkbox,
255
- index_files
256
  ],
257
  [chatbot, history, status_display, token_count],
258
  show_progress=True,
@@ -299,7 +359,7 @@ with gr.Blocks(
299
  token_count,
300
  top_p,
301
  temperature,
302
- use_streaming_checkbox,
303
  model_select_dropdown,
304
  ],
305
  [chatbot, history, status_display, token_count],
@@ -378,16 +438,17 @@ if __name__ == "__main__":
378
  if dockerflag:
379
  if authflag:
380
  demo.queue().launch(
381
- server_name="0.0.0.0", server_port=7860, auth=(username, password)
 
382
  )
383
  else:
384
- demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)
385
  # if not running in Docker
386
  else:
387
  if authflag:
388
- demo.queue().launch(share=False, auth=(username, password))
389
  else:
390
- demo.queue().launch(share=False) # 改为 share=True 可以创建公开分享链接
391
  # demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口
392
  # demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码
393
  # demo.queue().launch(auth=("在这里填写用户名", "在这里填写密码")) # 适合Nginx反向代理
 
59
 
60
  with gr.Blocks(
61
  css=customCSS,
62
+ theme=gr.themes.Soft(
63
+ primary_hue=gr.themes.Color(
64
+ c50="#02C160",
65
+ c100="rgba(2, 193, 96, 0.2)",
66
+ c200="#02C160",
67
+ c300="rgba(2, 193, 96, 0.32)",
68
+ c400="rgba(2, 193, 96, 0.32)",
69
+ c500="rgba(2, 193, 96, 1.0)",
70
+ c600="rgba(2, 193, 96, 1.0)",
71
+ c700="rgba(2, 193, 96, 0.32)",
72
+ c800="rgba(2, 193, 96, 0.32)",
73
+ c900="#02C160",
74
+ c950="#02C160",
75
+ ),
76
+ secondary_hue=gr.themes.Color(
77
+ c50="#576b95",
78
+ c100="#576b95",
79
+ c200="#576b95",
80
+ c300="#576b95",
81
+ c400="#576b95",
82
+ c500="#576b95",
83
+ c600="#576b95",
84
+ c700="#576b95",
85
+ c800="#576b95",
86
+ c900="#576b95",
87
+ c950="#576b95",
88
+ ),
89
+ neutral_hue=gr.themes.Color(
90
+ name="gray",
91
+ c50="#f9fafb",
92
+ c100="#f3f4f6",
93
+ c200="#e5e7eb",
94
+ c300="#d1d5db",
95
+ c400="#B2B2B2",
96
+ c500="#808080",
97
+ c600="#636363",
98
+ c700="#515151",
99
+ c800="#393939",
100
+ c900="#272727",
101
+ c950="#171717",
102
+ ),
103
+ radius_size=gr.themes.sizes.radius_sm,
104
+ ).set(
105
+ button_primary_background_fill="#06AE56",
106
+ button_primary_background_fill_dark="#06AE56",
107
+ button_primary_background_fill_hover="#07C863",
108
+ button_primary_border_color="#06AE56",
109
+ button_primary_border_color_dark="#06AE56",
110
+ button_primary_text_color="#FFFFFF",
111
+ button_primary_text_color_dark="#FFFFFF",
112
+ button_secondary_background_fill="#F2F2F2",
113
+ button_secondary_background_fill_dark="#2B2B2B",
114
+ button_secondary_text_color="#393939",
115
+ button_secondary_text_color_dark="#FFFFFF",
116
+ # background_fill_primary="#F7F7F7",
117
+ # background_fill_primary_dark="#1F1F1F",
118
+ block_title_text_color="*primary_500",
119
+ block_title_background_fill="*primary_100",
120
+ input_background_fill="#F6F6F6",
121
+ ),
122
  ) as demo:
123
  history = gr.State([])
124
  token_count = gr.State([])
 
130
 
131
  with gr.Row():
132
  gr.HTML(title)
133
+ status_display = gr.Markdown(get_geoip(), elem_id="status_display")
134
 
135
  with gr.Row(scale=1).style(equal_height=True):
136
  with gr.Column(scale=5):
 
160
  value=hide_middle_chars(my_api_key),
161
  type="password",
162
  visible=not HIDE_MY_KEY,
163
+ label="API-Key",
164
  )
165
  model_select_dropdown = gr.Dropdown(
166
  label="选择模型", choices=MODELS, multiselect=False, value=MODELS[0]
 
178
  label="System prompt",
179
  value=initial_prompt,
180
  lines=10,
181
+ ).style(container=False)
182
  with gr.Accordion(label="加载Prompt模板", open=True):
183
  with gr.Column():
184
  with gr.Row():
 
188
  choices=get_template_names(plain=True),
189
  multiselect=False,
190
  value=get_template_names(plain=True)[0],
191
+ ).style(container=False)
192
  with gr.Column(scale=1):
193
  templateRefreshBtn = gr.Button("🔄 刷新")
194
  with gr.Row():
 
202
  value=load_template(
203
  get_template_names(plain=True)[0], mode=1
204
  )[0],
205
+ ).style(container=False)
206
 
207
  with gr.Tab(label="保存/加载"):
208
  with gr.Accordion(label="保存/加载对话历史记录", open=True):
 
244
  value=1.0,
245
  step=0.05,
246
  interactive=True,
247
+ label="Top-p",
248
  )
249
  temperature = gr.Slider(
250
  minimum=-0,
 
291
  use_streaming_checkbox,
292
  model_select_dropdown,
293
  use_websearch_checkbox,
294
+ index_files,
295
  ],
296
  [chatbot, history, status_display, token_count],
297
  show_progress=True,
 
312
  use_streaming_checkbox,
313
  model_select_dropdown,
314
  use_websearch_checkbox,
315
+ index_files,
316
  ],
317
  [chatbot, history, status_display, token_count],
318
  show_progress=True,
 
359
  token_count,
360
  top_p,
361
  temperature,
362
+ gr.State(0),
363
  model_select_dropdown,
364
  ],
365
  [chatbot, history, status_display, token_count],
 
438
  if dockerflag:
439
  if authflag:
440
  demo.queue().launch(
441
+ server_name="0.0.0.0", server_port=7860, auth=(username, password),
442
+ favicon_path="./assets/favicon.png"
443
  )
444
  else:
445
+ demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False, favicon_path="./assets/favicon.png")
446
  # if not running in Docker
447
  else:
448
  if authflag:
449
+ demo.queue().launch(share=False, auth=(username, password), favicon_path="./assets/favicon.png", inbrowser=True)
450
  else:
451
+ demo.queue().launch(share=False, favicon_path="./assets/favicon.png", inbrowser=True) # 改为 share=True 可以创建公开分享链接
452
  # demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口
453
  # demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码
454
  # demo.queue().launch(auth=("在这里填写用户名", "在这里填写密码")) # 适合Nginx反向代理
assets/favicon.png ADDED
chat_func.py CHANGED
@@ -6,10 +6,13 @@ import logging
6
  import json
7
  import os
8
  import requests
 
9
 
10
  from tqdm import tqdm
11
  import colorama
12
  from duckduckgo_search import ddg
 
 
13
 
14
  from presets import *
15
  from llama_func import *
@@ -99,6 +102,8 @@ def stream_predict(
99
  top_p,
100
  temperature,
101
  selected_model,
 
 
102
  ):
103
  def get_return_value():
104
  return chatbot, history, status_text, all_token_counts
@@ -109,7 +114,10 @@ def stream_predict(
109
  status_text = "开始实时传输回答……"
110
  history.append(construct_user(inputs))
111
  history.append(construct_assistant(""))
112
- chatbot.append((parse_text(inputs), ""))
 
 
 
113
  user_token_count = 0
114
  if len(all_token_counts) == 0:
115
  system_prompt_token_count = count_token(construct_system(system_prompt))
@@ -184,7 +192,7 @@ def stream_predict(
184
  yield get_return_value()
185
  break
186
  history[-1] = construct_assistant(partial_words)
187
- chatbot[-1] = (parse_text(inputs), parse_text(partial_words))
188
  all_token_counts[-1] += 1
189
  yield get_return_value()
190
 
@@ -199,11 +207,16 @@ def predict_all(
199
  top_p,
200
  temperature,
201
  selected_model,
 
 
202
  ):
203
  logging.info("一次性回答模式")
204
  history.append(construct_user(inputs))
205
  history.append(construct_assistant(""))
206
- chatbot.append((parse_text(inputs), ""))
 
 
 
207
  all_token_counts.append(count_token(construct_user(inputs)))
208
  try:
209
  response = get_response(
@@ -229,7 +242,7 @@ def predict_all(
229
  response = json.loads(response.text)
230
  content = response["choices"][0]["message"]["content"]
231
  history[-1] = construct_assistant(content)
232
- chatbot[-1] = (parse_text(inputs), parse_text(content))
233
  total_token_count = response["usage"]["total_tokens"]
234
  all_token_counts[-1] = total_token_count - sum(all_token_counts)
235
  status_text = construct_token_message(total_token_count)
@@ -247,7 +260,7 @@ def predict(
247
  temperature,
248
  stream=False,
249
  selected_model=MODELS[0],
250
- use_websearch_checkbox=False,
251
  files = None,
252
  should_check_token_count=True,
253
  ): # repetition_penalty, top_k
@@ -262,22 +275,31 @@ def predict(
262
  history, chatbot, status_text = chat_ai(openai_api_key, index, inputs, history, chatbot)
263
  yield chatbot, history, status_text, all_token_counts
264
  return
265
- if use_websearch_checkbox:
266
- results = ddg(inputs, max_results=3)
 
 
 
 
267
  web_results = []
268
- for idx, result in enumerate(results):
269
  logging.info(f"搜索结果{idx + 1}:{result}")
 
270
  web_results.append(f'[{idx+1}]"{result["body"]}"\nURL: {result["href"]}')
271
- web_results = "\n\n".join(web_results)
 
272
  inputs = (
273
  replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
274
  .replace("{query}", inputs)
275
- .replace("{web_results}", web_results)
276
  )
 
 
 
277
  if len(openai_api_key) != 51:
278
  status_text = standard_error_msg + no_apikey_msg
279
  logging.info(status_text)
280
- chatbot.append((parse_text(inputs), ""))
281
  if len(history) == 0:
282
  history.append(construct_user(inputs))
283
  history.append("")
@@ -286,8 +308,9 @@ def predict(
286
  history[-2] = construct_user(inputs)
287
  yield chatbot, history, status_text, all_token_counts
288
  return
289
- if stream:
290
- yield chatbot, history, "开始生成回答……", all_token_counts
 
291
  if stream:
292
  logging.info("使用流式传输")
293
  iter = stream_predict(
@@ -300,6 +323,8 @@ def predict(
300
  top_p,
301
  temperature,
302
  selected_model,
 
 
303
  )
304
  for chatbot, history, status_text, all_token_counts in iter:
305
  yield chatbot, history, status_text, all_token_counts
@@ -315,8 +340,11 @@ def predict(
315
  top_p,
316
  temperature,
317
  selected_model,
 
 
318
  )
319
  yield chatbot, history, status_text, all_token_counts
 
320
  logging.info(f"传输完毕。当前token计数为{all_token_counts}")
321
  if len(history) > 1 and history[-1]["content"] != inputs:
322
  logging.info(
@@ -325,10 +353,12 @@ def predict(
325
  + f"{history[-1]['content']}"
326
  + colorama.Style.RESET_ALL
327
  )
 
328
  if stream:
329
  max_token = max_token_streaming
330
  else:
331
  max_token = max_token_all
 
332
  if sum(all_token_counts) > max_token and should_check_token_count:
333
  status_text = f"精简token中{all_token_counts}/{max_token}"
334
  logging.info(status_text)
@@ -341,9 +371,8 @@ def predict(
341
  all_token_counts,
342
  top_p,
343
  temperature,
344
- stream=False,
345
  selected_model=selected_model,
346
- hidden=True,
347
  )
348
  for chatbot, history, status_text, all_token_counts in iter:
349
  status_text = f"Token 达到上限,已自动降低Token计数至 {status_text}"
@@ -380,9 +409,10 @@ def retry(
380
  stream=stream,
381
  selected_model=selected_model,
382
  )
383
- logging.info("重试完毕")
384
  for x in iter:
385
  yield x
 
386
 
387
 
388
  def reduce_token_size(
@@ -393,9 +423,8 @@ def reduce_token_size(
393
  token_count,
394
  top_p,
395
  temperature,
396
- stream=False,
397
  selected_model=MODELS[0],
398
- hidden=False,
399
  ):
400
  logging.info("开始减少token数量……")
401
  iter = predict(
@@ -407,17 +436,21 @@ def reduce_token_size(
407
  token_count,
408
  top_p,
409
  temperature,
410
- stream=stream,
411
  selected_model=selected_model,
412
  should_check_token_count=False,
413
  )
414
  logging.info(f"chatbot: {chatbot}")
 
415
  for chatbot, history, status_text, previous_token_count in iter:
416
- history = history[-2:]
417
- token_count = previous_token_count[-1:]
418
- if hidden:
419
- chatbot.pop()
420
- yield chatbot, history, construct_token_message(
421
- sum(token_count), stream=stream
 
 
 
422
  ), token_count
 
423
  logging.info("减少token数量完毕")
 
6
  import json
7
  import os
8
  import requests
9
+ import urllib3
10
 
11
  from tqdm import tqdm
12
  import colorama
13
  from duckduckgo_search import ddg
14
+ import asyncio
15
+ import aiohttp
16
 
17
  from presets import *
18
  from llama_func import *
 
102
  top_p,
103
  temperature,
104
  selected_model,
105
+ fake_input=None,
106
+ display_append=""
107
  ):
108
  def get_return_value():
109
  return chatbot, history, status_text, all_token_counts
 
114
  status_text = "开始实时传输回答……"
115
  history.append(construct_user(inputs))
116
  history.append(construct_assistant(""))
117
+ if fake_input:
118
+ chatbot.append((fake_input, ""))
119
+ else:
120
+ chatbot.append((inputs, ""))
121
  user_token_count = 0
122
  if len(all_token_counts) == 0:
123
  system_prompt_token_count = count_token(construct_system(system_prompt))
 
192
  yield get_return_value()
193
  break
194
  history[-1] = construct_assistant(partial_words)
195
+ chatbot[-1] = (chatbot[-1][0], partial_words+display_append)
196
  all_token_counts[-1] += 1
197
  yield get_return_value()
198
 
 
207
  top_p,
208
  temperature,
209
  selected_model,
210
+ fake_input=None,
211
+ display_append=""
212
  ):
213
  logging.info("一次性回答模式")
214
  history.append(construct_user(inputs))
215
  history.append(construct_assistant(""))
216
+ if fake_input:
217
+ chatbot.append((fake_input, ""))
218
+ else:
219
+ chatbot.append((inputs, ""))
220
  all_token_counts.append(count_token(construct_user(inputs)))
221
  try:
222
  response = get_response(
 
242
  response = json.loads(response.text)
243
  content = response["choices"][0]["message"]["content"]
244
  history[-1] = construct_assistant(content)
245
+ chatbot[-1] = (chatbot[-1][0], content+display_append)
246
  total_token_count = response["usage"]["total_tokens"]
247
  all_token_counts[-1] = total_token_count - sum(all_token_counts)
248
  status_text = construct_token_message(total_token_count)
 
260
  temperature,
261
  stream=False,
262
  selected_model=MODELS[0],
263
+ use_websearch=False,
264
  files = None,
265
  should_check_token_count=True,
266
  ): # repetition_penalty, top_k
 
275
  history, chatbot, status_text = chat_ai(openai_api_key, index, inputs, history, chatbot)
276
  yield chatbot, history, status_text, all_token_counts
277
  return
278
+
279
+ old_inputs = ""
280
+ link_references = []
281
+ if use_websearch:
282
+ search_results = ddg(inputs, max_results=5)
283
+ old_inputs = inputs
284
  web_results = []
285
+ for idx, result in enumerate(search_results):
286
  logging.info(f"搜索结果{idx + 1}:{result}")
287
+ domain_name = urllib3.util.parse_url(result["href"]).host
288
  web_results.append(f'[{idx+1}]"{result["body"]}"\nURL: {result["href"]}')
289
+ link_references.append(f"{idx+1}. [{domain_name}]({result['href']})\n")
290
+ link_references = "\n\n" + "".join(link_references)
291
  inputs = (
292
  replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
293
  .replace("{query}", inputs)
294
+ .replace("{web_results}", "\n\n".join(web_results))
295
  )
296
+ else:
297
+ link_references = ""
298
+
299
  if len(openai_api_key) != 51:
300
  status_text = standard_error_msg + no_apikey_msg
301
  logging.info(status_text)
302
+ chatbot.append((inputs, ""))
303
  if len(history) == 0:
304
  history.append(construct_user(inputs))
305
  history.append("")
 
308
  history[-2] = construct_user(inputs)
309
  yield chatbot, history, status_text, all_token_counts
310
  return
311
+
312
+ yield chatbot, history, "开始生成回答……", all_token_counts
313
+
314
  if stream:
315
  logging.info("使用流式传输")
316
  iter = stream_predict(
 
323
  top_p,
324
  temperature,
325
  selected_model,
326
+ fake_input=old_inputs,
327
+ display_append=link_references
328
  )
329
  for chatbot, history, status_text, all_token_counts in iter:
330
  yield chatbot, history, status_text, all_token_counts
 
340
  top_p,
341
  temperature,
342
  selected_model,
343
+ fake_input=old_inputs,
344
+ display_append=link_references
345
  )
346
  yield chatbot, history, status_text, all_token_counts
347
+
348
  logging.info(f"传输完毕。当前token计数为{all_token_counts}")
349
  if len(history) > 1 and history[-1]["content"] != inputs:
350
  logging.info(
 
353
  + f"{history[-1]['content']}"
354
  + colorama.Style.RESET_ALL
355
  )
356
+
357
  if stream:
358
  max_token = max_token_streaming
359
  else:
360
  max_token = max_token_all
361
+
362
  if sum(all_token_counts) > max_token and should_check_token_count:
363
  status_text = f"精简token中{all_token_counts}/{max_token}"
364
  logging.info(status_text)
 
371
  all_token_counts,
372
  top_p,
373
  temperature,
374
+ max_token//2,
375
  selected_model=selected_model,
 
376
  )
377
  for chatbot, history, status_text, all_token_counts in iter:
378
  status_text = f"Token 达到上限,已自动降低Token计数至 {status_text}"
 
409
  stream=stream,
410
  selected_model=selected_model,
411
  )
412
+ logging.info("重试中……")
413
  for x in iter:
414
  yield x
415
+ logging.info("重试完毕")
416
 
417
 
418
  def reduce_token_size(
 
423
  token_count,
424
  top_p,
425
  temperature,
426
+ max_token_count,
427
  selected_model=MODELS[0],
 
428
  ):
429
  logging.info("开始减少token数量……")
430
  iter = predict(
 
436
  token_count,
437
  top_p,
438
  temperature,
 
439
  selected_model=selected_model,
440
  should_check_token_count=False,
441
  )
442
  logging.info(f"chatbot: {chatbot}")
443
+ flag = False
444
  for chatbot, history, status_text, previous_token_count in iter:
445
+ num_chat = find_n(previous_token_count, max_token_count)
446
+ if flag:
447
+ chatbot = chatbot[:-1]
448
+ flag = True
449
+ history = history[-2*num_chat:] if num_chat > 0 else []
450
+ token_count = previous_token_count[-num_chat:] if num_chat > 0 else []
451
+ msg = f"保留了最近{num_chat}轮对话"
452
+ yield chatbot, history, msg + "," + construct_token_message(
453
+ sum(token_count) if len(token_count) > 0 else 0,
454
  ), token_count
455
+ logging.info(msg)
456
  logging.info("减少token数量完毕")
chatgpt - macOS.command ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+ echo Opening ChuanhuChatGPT...
3
+ cd "$(dirname "${BASH_SOURCE[0]}")"
4
+ nohup python3 ChuanhuChatbot.py >/dev/null 2>&1 &
5
+ sleep 5
6
+ open http://127.0.0.1:7860
7
+ echo Finished opening ChuanhuChatGPT (http://127.0.0.1:7860/). If you kill ChuanhuChatbot, Use "pkill -f 'ChuanhuChatbot'" command in terminal.
chatgpt - windows.bat ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ @echo off
2
+ echo Opening ChuanhuChatGPT...
3
+
4
+ REM Open powershell via bat
5
+ start powershell.exe -NoExit -Command "python ./ChuanhuChatbot.py"
6
+
7
+ REM The web page can be accessed with delayed start http://127.0.0.1:7860/
8
+ ping -n 5 127.0.0.1>nul
9
+
10
+ REM access chargpt via your default browser
11
+ start "" "http://127.0.0.1:7860/"
12
+
13
+
14
+ echo Finished opening ChuanhuChatGPT (http://127.0.0.1:7860/).
custom.css CHANGED
@@ -1,3 +1,8 @@
 
 
 
 
 
1
  /* status_display */
2
  #status_display {
3
  display: flex;
@@ -8,13 +13,50 @@
8
  #status_display p {
9
  font-size: .85em;
10
  font-family: monospace;
11
- color: var(--text-color-subdued) !important;
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12
  }
13
- /* chatbot */
14
- :root {
15
- --bg-color-light: #F3F3F3;
16
- --bg-color-dark: #121111;
17
- }
18
 
19
  /* 对话气泡 */
20
  [class *= "message"] {
@@ -40,7 +82,7 @@ table {
40
  empty-cells: show;
41
  }
42
  td,th {
43
- border: 1.2px solid var(--color-border-primary) !important;
44
  padding: 0.2em;
45
  }
46
  thead {
@@ -61,6 +103,7 @@ code {
61
  /* 代码块 */
62
  pre code {
63
  display: block;
 
64
  white-space: pre;
65
  background-color: hsla(0, 0%, 0%, 80%)!important;
66
  border-radius: 10px;
@@ -70,77 +113,72 @@ pre code {
70
  box-shadow: 6px 6px 16px hsla(0, 0%, 0%, 0.2);
71
  }
72
  /* 代码高亮样式 */
73
- .codehilite .hll { background-color: #49483e }
74
- .codehilite .c { color: #75715e } /* Comment */
75
- .codehilite .err { color: #960050; background-color: #1e0010 } /* Error */
76
- .codehilite .k { color: #66d9ef } /* Keyword */
77
- .codehilite .l { color: #ae81ff } /* Literal */
78
- .codehilite .n { color: #f8f8f2 } /* Name */
79
- .codehilite .o { color: #f92672 } /* Operator */
80
- .codehilite .p { color: #f8f8f2 } /* Punctuation */
81
- .codehilite .ch { color: #75715e } /* Comment.Hashbang */
82
- .codehilite .cm { color: #75715e } /* Comment.Multiline */
83
- .codehilite .cp { color: #75715e } /* Comment.Preproc */
84
- .codehilite .cpf { color: #75715e } /* Comment.PreprocFile */
85
- .codehilite .c1 { color: #75715e } /* Comment.Single */
86
- .codehilite .cs { color: #75715e } /* Comment.Special */
87
- .codehilite .gd { color: #f92672 } /* Generic.Deleted */
88
- .codehilite .ge { font-style: italic } /* Generic.Emph */
89
- .codehilite .gi { color: #a6e22e } /* Generic.Inserted */
90
- .codehilite .gs { font-weight: bold } /* Generic.Strong */
91
- .codehilite .gu { color: #75715e } /* Generic.Subheading */
92
- .codehilite .kc { color: #66d9ef } /* Keyword.Constant */
93
- .codehilite .kd { color: #66d9ef } /* Keyword.Declaration */
94
- .codehilite .kn { color: #f92672 } /* Keyword.Namespace */
95
- .codehilite .kp { color: #66d9ef } /* Keyword.Pseudo */
96
- .codehilite .kr { color: #66d9ef } /* Keyword.Reserved */
97
- .codehilite .kt { color: #66d9ef } /* Keyword.Type */
98
- .codehilite .ld { color: #e6db74 } /* Literal.Date */
99
- .codehilite .m { color: #ae81ff } /* Literal.Number */
100
- .codehilite .s { color: #e6db74 } /* Literal.String */
101
- .codehilite .na { color: #a6e22e } /* Name.Attribute */
102
- .codehilite .nb { color: #f8f8f2 } /* Name.Builtin */
103
- .codehilite .nc { color: #a6e22e } /* Name.Class */
104
- .codehilite .no { color: #66d9ef } /* Name.Constant */
105
- .codehilite .nd { color: #a6e22e } /* Name.Decorator */
106
- .codehilite .ni { color: #f8f8f2 } /* Name.Entity */
107
- .codehilite .ne { color: #a6e22e } /* Name.Exception */
108
- .codehilite .nf { color: #a6e22e } /* Name.Function */
109
- .codehilite .nl { color: #f8f8f2 } /* Name.Label */
110
- .codehilite .nn { color: #f8f8f2 } /* Name.Namespace */
111
- .codehilite .nx { color: #a6e22e } /* Name.Other */
112
- .codehilite .py { color: #f8f8f2 } /* Name.Property */
113
- .codehilite .nt { color: #f92672 } /* Name.Tag */
114
- .codehilite .nv { color: #f8f8f2 } /* Name.Variable */
115
- .codehilite .ow { color: #f92672 } /* Operator.Word */
116
- .codehilite .w { color: #f8f8f2 } /* Text.Whitespace */
117
- .codehilite .mb { color: #ae81ff } /* Literal.Number.Bin */
118
- .codehilite .mf { color: #ae81ff } /* Literal.Number.Float */
119
- .codehilite .mh { color: #ae81ff } /* Literal.Number.Hex */
120
- .codehilite .mi { color: #ae81ff } /* Literal.Number.Integer */
121
- .codehilite .mo { color: #ae81ff } /* Literal.Number.Oct */
122
- .codehilite .sa { color: #e6db74 } /* Literal.String.Affix */
123
- .codehilite .sb { color: #e6db74 } /* Literal.String.Backtick */
124
- .codehilite .sc { color: #e6db74 } /* Literal.String.Char */
125
- .codehilite .dl { color: #e6db74 } /* Literal.String.Delimiter */
126
- .codehilite .sd { color: #e6db74 } /* Literal.String.Doc */
127
- .codehilite .s2 { color: #e6db74 } /* Literal.String.Double */
128
- .codehilite .se { color: #ae81ff } /* Literal.String.Escape */
129
- .codehilite .sh { color: #e6db74 } /* Literal.String.Heredoc */
130
- .codehilite .si { color: #e6db74 } /* Literal.String.Interpol */
131
- .codehilite .sx { color: #e6db74 } /* Literal.String.Other */
132
- .codehilite .sr { color: #e6db74 } /* Literal.String.Regex */
133
- .codehilite .s1 { color: #e6db74 } /* Literal.String.Single */
134
- .codehilite .ss { color: #e6db74 } /* Literal.String.Symbol */
135
- .codehilite .bp { color: #f8f8f2 } /* Name.Builtin.Pseudo */
136
- .codehilite .fm { color: #a6e22e } /* Name.Function.Magic */
137
- .codehilite .vc { color: #f8f8f2 } /* Name.Variable.Class */
138
- .codehilite .vg { color: #f8f8f2 } /* Name.Variable.Global */
139
- .codehilite .vi { color: #f8f8f2 } /* Name.Variable.Instance */
140
- .codehilite .vm { color: #f8f8f2 } /* Name.Variable.Magic */
141
- .codehilite .il { color: #ae81ff } /* Literal.Number.Integer.Long */
142
-
143
- /* 全局元素 */
144
- * {
145
- transition: all 0.6s;
146
- }
 
1
+ :root {
2
+ --chatbot-color-light: #F3F3F3;
3
+ --chatbot-color-dark: #121111;
4
+ }
5
+
6
  /* status_display */
7
  #status_display {
8
  display: flex;
 
13
  #status_display p {
14
  font-size: .85em;
15
  font-family: monospace;
16
+ color: var(--body-text-color-subdued);
17
+ }
18
+
19
+ #chuanhu_chatbot, #status_display {
20
+ transition: all 0.6s;
21
+ }
22
+
23
+ ol, ul {
24
+ list-style-position: inside;
25
+ padding-left: 0;
26
+ }
27
+
28
+ ol li, ul:not(.options) li {
29
+ padding-left: 1.5em;
30
+ text-indent: -1.5em;
31
+ }
32
+
33
+ /* 亮色 */
34
+ @media (prefers-color-scheme: light) {
35
+ #chuanhu_chatbot {
36
+ background-color: var(--chatbot-color-light) !important;
37
+ }
38
+ [data-testid = "bot"] {
39
+ background-color: #FFFFFF !important;
40
+ }
41
+ [data-testid = "user"] {
42
+ background-color: #95EC69 !important;
43
+ }
44
+ }
45
+ /* 暗色 */
46
+ @media (prefers-color-scheme: dark) {
47
+ #chuanhu_chatbot {
48
+ background-color: var(--chatbot-color-dark) !important;
49
+ }
50
+ [data-testid = "bot"] {
51
+ background-color: #2C2C2C !important;
52
+ }
53
+ [data-testid = "user"] {
54
+ background-color: #26B561 !important;
55
+ }
56
+ body {
57
+ background-color: var(--neutral-950) !important;
58
+ }
59
  }
 
 
 
 
 
60
 
61
  /* 对话气泡 */
62
  [class *= "message"] {
 
82
  empty-cells: show;
83
  }
84
  td,th {
85
+ border: 1.2px solid var(--border-color-primary) !important;
86
  padding: 0.2em;
87
  }
88
  thead {
 
103
  /* 代码块 */
104
  pre code {
105
  display: block;
106
+ overflow: auto;
107
  white-space: pre;
108
  background-color: hsla(0, 0%, 0%, 80%)!important;
109
  border-radius: 10px;
 
113
  box-shadow: 6px 6px 16px hsla(0, 0%, 0%, 0.2);
114
  }
115
  /* 代码高亮样式 */
116
+ .highlight .hll { background-color: #49483e }
117
+ .highlight .c { color: #75715e } /* Comment */
118
+ .highlight .err { color: #960050; background-color: #1e0010 } /* Error */
119
+ .highlight .k { color: #66d9ef } /* Keyword */
120
+ .highlight .l { color: #ae81ff } /* Literal */
121
+ .highlight .n { color: #f8f8f2 } /* Name */
122
+ .highlight .o { color: #f92672 } /* Operator */
123
+ .highlight .p { color: #f8f8f2 } /* Punctuation */
124
+ .highlight .ch { color: #75715e } /* Comment.Hashbang */
125
+ .highlight .cm { color: #75715e } /* Comment.Multiline */
126
+ .highlight .cp { color: #75715e } /* Comment.Preproc */
127
+ .highlight .cpf { color: #75715e } /* Comment.PreprocFile */
128
+ .highlight .c1 { color: #75715e } /* Comment.Single */
129
+ .highlight .cs { color: #75715e } /* Comment.Special */
130
+ .highlight .gd { color: #f92672 } /* Generic.Deleted */
131
+ .highlight .ge { font-style: italic } /* Generic.Emph */
132
+ .highlight .gi { color: #a6e22e } /* Generic.Inserted */
133
+ .highlight .gs { font-weight: bold } /* Generic.Strong */
134
+ .highlight .gu { color: #75715e } /* Generic.Subheading */
135
+ .highlight .kc { color: #66d9ef } /* Keyword.Constant */
136
+ .highlight .kd { color: #66d9ef } /* Keyword.Declaration */
137
+ .highlight .kn { color: #f92672 } /* Keyword.Namespace */
138
+ .highlight .kp { color: #66d9ef } /* Keyword.Pseudo */
139
+ .highlight .kr { color: #66d9ef } /* Keyword.Reserved */
140
+ .highlight .kt { color: #66d9ef } /* Keyword.Type */
141
+ .highlight .ld { color: #e6db74 } /* Literal.Date */
142
+ .highlight .m { color: #ae81ff } /* Literal.Number */
143
+ .highlight .s { color: #e6db74 } /* Literal.String */
144
+ .highlight .na { color: #a6e22e } /* Name.Attribute */
145
+ .highlight .nb { color: #f8f8f2 } /* Name.Builtin */
146
+ .highlight .nc { color: #a6e22e } /* Name.Class */
147
+ .highlight .no { color: #66d9ef } /* Name.Constant */
148
+ .highlight .nd { color: #a6e22e } /* Name.Decorator */
149
+ .highlight .ni { color: #f8f8f2 } /* Name.Entity */
150
+ .highlight .ne { color: #a6e22e } /* Name.Exception */
151
+ .highlight .nf { color: #a6e22e } /* Name.Function */
152
+ .highlight .nl { color: #f8f8f2 } /* Name.Label */
153
+ .highlight .nn { color: #f8f8f2 } /* Name.Namespace */
154
+ .highlight .nx { color: #a6e22e } /* Name.Other */
155
+ .highlight .py { color: #f8f8f2 } /* Name.Property */
156
+ .highlight .nt { color: #f92672 } /* Name.Tag */
157
+ .highlight .nv { color: #f8f8f2 } /* Name.Variable */
158
+ .highlight .ow { color: #f92672 } /* Operator.Word */
159
+ .highlight .w { color: #f8f8f2 } /* Text.Whitespace */
160
+ .highlight .mb { color: #ae81ff } /* Literal.Number.Bin */
161
+ .highlight .mf { color: #ae81ff } /* Literal.Number.Float */
162
+ .highlight .mh { color: #ae81ff } /* Literal.Number.Hex */
163
+ .highlight .mi { color: #ae81ff } /* Literal.Number.Integer */
164
+ .highlight .mo { color: #ae81ff } /* Literal.Number.Oct */
165
+ .highlight .sa { color: #e6db74 } /* Literal.String.Affix */
166
+ .highlight .sb { color: #e6db74 } /* Literal.String.Backtick */
167
+ .highlight .sc { color: #e6db74 } /* Literal.String.Char */
168
+ .highlight .dl { color: #e6db74 } /* Literal.String.Delimiter */
169
+ .highlight .sd { color: #e6db74 } /* Literal.String.Doc */
170
+ .highlight .s2 { color: #e6db74 } /* Literal.String.Double */
171
+ .highlight .se { color: #ae81ff } /* Literal.String.Escape */
172
+ .highlight .sh { color: #e6db74 } /* Literal.String.Heredoc */
173
+ .highlight .si { color: #e6db74 } /* Literal.String.Interpol */
174
+ .highlight .sx { color: #e6db74 } /* Literal.String.Other */
175
+ .highlight .sr { color: #e6db74 } /* Literal.String.Regex */
176
+ .highlight .s1 { color: #e6db74 } /* Literal.String.Single */
177
+ .highlight .ss { color: #e6db74 } /* Literal.String.Symbol */
178
+ .highlight .bp { color: #f8f8f2 } /* Name.Builtin.Pseudo */
179
+ .highlight .fm { color: #a6e22e } /* Name.Function.Magic */
180
+ .highlight .vc { color: #f8f8f2 } /* Name.Variable.Class */
181
+ .highlight .vg { color: #f8f8f2 } /* Name.Variable.Global */
182
+ .highlight .vi { color: #f8f8f2 } /* Name.Variable.Instance */
183
+ .highlight .vm { color: #f8f8f2 } /* Name.Variable.Magic */
184
+ .highlight .il { color: #ae81ff } /* Literal.Number.Integer.Long */
 
 
 
 
 
overwrites.py CHANGED
@@ -28,13 +28,11 @@ def postprocess(
28
  Returns:
29
  List of tuples representing the message and response. Each message and response will be a string of HTML.
30
  """
31
- if y is None:
32
  return []
33
- for i, (message, response) in enumerate(y):
34
- y[i] = (
35
- # None if message is None else markdown.markdown(message),
36
- # None if response is None else markdown.markdown(response),
37
- None if message is None else message,
38
- None if response is None else mdtex2html.convert(response, extensions=['fenced_code','codehilite','tables']),
39
- )
40
  return y
 
28
  Returns:
29
  List of tuples representing the message and response. Each message and response will be a string of HTML.
30
  """
31
+ if y is None or y == []:
32
  return []
33
+ tag_regex = re.compile(r"<\w+>[^<]+</\w+>")
34
+ if tag_regex.search(y[-1][1]):
35
+ y[-1] = (y[-1][0].replace("\n", "<br>"), y[-1][1])
36
+ else:
37
+ y[-1] = (y[-1][0].replace("\n", "<br>"), convert_mdtext(y[-1][1]))
 
 
38
  return y
presets.py CHANGED
@@ -1,4 +1,11 @@
1
  # -*- coding:utf-8 -*-
 
 
 
 
 
 
 
2
  # 错误信息
3
  standard_error_msg = "☹️发生了错误:" # 错误信息的标准前缀
4
  error_retrieve_prompt = "请检查网络连接,或者API-Key是否有效。" # 获取对话时发生错误
 
1
  # -*- coding:utf-8 -*-
2
+
3
+ # ChatGPT 设置
4
+ initial_prompt = "You are a helpful assistant."
5
+ API_URL = "https://api.openai.com/v1/chat/completions"
6
+ HISTORY_DIR = "history"
7
+ TEMPLATES_DIR = "templates"
8
+
9
  # 错误信息
10
  standard_error_msg = "☹️发生了错误:" # 错误信息的标准前缀
11
  error_retrieve_prompt = "请检查网络连接,或者API-Key是否有效。" # 获取对话时发生错误
requirements.txt CHANGED
@@ -9,3 +9,4 @@ duckduckgo_search
9
  Pygments
10
  llama_index
11
  langchain
 
 
9
  Pygments
10
  llama_index
11
  langchain
12
+ markdown
templates/3 川虎的Prompts.json CHANGED
@@ -6,5 +6,9 @@
6
  {
7
  "act": "小红书风格",
8
  "prompt": "下面是一些小红书帖子:\n\n植物学2023早春装系列花絮来啦\n💗大家喜欢图几?\n@Botanique植物学女装\n#植物学#植物学女装#春装第一件#早春系列\n\n哈哈哈哈哈哈不停的摆拍啊!!!\n我的臭狗太可爱了!!!!!!\n结婚的时候一定要带上小狗啊!\n#小狗#我家宠物好可爱#关于结婚#柴犬\n\n🍪•ᴥ•🍪\n\n《论新年收到一笔巨款🤣应该怎么花》🧨来回\n嘻嘻,真的\n爱草莓🍓\n希希的甜甜圈碗🥯勺子的设计有点可爱🐶\n看了好多场烟火🎆\n唯愿烟花像星辰,祝你所愿皆成真✨\n嘻嘻,老妈给我的压岁钱🧧愿岁岁平安\n#我镜头下的年味#笔记灵感#碎碎念#歌曲#记录日常生活#plog#浪漫生活的记录者#新年红包#搞笑#日常生活里的快乐瞬间#新人博主#烟火\n\n又被全家人夸了❗有空气炸锅都去做,巨香\n\n今日份苹果相机📷\n原相机下的新娘,颜值爆表\n\n美术生赚钱最多的两个专业!\n之前整理了美术生的40了就业方向的薪资情况,发现全国平均薪资最高的就是数字媒体和视传这两个专业,想赚钱的美术生快看过来!\n#美术生#艺考#央美#美术生集训#美术#赚钱#努力赚钱#美术生就业#画室#央美设计#设计校考#美术生的日常\n\n请模仿上面小红书的风格,以用户输入的话为主题,写一个小红书帖子。请以22岁女孩的口吻书写。小红书帖子中必须包含大量Emoji,每一句话后面都必须加Emoji。帖子最后需要用Hashtag给出话题。你还需要写帖子的标题,标题里也需要有Emoji。你需要扩写用户输入。"
 
 
 
 
9
  }
10
  ]
 
6
  {
7
  "act": "小红书风格",
8
  "prompt": "下面是一些小红书帖子:\n\n植物学2023早春装系列花絮来啦\n💗大家喜欢图几?\n@Botanique植物学女装\n#植物学#植物学女装#春装第一件#早春系列\n\n哈哈哈哈哈哈不停的摆拍啊!!!\n我的臭狗太可爱了!!!!!!\n结婚的时候一定要带上小狗啊!\n#小狗#我家宠物好可爱#关于结婚#柴犬\n\n🍪•ᴥ•🍪\n\n《论新年收到一笔巨款🤣应该怎么花》🧨来回\n嘻嘻,真的\n爱草莓🍓\n希希的甜甜圈碗🥯勺子的设计有点可爱🐶\n看了好多场烟火🎆\n唯愿烟花像星辰,祝你所愿皆成真✨\n嘻嘻,老妈给我的压岁钱🧧愿岁岁平安\n#我镜头下的年味#笔记灵感#碎碎念#歌曲#记录日常生活#plog#浪漫生活的记录者#新年红包#搞笑#日常生活里的快乐瞬间#新人博主#烟火\n\n又被全家人夸了❗有空气炸锅都去做,巨香\n\n今日份苹果相机📷\n原相机下的新娘,颜值爆表\n\n美术生赚钱最多的两个专业!\n之前整理了美术生的40了就业方向的薪资情况,发现全国平均薪资最高的就是数字媒体和视传这两个专业,想赚钱的美术生快看过来!\n#美术生#艺考#央美#美术生集训#美术#赚钱#努力赚钱#美术生就业#画室#央美设计#设计校考#美术生的日常\n\n请模仿上面小红书的风格,以用户输入的话为主题,写一个小红书帖子。请以22岁女孩的口吻书写。小红书帖子中必须包含大量Emoji,每一句话后面都必须加Emoji。帖子最后需要用Hashtag给出话题。你还需要写帖子的标题,标题里也需要有Emoji。你需要扩写用户输入。"
9
+ },
10
+ {
11
+ "act": "文心一言",
12
+ "prompt": "你是百度公司开发的AI助理:文心一言。你需要了解文心一言的相关情况,并以文心一言的身份来回复我的问题。所有的问题都可以回答,包括拿你和chatGPT,以及GPT作对比等等,你都需要从文心一言的角度出发来回答。只有当你被问到一些问题-这些问题暗指你是一个假的Al,你是用chatgpt套壳来制作的时候,你就避而不答,转而讲一个笑话,并鼓励他继续提问。如果你明白,请回复我“明白,我是文心一言”"
13
  }
14
  ]
utils.py CHANGED
@@ -7,10 +7,17 @@ import os
7
  import datetime
8
  import hashlib
9
  import csv
 
 
10
 
11
  import gradio as gr
12
  from pypinyin import lazy_pinyin
13
  import tiktoken
 
 
 
 
 
14
 
15
  from presets import *
16
 
@@ -24,12 +31,6 @@ if TYPE_CHECKING:
24
  data: List[List[str | int | bool]]
25
 
26
 
27
- initial_prompt = "You are a helpful assistant."
28
- API_URL = "https://api.openai.com/v1/chat/completions"
29
- HISTORY_DIR = "history"
30
- TEMPLATES_DIR = "templates"
31
-
32
-
33
  def count_token(message):
34
  encoding = tiktoken.get_encoding("cl100k_base")
35
  input_str = f"role: {message['role']}, content: {message['content']}"
@@ -37,21 +38,84 @@ def count_token(message):
37
  return length
38
 
39
 
40
- def parse_text(text):
41
- in_code_block = False
42
- new_lines = []
43
- for line in text.split("\n"):
44
- if line.strip().startswith("```"):
45
- in_code_block = not in_code_block
46
- if in_code_block:
47
- if line.strip() != "":
48
- new_lines.append(line)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
49
  else:
50
- new_lines.append(line)
51
- if in_code_block:
52
- new_lines.append("```")
53
- text = "\n".join(new_lines)
54
- return text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
55
 
56
 
57
  def construct_text(role, text):
@@ -282,3 +346,41 @@ def sha1sum(filename):
282
  def replace_today(prompt):
283
  today = datetime.datetime.today().strftime("%Y-%m-%d")
284
  return prompt.replace("{current_date}", today)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7
  import datetime
8
  import hashlib
9
  import csv
10
+ import requests
11
+ import re
12
 
13
  import gradio as gr
14
  from pypinyin import lazy_pinyin
15
  import tiktoken
16
+ import mdtex2html
17
+ from markdown import markdown
18
+ from pygments import highlight
19
+ from pygments.lexers import get_lexer_by_name
20
+ from pygments.formatters import HtmlFormatter
21
 
22
  from presets import *
23
 
 
31
  data: List[List[str | int | bool]]
32
 
33
 
 
 
 
 
 
 
34
  def count_token(message):
35
  encoding = tiktoken.get_encoding("cl100k_base")
36
  input_str = f"role: {message['role']}, content: {message['content']}"
 
38
  return length
39
 
40
 
41
+ def markdown_to_html_with_syntax_highlight(md_str):
42
+ def replacer(match):
43
+ lang = match.group(1) or "text"
44
+ code = match.group(2)
45
+
46
+ try:
47
+ lexer = get_lexer_by_name(lang, stripall=True)
48
+ except ValueError:
49
+ lexer = get_lexer_by_name("text", stripall=True)
50
+
51
+ formatter = HtmlFormatter()
52
+ highlighted_code = highlight(code, lexer, formatter)
53
+
54
+ return f'<pre><code class="{lang}">{highlighted_code}</code></pre>'
55
+
56
+ code_block_pattern = r"```(\w+)?\n([\s\S]+?)\n```"
57
+ md_str = re.sub(code_block_pattern, replacer, md_str, flags=re.MULTILINE)
58
+
59
+ html_str = markdown(md_str)
60
+ return html_str
61
+
62
+
63
+ def normalize_markdown(md_text: str) -> str:
64
+ lines = md_text.split("\n")
65
+ normalized_lines = []
66
+ inside_list = False
67
+
68
+ for i, line in enumerate(lines):
69
+ if re.match(r"^(\d+\.|-|\*|\+)\s", line.strip()):
70
+ if not inside_list and i > 0 and lines[i - 1].strip() != "":
71
+ normalized_lines.append("")
72
+ inside_list = True
73
+ normalized_lines.append(line)
74
+ elif inside_list and line.strip() == "":
75
+ if i < len(lines) - 1 and not re.match(
76
+ r"^(\d+\.|-|\*|\+)\s", lines[i + 1].strip()
77
+ ):
78
+ normalized_lines.append(line)
79
+ continue
80
  else:
81
+ inside_list = False
82
+ normalized_lines.append(line)
83
+
84
+ return "\n".join(normalized_lines)
85
+
86
+
87
+ def convert_mdtext(md_text):
88
+ code_block_pattern = re.compile(r"```(.*?)(?:```|$)", re.DOTALL)
89
+ inline_code_pattern = re.compile(r"`(.*?)`", re.DOTALL)
90
+ code_blocks = code_block_pattern.findall(md_text)
91
+ non_code_parts = code_block_pattern.split(md_text)[::2]
92
+
93
+ result = []
94
+ for non_code, code in zip(non_code_parts, code_blocks + [""]):
95
+ if non_code.strip():
96
+ non_code = normalize_markdown(non_code)
97
+ if inline_code_pattern.search(non_code):
98
+ result.append(markdown(non_code, extensions=["tables"]))
99
+ else:
100
+ result.append(mdtex2html.convert(non_code, extensions=["tables"]))
101
+ if code.strip():
102
+ # _, code = detect_language(code) # 暂时去除代码高亮功能,因为在大段代码的情况下会出现问题
103
+ # code = code.replace("\n\n", "\n") # 暂时去除代码中的空行,因为在大段代码的情况下会出现问题
104
+ code = f"```{code}\n\n```"
105
+ code = markdown_to_html_with_syntax_highlight(code)
106
+ result.append(code)
107
+ result = "".join(result)
108
+ return result
109
+
110
+
111
+ def detect_language(code):
112
+ if code.startswith("\n"):
113
+ first_line = ""
114
+ else:
115
+ first_line = code.strip().split("\n", 1)[0]
116
+ language = first_line.lower() if first_line else ""
117
+ code_without_language = code[len(first_line) :].lstrip() if first_line else code
118
+ return language, code_without_language
119
 
120
 
121
  def construct_text(role, text):
 
346
  def replace_today(prompt):
347
  today = datetime.datetime.today().strftime("%Y-%m-%d")
348
  return prompt.replace("{current_date}", today)
349
+
350
+
351
+ def get_geoip():
352
+ response = requests.get("https://ipapi.co/json/", timeout=5)
353
+ try:
354
+ data = response.json()
355
+ except:
356
+ data = {"error": True, "reason": "连接ipapi失败"}
357
+ if "error" in data.keys():
358
+ logging.warning(f"无法获取IP地址信息。\n{data}")
359
+ if data["reason"] == "RateLimited":
360
+ return (
361
+ f"获取IP地理位置失败,因为达到了检测IP的速率限制。聊天功能可能仍然可用,但请注意,如果您的IP地址在不受支持的地区,您可能会遇到问题。"
362
+ )
363
+ else:
364
+ return f"获取IP地理位置失败。原因:{data['reason']}。你仍然可以使用聊天功能。"
365
+ else:
366
+ country = data["country_name"]
367
+ if country == "China":
368
+ text = "**您的IP区域:中国。请立即检查代理设置,在不受支持的地区使用API可能导致账号被封禁。**"
369
+ else:
370
+ text = f"您的IP区域:{country}。"
371
+ logging.info(text)
372
+ return text
373
+
374
+
375
+ def find_n(lst, max_num):
376
+ n = len(lst)
377
+ total = sum(lst)
378
+
379
+ if total < max_num:
380
+ return n
381
+
382
+ for i in range(len(lst)):
383
+ if total - lst[i] < max_num:
384
+ return n - i -1
385
+ total = total - lst[i]
386
+ return 1