forked from PierXuY/ChatGPT-Assistant
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathapp.py
416 lines (372 loc) · 20.3 KB
/
app.py
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
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
from helper import *
import streamlit as st
import uuid
import copy
import pandas as pd
import openai
from requests.models import ChunkedEncodingError
from streamlit.components import v1
from voice_toolkit import voice_toolkit
st.set_page_config(page_title='ChatGPT Assistant', layout='wide', page_icon='🤖')
# 自定义元素样式
st.markdown(css_code, unsafe_allow_html=True)
if "initial_settings" not in st.session_state:
# 历史聊天窗口
st.session_state["path"] = 'history_chats_file'
st.session_state['history_chats'] = get_history_chats(st.session_state["path"])
# ss参数初始化
st.session_state['delete_dict'] = {}
st.session_state['delete_count'] = 0
st.session_state['voice_flag'] = ''
st.session_state['user_voice_value'] = ''
st.session_state['error_info'] = ''
st.session_state["current_chat_index"] = 0
st.session_state['user_input_content'] = ''
# 读取全局设置
if os.path.exists('./set.json'):
with open('./set.json', 'r', encoding='utf-8') as f:
data_set = json.load(f)
for key, value in data_set.items():
st.session_state[key] = value
# 设置完成
st.session_state["initial_settings"] = True
with st.sidebar:
st.markdown("# 🤖 聊天窗口")
# 创建容器的目的是配合自定义组件的监听操作
chat_container = st.container()
with chat_container:
current_chat = st.radio(
label='历史聊天窗口',
format_func=lambda x: x.split('_')[0] if '_' in x else x,
options=st.session_state['history_chats'],
label_visibility='collapsed',
index=st.session_state["current_chat_index"],
key='current_chat' + st.session_state['history_chats'][st.session_state["current_chat_index"]],
# on_change=current_chat_callback # 此处不适合用回调，无法识别到窗口增减的变动
)
st.write("---")
# 数据写入文件
def write_data(new_chat_name=current_chat):
if "apikey" in st.secrets:
st.session_state["paras"] = {
"temperature": st.session_state["temperature" + current_chat],
"top_p": st.session_state["top_p" + current_chat],
"presence_penalty": st.session_state["presence_penalty" + current_chat],
"frequency_penalty": st.session_state["frequency_penalty" + current_chat],
}
st.session_state["contexts"] = {
"context_select": st.session_state["context_select" + current_chat],
"context_input": st.session_state["context_input" + current_chat],
"context_level": st.session_state["context_level" + current_chat],
}
save_data(st.session_state["path"], new_chat_name, st.session_state["history" + current_chat],
st.session_state["paras"], st.session_state["contexts"])
def reset_chat_name_fun(chat_name):
chat_name = chat_name + '_' + str(uuid.uuid4())
new_name = filename_correction(chat_name)
current_chat_index = st.session_state['history_chats'].index(current_chat)
st.session_state['history_chats'][current_chat_index] = new_name
st.session_state["current_chat_index"] = current_chat_index
# 写入新文件
write_data(new_name)
# 转移数据
st.session_state['history' + new_name] = st.session_state['history' + current_chat]
for item in ["context_select", "context_input", "context_level", *initial_content_all['paras']]:
st.session_state[item + new_name + "value"] = st.session_state[item + current_chat + "value"]
remove_data(st.session_state["path"], current_chat)
def create_chat_fun():
st.session_state['history_chats'] = ['New Chat_' + str(uuid.uuid4())] + st.session_state['history_chats']
st.session_state["current_chat_index"] = 0
def delete_chat_fun():
if len(st.session_state['history_chats']) == 1:
chat_init = 'New Chat_' + str(uuid.uuid4())
st.session_state['history_chats'].append(chat_init)
pre_chat_index = st.session_state['history_chats'].index(current_chat)
if pre_chat_index > 0:
st.session_state["current_chat_index"] = st.session_state['history_chats'].index(current_chat) - 1
else:
st.session_state["current_chat_index"] = 0
st.session_state['history_chats'].remove(current_chat)
remove_data(st.session_state["path"], current_chat)
with st.sidebar:
c1, c2 = st.columns(2)
create_chat_button = c1.button('新建', use_container_width=True, key='create_chat_button')
if create_chat_button:
create_chat_fun()
st.experimental_rerun()
delete_chat_button = c2.button('删除', use_container_width=True, key='delete_chat_button')
if delete_chat_button:
delete_chat_fun()
st.experimental_rerun()
with st.sidebar:
if ("set_chat_name" in st.session_state) and st.session_state['set_chat_name'] != '':
reset_chat_name_fun(st.session_state['set_chat_name'])
st.session_state['set_chat_name'] = ''
st.experimental_rerun()
st.write("\n")
st.write("\n")
st.text_input("设定窗口名称：", key="set_chat_name", placeholder="点击输入")
st.selectbox("选择模型：", index=0, options=['gpt-3.5-turbo', 'gpt-4'], key="select_model")
st.write("\n")
st.caption("""
- 双击页面可直接定位输入栏
- Ctrl + Enter 可快捷提交问题
""")
st.markdown('<a href="https://github.com/PierXuY/ChatGPT-Assistant" target="_blank" rel="ChatGPT-Assistant">'
'<img src="https://badgen.net/badge/icon/GitHub?icon=github&label=ChatGPT Assistant" alt="GitHub">'
'</a>', unsafe_allow_html=True)
# 加载数据
if "history" + current_chat not in st.session_state:
for key, value in load_data(st.session_state["path"], current_chat).items():
if key == 'history':
st.session_state[key + current_chat] = value
else:
for k, v in value.items():
st.session_state[k + current_chat + "value"] = v
# 保证不同chat的页面层次一致，否则会导致自定义组件重新渲染
container_show_messages = st.container()
container_show_messages.write("")
# 对话展示
with container_show_messages:
if st.session_state["history" + current_chat]:
show_messages(current_chat, st.session_state["history" + current_chat])
# 核查是否有对话需要删除
if any(st.session_state['delete_dict'].values()):
for key, value in st.session_state['delete_dict'].items():
try:
deleteCount = value.get("deleteCount")
except AttributeError:
deleteCount = None
if deleteCount == st.session_state['delete_count']:
delete_keys = key
st.session_state['delete_count'] = deleteCount + 1
delete_current_chat, idr = delete_keys.split('>')
df_history_tem = pd.DataFrame(st.session_state["history" + delete_current_chat])
df_history_tem.drop(index=df_history_tem.query("role=='user'").iloc[[int(idr)], :].index, inplace=True)
df_history_tem.drop(index=df_history_tem.query("role=='assistant'").iloc[[int(idr)], :].index, inplace=True)
st.session_state["history" + delete_current_chat] = df_history_tem.to_dict('records')
write_data()
st.experimental_rerun()
def callback_fun(arg):
# 连续快速点击新建与删除会触发错误回调，增加判断
if ("history" + current_chat in st.session_state) and ("frequency_penalty" + current_chat in st.session_state):
write_data()
st.session_state[arg + current_chat + "value"] = st.session_state[arg + current_chat]
def clear_button_callback():
st.session_state['history' + current_chat] = []
write_data()
def save_set(arg):
st.session_state[arg + "_value"] = st.session_state[arg]
if "apikey" in st.secrets:
with open("./set.json", 'w', encoding='utf-8') as f:
json.dump({"open_text_toolkit_value": st.session_state["open_text_toolkit"],
"open_voice_toolkit_value": st.session_state['open_voice_toolkit'],
}, f)
# 输入内容展示
area_user_svg = st.empty()
area_user_content = st.empty()
# 回复展示
area_gpt_svg = st.empty()
area_gpt_content = st.empty()
# 报错展示
area_error = st.empty()
st.write("\n")
st.header('ChatGPT Assistant')
tap_input, tap_context, tap_model, tab_func = st.tabs(['💬 聊天', '🗒️ 预设', '⚙️ 模型', '🛠️ 功能'])
with tap_context:
set_context_list = list(set_context_all.keys())
context_select_index = set_context_list.index(st.session_state['context_select' + current_chat + "value"])
st.selectbox(
label='选择上下文',
options=set_context_list,
key='context_select' + current_chat,
index=context_select_index,
on_change=callback_fun,
args=("context_select",))
st.caption(set_context_all[st.session_state['context_select' + current_chat]])
st.text_area(
label='补充或自定义上下文：', key="context_input" + current_chat,
value=st.session_state['context_input' + current_chat + "value"],
on_change=callback_fun, args=("context_input",))
with tap_model:
st.markdown("OpenAI API Key (可选)")
st.text_input("OpenAI API Key (可选)", type='password', key='apikey_input', label_visibility='collapsed')
st.caption(
"此Key仅在当前网页有效，且优先级高于Secrets中的配置，仅自己可用，他人无法共享。[官网获取](https://platform.openai.com/account/api-keys)")
st.markdown("包含对话次数：")
st.slider(
"Context Level", 0, 10,
st.session_state['context_level' + current_chat + "value"], 1,
on_change=callback_fun,
key='context_level' + current_chat, args=('context_level',),
help="表示每次会话中包含的历史对话次数，预设内容不计算在内。")
st.markdown("模型参数：")
st.slider("Temperature", 0.0, 2.0, st.session_state["temperature" + current_chat + "value"], 0.1,
help="""在0和2之间，应该使用什么样的采样温度？较高的值（如0.8）会使输出更随机，而较低的值（如0.2）则会使其更加集中和确定性。
我们一般建议只更改这个参数或top_p参数中的一个，而不要同时更改两个。""",
on_change=callback_fun, key='temperature' + current_chat, args=('temperature',))
st.slider("Top P", 0.1, 1.0, st.session_state["top_p" + current_chat + "value"], 0.1,
help="""一种替代采用温度进行采样的方法，称为“基于核心概率”的采样。在该方法中，模型会考虑概率最高的top_p个标记的预测结果。
因此，当该参数为0.1时，只有包括前10%概率质量的标记将被考虑。我们一般建议只更改这个参数或采样温度参数中的一个，而不要同时更改两个。""",
on_change=callback_fun, key='top_p' + current_chat, args=('top_p',))
st.slider("Presence Penalty", -2.0, 2.0,
st.session_state["presence_penalty" + current_chat + "value"], 0.1,
help="""该参数的取值范围为-2.0到2.0。正值会根据新标记是否出现在当前生成的文本中对其进行惩罚，从而增加模型谈论新话题的可能性。""",
on_change=callback_fun, key='presence_penalty' + current_chat, args=('presence_penalty',))
st.slider("Frequency Penalty", -2.0, 2.0,
st.session_state["frequency_penalty" + current_chat + "value"], 0.1,
help="""该参数的取值范围为-2.0到2.0。正值会根据新标记在当前生成的文本中的已有频率对其进行惩罚，从而减少模型直接重复相同语句的可能性。""",
on_change=callback_fun, key='frequency_penalty' + current_chat, args=('frequency_penalty',))
st.caption("[官网参数说明](https://platform.openai.com/docs/api-reference/completions/create)")
with tab_func:
c0, c1, c2 = st.columns(3)
with c0:
options = ['docx', 'pdf', 'md']
file_ext = st.selectbox('选择导出格式', options)
if file_ext == 'md':
mime_str = "text/markdown"
with c1:
st.button("清空聊天记录", use_container_width=True, on_click=clear_button_callback)
with c2:
btn = st.download_button(
label="导出聊天记录",
data=download_history(st.session_state['history' + current_chat], file_ext),
file_name=f'{current_chat.split("_")[0]}.{file_ext}',
mime=mime_str,
use_container_width=True
)
st.write("\n")
st.markdown("自定义功能：")
c1, c2 = st.columns(2)
with c1:
if "open_text_toolkit_value" in st.session_state:
default = st.session_state["open_text_toolkit_value"]
else:
default = True
st.checkbox("开启文本下的功能组件", value=default, key='open_text_toolkit',
on_change=save_set, args=("open_text_toolkit",))
with c2:
if "open_voice_toolkit_value" in st.session_state:
default = st.session_state["open_voice_toolkit_value"]
else:
default = True
st.checkbox("开启语音输入组件", value=default, key='open_voice_toolkit',
on_change=save_set, args=('open_voice_toolkit',))
with tap_input:
def input_callback():
if st.session_state['user_input_area'] != "":
# 修改窗口名称
user_input_content = st.session_state['user_input_area']
df_history = pd.DataFrame(st.session_state["history" + current_chat])
if df_history.empty or len(df_history.query('role!="system"')) == 0:
new_name = extract_chars(user_input_content, 18)
reset_chat_name_fun(new_name)
with st.form("input_form", clear_on_submit=True):
user_input = st.text_area("**输入：**", key="user_input_area",
help="内容将以Markdown格式在页面展示，建议遵循相关语言规范，同样有利于GPT正确读取，例如："
"\n- 代码块写在三个反引号内，并标注语言类型"
"\n- 以英文冒号开头的内容或者正则表达式等写在单反引号内",
value=st.session_state['user_voice_value'])
submitted = st.form_submit_button("确认提交", use_container_width=True, on_click=input_callback)
if submitted:
st.session_state['user_input_content'] = user_input
st.session_state['user_voice_value'] = ''
st.experimental_rerun()
if "open_voice_toolkit_value" not in st.session_state or st.session_state["open_voice_toolkit_value"]:
# 语音输入功能
vocie_result = voice_toolkit()
# vocie_result会保存最后一次结果
if (vocie_result and vocie_result['voice_result']['flag'] == 'interim') or st.session_state['voice_flag'] == "interim":
st.session_state['voice_flag'] = 'interim'
st.session_state['user_voice_value'] = vocie_result['voice_result']['value']
if vocie_result['voice_result']['flag'] == 'final':
st.session_state['voice_flag'] = 'final'
st.experimental_rerun()
def get_model_input():
# 需输入的历史记录
context_level = st.session_state['context_level' + current_chat]
history = (get_history_input(st.session_state["history" + current_chat], context_level) +
[{"role": "user", "content": st.session_state['pre_user_input_content']}])
for ctx in [st.session_state['context_input' + current_chat],
set_context_all[st.session_state['context_select' + current_chat]]]:
if ctx != "":
history = [{"role": "system", "content": ctx}] + history
# 设定的模型参数
paras = {
"temperature": st.session_state["temperature" + current_chat],
"top_p": st.session_state["top_p" + current_chat],
"presence_penalty": st.session_state["presence_penalty" + current_chat],
"frequency_penalty": st.session_state["frequency_penalty" + current_chat],
}
return history, paras
if st.session_state['user_input_content'] != '':
if 'r' in st.session_state:
st.session_state.pop("r")
st.session_state[current_chat + 'report'] = ""
st.session_state['pre_user_input_content'] = st.session_state['user_input_content']
st.session_state['user_input_content'] = ''
# 临时展示
show_each_message(st.session_state['pre_user_input_content'], 'user', 'tem',
[area_user_svg.markdown, area_user_content.markdown])
# 模型输入
history_need_input, paras_need_input = get_model_input()
# 调用接口
with st.spinner("🤔"):
try:
if apikey := st.session_state['apikey_input']:
openai.api_key = apikey
# 配置临时apikey，此时不会留存聊天记录，适合公开使用
elif "apikey_tem" in st.secrets:
openai.api_key = st.secrets["apikey_tem"]
# 注：当st.secrets中配置apikey后将会留存聊天记录，即使未使用此apikey
else:
openai.api_key = st.secrets["apikey"]
r = openai.ChatCompletion.create(model=st.session_state["select_model"], messages=history_need_input,
stream=True,
**paras_need_input)
except (FileNotFoundError, KeyError):
area_error.error("缺失 OpenAI API Key，请在复制项目后配置Secrets，或者在模型选项中进行临时配置。"
"详情见[项目仓库](https://github.com/PierXuY/ChatGPT-Assistant)。")
except openai.error.AuthenticationError:
area_error.error("无效的 OpenAI API Key。")
except openai.error.APIConnectionError as e:
area_error.error("连接超时，请重试。报错： \n" + str(e.args[0]))
except openai.error.InvalidRequestError as e:
area_error.error("无效的请求，请重试。报错： \n" + str(e.args[0]))
except openai.error.RateLimitError as e:
area_error.error("请求受限。报错： \n" + str(e.args[0]))
else:
st.session_state["chat_of_r"] = current_chat
st.session_state["r"] = r
st.experimental_rerun()
if ("r" in st.session_state) and (current_chat == st.session_state["chat_of_r"]):
if current_chat + 'report' not in st.session_state:
st.session_state[current_chat + 'report'] = ""
try:
for e in st.session_state["r"]:
if "content" in e["choices"][0]["delta"]:
st.session_state[current_chat + 'report'] += e["choices"][0]["delta"]["content"]
show_each_message(st.session_state['pre_user_input_content'], 'user', 'tem',
[area_user_svg.markdown, area_user_content.markdown])
show_each_message(st.session_state[current_chat + 'report'], 'assistant', 'tem',
[area_gpt_svg.markdown, area_gpt_content.markdown])
except ChunkedEncodingError:
area_error.error("网络状况不佳，请刷新页面重试。")
# 应对stop情形
except Exception:
pass
else:
# 保存内容
st.session_state["history" + current_chat].append(
{"role": "user", "content": st.session_state['pre_user_input_content']})
st.session_state["history" + current_chat].append(
{"role": "assistant", "content": st.session_state[current_chat + 'report']})
write_data()
# 用户在网页点击stop时，ss某些情形下会暂时为空
if current_chat + 'report' in st.session_state:
st.session_state.pop(current_chat + 'report')
if 'r' in st.session_state:
st.session_state.pop("r")
st.experimental_rerun()
# 添加事件监听
v1.html(js_code, height=0)