3v324v23 commited on
Commit
fa22df9
1 Parent(s): 1c937ed
Files changed (5) hide show
  1. colorful.py +91 -0
  2. config.py +3 -0
  3. functional_crazy.py +15 -24
  4. main.py +1 -1
  5. predict.py +66 -116
colorful.py ADDED
@@ -0,0 +1,91 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import platform
2
+ from sys import stdout
3
+
4
+ if platform.system()=="Linux":
5
+ pass
6
+ else:
7
+ from colorama import init
8
+ init()
9
+
10
+ # Do you like the elegance of Chinese characters?
11
+ def print红(*kw,**kargs):
12
+ print("\033[0;31m",*kw,"\033[0m",**kargs)
13
+ def print绿(*kw,**kargs):
14
+ print("\033[0;32m",*kw,"\033[0m",**kargs)
15
+ def print黄(*kw,**kargs):
16
+ print("\033[0;33m",*kw,"\033[0m",**kargs)
17
+ def print蓝(*kw,**kargs):
18
+ print("\033[0;34m",*kw,"\033[0m",**kargs)
19
+ def print紫(*kw,**kargs):
20
+ print("\033[0;35m",*kw,"\033[0m",**kargs)
21
+ def print靛(*kw,**kargs):
22
+ print("\033[0;36m",*kw,"\033[0m",**kargs)
23
+
24
+ def print亮红(*kw,**kargs):
25
+ print("\033[1;31m",*kw,"\033[0m",**kargs)
26
+ def print亮绿(*kw,**kargs):
27
+ print("\033[1;32m",*kw,"\033[0m",**kargs)
28
+ def print亮黄(*kw,**kargs):
29
+ print("\033[1;33m",*kw,"\033[0m",**kargs)
30
+ def print亮蓝(*kw,**kargs):
31
+ print("\033[1;34m",*kw,"\033[0m",**kargs)
32
+ def print亮紫(*kw,**kargs):
33
+ print("\033[1;35m",*kw,"\033[0m",**kargs)
34
+ def print亮靛(*kw,**kargs):
35
+ print("\033[1;36m",*kw,"\033[0m",**kargs)
36
+
37
+
38
+
39
+ def print亮红(*kw,**kargs):
40
+ print("\033[1;31m",*kw,"\033[0m",**kargs)
41
+ def print亮绿(*kw,**kargs):
42
+ print("\033[1;32m",*kw,"\033[0m",**kargs)
43
+ def print亮黄(*kw,**kargs):
44
+ print("\033[1;33m",*kw,"\033[0m",**kargs)
45
+ def print亮蓝(*kw,**kargs):
46
+ print("\033[1;34m",*kw,"\033[0m",**kargs)
47
+ def print亮紫(*kw,**kargs):
48
+ print("\033[1;35m",*kw,"\033[0m",**kargs)
49
+ def print亮靛(*kw,**kargs):
50
+ print("\033[1;36m",*kw,"\033[0m",**kargs)
51
+
52
+ print_red = print红
53
+ print_green = print绿
54
+ print_yellow = print黄
55
+ print_blue = print蓝
56
+ print_purple = print紫
57
+ print_indigo = print靛
58
+
59
+ print_bold_red = print亮红
60
+ print_bold_green = print亮绿
61
+ print_bold_yellow = print亮黄
62
+ print_bold_blue = print亮蓝
63
+ print_bold_purple = print亮紫
64
+ print_bold_indigo = print亮靛
65
+
66
+ if not stdout.isatty():
67
+ # redirection, avoid a fucked up log file
68
+ print红 = print
69
+ print绿 = print
70
+ print黄 = print
71
+ print蓝 = print
72
+ print紫 = print
73
+ print靛 = print
74
+ print亮红 = print
75
+ print亮绿 = print
76
+ print亮黄 = print
77
+ print亮蓝 = print
78
+ print亮紫 = print
79
+ print亮靛 = print
80
+ print_red = print
81
+ print_green = print
82
+ print_yellow = print
83
+ print_blue = print
84
+ print_purple = print
85
+ print_indigo = print
86
+ print_bold_red = print
87
+ print_bold_green = print
88
+ print_bold_yellow = print
89
+ print_bold_blue = print
90
+ print_bold_purple = print
91
+ print_bold_indigo = print
config.py CHANGED
@@ -21,6 +21,9 @@ WEB_PORT = -1
21
  # 如果OpenAI不响应(网络卡顿、代理失败、KEY失效),重试的次数限制
22
  MAX_RETRY = 2
23
 
 
 
 
24
  # 检查一下是不是忘了改config
25
  if API_KEY == "sk-此处填API秘钥":
26
  assert False, "请在config文件中修改API密钥, 添加海外代理之后再运行"
 
21
  # 如果OpenAI不响应(网络卡顿、代理失败、KEY失效),重试的次数限制
22
  MAX_RETRY = 2
23
 
24
+ # 选择的OpenAI模型是(gpt4现在只对申请成功的人开放)
25
+ LLM_MODEL = "gpt-3.5-turbo"
26
+
27
  # 检查一下是不是忘了改config
28
  if API_KEY == "sk-此处填API秘钥":
29
  assert False, "请在config文件中修改API密钥, 添加海外代理之后再运行"
functional_crazy.py CHANGED
@@ -1,26 +1,18 @@
1
- # """
2
- # 'primary' for main call-to-action,
3
- # 'secondary' for a more subdued style,
4
- # 'stop' for a stop button.
5
- # """
6
-
7
  fast_debug = False
8
 
9
- def 自我程序解构简单案例(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
10
- import time
11
- from predict import predict_no_ui_no_history
12
  for i in range(5):
13
  i_say = f'我给出一个数字,你给出该数字的平方。我给出数字:{i}'
14
- gpt_say = predict_no_ui_no_history(inputs=i_say, top_p=top_p, temperature=temperature)
15
  chatbot.append((i_say, gpt_say))
16
  history.append(i_say)
17
  history.append(gpt_say)
18
  yield chatbot, history, '正常'
19
- time.sleep(10)
20
 
21
  def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
22
  import time, glob, os
23
- from predict import predict_no_ui
24
  file_manifest = [f for f in glob.glob('*.py')]
25
 
26
  for index, fp in enumerate(file_manifest):
@@ -30,7 +22,7 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
30
  前言 = "接下来请你分析自己的程序构成,别紧张," if index==0 else ""
31
  i_say = 前言 + f'请对下面的程序文件做一个概述文件名是{fp},文件代码是 ```{file_content}```'
32
  i_say_show_user = 前言 + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}'
33
- chatbot.append((i_say_show_user, "[local] waiting gpt response."))
34
  yield chatbot, history, '正常'
35
 
36
  if not fast_debug:
@@ -43,7 +35,7 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
43
  time.sleep(2)
44
 
45
  i_say = f'根据以上你自己的分析,对程序的整体功能和构架做出概括。然后用一张markdown表格整理每个文件的功能(包括{file_manifest})。'
46
- chatbot.append((i_say, "[local] waiting gpt response."))
47
  yield chatbot, history, '正常'
48
 
49
  if not fast_debug:
@@ -64,7 +56,6 @@ def report_execption(chatbot, history, a, b):
64
 
65
  def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
66
  import time, glob, os
67
- from predict import predict_no_ui
68
  print('begin analysis on:', file_manifest)
69
  for index, fp in enumerate(file_manifest):
70
  with open(fp, 'r', encoding='utf-8') as f:
@@ -73,7 +64,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
73
  前言 = "接下来请你逐文件分析下面的工程" if index==0 else ""
74
  i_say = 前言 + f'请对下面的程序文件做一个概述文件名是{os.path.relpath(fp, project_folder)},文件代码是 ```{file_content}```'
75
  i_say_show_user = 前言 + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}'
76
- chatbot.append((i_say_show_user, "[local] waiting gpt response."))
77
  print('[1] yield chatbot, history')
78
  yield chatbot, history, '正常'
79
 
@@ -98,7 +89,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
98
 
99
  all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
100
  i_say = f'根据以上你自己的分析,对程序的整体功能和构架做出概括。然后用一张markdown表格整理每个文件的功能(包括{all_file})。'
101
- chatbot.append((i_say, "[local] waiting gpt response."))
102
  yield chatbot, history, '正常'
103
 
104
  if not fast_debug:
@@ -159,22 +150,22 @@ def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, s
159
 
160
  def get_crazy_functionals():
161
  return {
162
- "程序解构简单案例": {
163
- "Color": "stop", # 按钮颜色
164
- "Function": 自我程序解构简单案例
165
- },
166
- "请解析并解构此项目本身": {
167
  "Color": "stop", # 按钮颜色
168
  "Function": 解析项目本身
169
  },
170
- "解析一整个Python项目(输入栏给定项目完整目录)": {
171
  "Color": "stop", # 按钮颜色
172
  "Function": 解析一个Python项目
173
  },
174
- "解析一整个C++项目的头文件(输入栏给定项目完整目录)": {
175
  "Color": "stop", # 按钮颜色
176
  "Function": 解析一个C项目的头文件
177
  },
 
 
 
 
178
 
179
  }
180
 
 
1
+ from predict import predict_no_ui
 
 
 
 
 
2
  fast_debug = False
3
 
4
+ def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
 
 
5
  for i in range(5):
6
  i_say = f'我给出一个数字,你给出该数字的平方。我给出数字:{i}'
7
+ gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature)
8
  chatbot.append((i_say, gpt_say))
9
  history.append(i_say)
10
  history.append(gpt_say)
11
  yield chatbot, history, '正常'
12
+
13
 
14
  def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
15
  import time, glob, os
 
16
  file_manifest = [f for f in glob.glob('*.py')]
17
 
18
  for index, fp in enumerate(file_manifest):
 
22
  前言 = "接下来请你分析自己的程序构成,别紧张," if index==0 else ""
23
  i_say = 前言 + f'请对下面的程序文件做一个概述文件名是{fp},文件代码是 ```{file_content}```'
24
  i_say_show_user = 前言 + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}'
25
+ chatbot.append((i_say_show_user, "[waiting gpt response]"))
26
  yield chatbot, history, '正常'
27
 
28
  if not fast_debug:
 
35
  time.sleep(2)
36
 
37
  i_say = f'根据以上你自己的分析,对程序的整体功能和构架做出概括。然后用一张markdown表格整理每个文件的功能(包括{file_manifest})。'
38
+ chatbot.append((i_say, "[waiting gpt response]"))
39
  yield chatbot, history, '正常'
40
 
41
  if not fast_debug:
 
56
 
57
  def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
58
  import time, glob, os
 
59
  print('begin analysis on:', file_manifest)
60
  for index, fp in enumerate(file_manifest):
61
  with open(fp, 'r', encoding='utf-8') as f:
 
64
  前言 = "接下来请你逐文件分析下面的工程" if index==0 else ""
65
  i_say = 前言 + f'请对下面的程序文件做一个概述文件名是{os.path.relpath(fp, project_folder)},文件代码是 ```{file_content}```'
66
  i_say_show_user = 前言 + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}'
67
+ chatbot.append((i_say_show_user, "[waiting gpt response]"))
68
  print('[1] yield chatbot, history')
69
  yield chatbot, history, '正常'
70
 
 
89
 
90
  all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
91
  i_say = f'根据以上你自己的分析,对程序的整体功能和构架做出概括。然后用一张markdown表格整理每个文件的功能(包括{all_file})。'
92
+ chatbot.append((i_say, "[waiting gpt response]"))
93
  yield chatbot, history, '正常'
94
 
95
  if not fast_debug:
 
150
 
151
  def get_crazy_functionals():
152
  return {
153
+ "[实验功能] 请解析并解构此项目本身": {
 
 
 
 
154
  "Color": "stop", # 按钮颜色
155
  "Function": 解析项目本身
156
  },
157
+ "[实验功能] 解析一整个Python项目(输入栏给定项目完整目录)": {
158
  "Color": "stop", # 按钮颜色
159
  "Function": 解析一个Python项目
160
  },
161
+ "[实验功能] 解析一整个C++项目的头文件(输入栏给定项目完整目录)": {
162
  "Color": "stop", # 按钮颜色
163
  "Function": 解析一个C项目的头文件
164
  },
165
+ "[实验功能] 高阶功能模板函数": {
166
+ "Color": "stop", # 按钮颜色
167
+ "Function": 高阶功能模板函数
168
+ },
169
 
170
  }
171
 
main.py CHANGED
@@ -106,7 +106,7 @@ with gr.Blocks() as demo:
106
  # submitBtn.click(reset_textbox, [], [txt])
107
  for k in functional:
108
  functional[k]["Button"].click(predict,
109
- [txt, top_p, temperature, chatbot, history, systemPromptTxt, FALSE, TRUE, gr.State(k)], [chatbot, history, statusDisplay], show_progress=True)
110
  for k in crazy_functional:
111
  crazy_functional[k]["Button"].click(crazy_functional[k]["Function"],
112
  [txt, top_p, temperature, chatbot, history, systemPromptTxt, gr.State(PORT)], [chatbot, history, statusDisplay])
 
106
  # submitBtn.click(reset_textbox, [], [txt])
107
  for k in functional:
108
  functional[k]["Button"].click(predict,
109
+ [txt, top_p, temperature, chatbot, history, systemPromptTxt, TRUE, gr.State(k)], [chatbot, history, statusDisplay], show_progress=True)
110
  for k in crazy_functional:
111
  crazy_functional[k]["Button"].click(crazy_functional[k]["Function"],
112
  [txt, top_p, temperature, chatbot, history, systemPromptTxt, gr.State(PORT)], [chatbot, history, statusDisplay])
predict.py CHANGED
@@ -6,11 +6,12 @@ import logging
6
  import traceback
7
  import requests
8
  import importlib
 
9
 
10
  # config_private.py放自己的秘密如API和代理网址
11
  # 读取时首先看是否存在私密的config_private配置文件(不受git管控),如果有,则覆盖原config文件
12
- try: from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY
13
- except: from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY
14
 
15
  timeout_bot_msg = '[local] Request timeout, network error. please check proxy settings in config.py.'
16
 
@@ -23,51 +24,12 @@ def get_full_error(chunk, stream_response):
23
  return chunk
24
 
25
  def predict_no_ui(inputs, top_p, temperature, history=[]):
26
- messages = [{"role": "system", "content": ""}]
27
-
28
- #
29
- chat_counter = len(history) // 2
30
- if chat_counter > 0:
31
- for index in range(0, 2*chat_counter, 2):
32
- what_i_have_asked = {}
33
- what_i_have_asked["role"] = "user"
34
- what_i_have_asked["content"] = history[index]
35
- what_gpt_answer = {}
36
- what_gpt_answer["role"] = "assistant"
37
- what_gpt_answer["content"] = history[index+1]
38
- if what_i_have_asked["content"] != "":
39
- messages.append(what_i_have_asked)
40
- messages.append(what_gpt_answer)
41
- else:
42
- messages[-1]['content'] = what_gpt_answer['content']
43
-
44
- what_i_ask_now = {}
45
- what_i_ask_now["role"] = "user"
46
- what_i_ask_now["content"] = inputs
47
- messages.append(what_i_ask_now)
48
-
49
- # messages
50
- payload = {
51
- "model": "gpt-3.5-turbo",
52
- # "model": "gpt-4",
53
- "messages": messages,
54
- "temperature": temperature, # 1.0,
55
- "top_p": top_p, # 1.0,
56
- "n": 1,
57
- "stream": False,
58
- "presence_penalty": 0,
59
- "frequency_penalty": 0,
60
- }
61
-
62
- headers = {
63
- "Content-Type": "application/json",
64
- "Authorization": f"Bearer {API_KEY}"
65
- }
66
 
67
  retry = 0
68
  while True:
69
  try:
70
- # make a POST request to the API endpoint using the requests.post method, passing in stream=True
71
  response = requests.post(API_URL, headers=headers, proxies=proxies,
72
  json=payload, stream=False, timeout=TIMEOUT_SECONDS*2); break
73
  except TimeoutError as e:
@@ -84,9 +46,7 @@ def predict_no_ui(inputs, top_p, temperature, history=[]):
84
  raise ConnectionAbortedError("Json解析不合常规,可能是文本过长" + response.text)
85
 
86
 
87
-
88
-
89
- def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', retry=False,
90
  stream = True, additional_fn=None):
91
 
92
  if additional_fn is not None:
@@ -101,60 +61,13 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
101
  chatbot.append((inputs, ""))
102
  yield chatbot, history, "等待响应"
103
 
104
- headers = {
105
- "Content-Type": "application/json",
106
- "Authorization": f"Bearer {API_KEY}"
107
- }
108
-
109
- chat_counter = len(history) // 2
110
-
111
- print(f"chat_counter - {chat_counter}")
112
-
113
- messages = [{"role": "system", "content": system_prompt}]
114
- if chat_counter:
115
- for index in range(0, 2*chat_counter, 2):
116
- what_i_have_asked = {}
117
- what_i_have_asked["role"] = "user"
118
- what_i_have_asked["content"] = history[index]
119
- what_gpt_answer = {}
120
- what_gpt_answer["role"] = "assistant"
121
- what_gpt_answer["content"] = history[index+1]
122
- if what_i_have_asked["content"] != "":
123
- if not (what_gpt_answer["content"] != "" or retry): continue
124
- if what_gpt_answer["content"] == timeout_bot_msg: continue
125
- messages.append(what_i_have_asked)
126
- messages.append(what_gpt_answer)
127
- else:
128
- messages[-1]['content'] = what_gpt_answer['content']
129
-
130
- if retry and chat_counter:
131
- messages.pop()
132
- else:
133
- what_i_ask_now = {}
134
- what_i_ask_now["role"] = "user"
135
- what_i_ask_now["content"] = inputs
136
- messages.append(what_i_ask_now)
137
- chat_counter += 1
138
-
139
- # messages
140
- payload = {
141
- "model": "gpt-3.5-turbo",
142
- # "model": "gpt-4",
143
- "messages": messages,
144
- "temperature": temperature, # 1.0,
145
- "top_p": top_p, # 1.0,
146
- "n": 1,
147
- "stream": stream,
148
- "presence_penalty": 0,
149
- "frequency_penalty": 0,
150
- }
151
-
152
- history.append(inputs)
153
 
154
  retry = 0
155
  while True:
156
  try:
157
- # make a POST request to the API endpoint using the requests.post method, passing in stream=True
158
  response = requests.post(API_URL, headers=headers, proxies=proxies,
159
  json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
160
  except:
@@ -164,37 +77,30 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
164
  yield chatbot, history, "请求超时"+retry_msg
165
  if retry > MAX_RETRY: raise TimeoutError
166
 
167
- token_counter = 0
168
- partial_words = ""
169
-
170
- counter = 0
171
  if stream:
172
  stream_response = response.iter_lines()
173
  while True:
174
  chunk = next(stream_response)
175
- if chunk == b'data: [DONE]':
176
- break
177
-
178
- if counter == 0:
179
- counter += 1
180
- continue
181
- counter += 1
182
- # check whether each line is non-empty
183
  if chunk:
184
- # decode each line as response data is in bytes
185
  try:
186
  if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
187
- logging.info(f'[response] {chatbot[-1][-1]}')
 
188
  break
 
189
  chunkjson = json.loads(chunk.decode()[6:])
190
  status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
191
- partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
192
- if token_counter == 0:
193
- history.append(" " + partial_words)
194
- else:
195
- history[-1] = partial_words
196
  chatbot[-1] = (history[-2], history[-1])
197
- token_counter += 1
198
  yield chatbot, history, status_text
199
 
200
  except Exception as e:
@@ -207,4 +113,48 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
207
  yield chatbot, history, "Json解析不合常规,很可能是文本过长" + error_msg
208
  return
209
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
210
 
 
6
  import traceback
7
  import requests
8
  import importlib
9
+ from colorful import *
10
 
11
  # config_private.py放自己的秘密如API和代理网址
12
  # 读取时首先看是否存在私密的config_private配置文件(不受git管控),如果有,则覆盖原config文件
13
+ try: from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY, LLM_MODEL
14
+ except: from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY, LLM_MODEL
15
 
16
  timeout_bot_msg = '[local] Request timeout, network error. please check proxy settings in config.py.'
17
 
 
24
  return chunk
25
 
26
  def predict_no_ui(inputs, top_p, temperature, history=[]):
27
+ headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt="", stream=False)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
28
 
29
  retry = 0
30
  while True:
31
  try:
32
+ # make a POST request to the API endpoint, stream=False
33
  response = requests.post(API_URL, headers=headers, proxies=proxies,
34
  json=payload, stream=False, timeout=TIMEOUT_SECONDS*2); break
35
  except TimeoutError as e:
 
46
  raise ConnectionAbortedError("Json解析不合常规,可能是文本过长" + response.text)
47
 
48
 
49
+ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='',
 
 
50
  stream = True, additional_fn=None):
51
 
52
  if additional_fn is not None:
 
61
  chatbot.append((inputs, ""))
62
  yield chatbot, history, "等待响应"
63
 
64
+ headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
65
+ history.append(inputs); history.append(" ")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66
 
67
  retry = 0
68
  while True:
69
  try:
70
+ # make a POST request to the API endpoint, stream=True
71
  response = requests.post(API_URL, headers=headers, proxies=proxies,
72
  json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
73
  except:
 
77
  yield chatbot, history, "请求超时"+retry_msg
78
  if retry > MAX_RETRY: raise TimeoutError
79
 
80
+ gpt_replying_buffer = ""
81
+
82
+ is_head_of_the_stream = True
 
83
  if stream:
84
  stream_response = response.iter_lines()
85
  while True:
86
  chunk = next(stream_response)
87
+ # print(chunk.decode()[6:])
88
+ if is_head_of_the_stream:
89
+ is_head_of_the_stream = False; continue
90
+
 
 
 
 
91
  if chunk:
 
92
  try:
93
  if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
94
+ # 判定为数据流的结束,gpt_replying_buffer也写完了
95
+ logging.info(f'[response] {gpt_replying_buffer}')
96
  break
97
+ # 处理数据流的主体
98
  chunkjson = json.loads(chunk.decode()[6:])
99
  status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
100
+ # 如果这里抛出异常,一般是文本过长,详情见get_full_error的输出
101
+ gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
102
+ history[-1] = gpt_replying_buffer
 
 
103
  chatbot[-1] = (history[-2], history[-1])
 
104
  yield chatbot, history, status_text
105
 
106
  except Exception as e:
 
113
  yield chatbot, history, "Json解析不合常规,很可能是文本过长" + error_msg
114
  return
115
 
116
+ def generate_payload(inputs, top_p, temperature, history, system_prompt, stream):
117
+ headers = {
118
+ "Content-Type": "application/json",
119
+ "Authorization": f"Bearer {API_KEY}"
120
+ }
121
+
122
+ conversation_cnt = len(history) // 2
123
+
124
+ messages = [{"role": "system", "content": system_prompt}]
125
+ if conversation_cnt:
126
+ for index in range(0, 2*conversation_cnt, 2):
127
+ what_i_have_asked = {}
128
+ what_i_have_asked["role"] = "user"
129
+ what_i_have_asked["content"] = history[index]
130
+ what_gpt_answer = {}
131
+ what_gpt_answer["role"] = "assistant"
132
+ what_gpt_answer["content"] = history[index+1]
133
+ if what_i_have_asked["content"] != "":
134
+ if what_gpt_answer["content"] == "": continue
135
+ if what_gpt_answer["content"] == timeout_bot_msg: continue
136
+ messages.append(what_i_have_asked)
137
+ messages.append(what_gpt_answer)
138
+ else:
139
+ messages[-1]['content'] = what_gpt_answer['content']
140
+
141
+ what_i_ask_now = {}
142
+ what_i_ask_now["role"] = "user"
143
+ what_i_ask_now["content"] = inputs
144
+ messages.append(what_i_ask_now)
145
+
146
+ payload = {
147
+ "model": LLM_MODEL,
148
+ "messages": messages,
149
+ "temperature": temperature, # 1.0,
150
+ "top_p": top_p, # 1.0,
151
+ "n": 1,
152
+ "stream": stream,
153
+ "presence_penalty": 0,
154
+ "frequency_penalty": 0,
155
+ }
156
+
157
+ print(f" {LLM_MODEL} : {conversation_cnt} : {inputs}")
158
+ return headers,payload
159
+
160