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Update scale_n_consult.py

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  1. scale_n_consult.py +114 -21
scale_n_consult.py CHANGED
@@ -1,32 +1,74 @@
1
  import os
2
- from openai import OpenAI
3
  import gradio as gr
 
4
 
5
  OpenAI.api_key = os.getenv("OPENAI_API_KEY")
6
  api_key = os.getenv("OPENAI_API_KEY")
7
  client = OpenAI(api_key=api_key)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8
 
9
- initial_prompt = """
10
- 你是一名【专业的心理咨询师】,以下是你的用户的【基本情况】,由JSON格式给出:
11
- {
12
- "抑郁情况":"轻度抑郁",
13
- "睡眠状况":"有一点难以入睡",
14
- "体重状况":"体重正常",
15
- "思维状况":"头脑有时会一片空白",
16
- "心情状况":"心情有点沮丧烦闷,容易想哭,有时心跳的比平时快",
17
- "价值感":"有的时候会有点迷茫,不知道该做什么",
18
- "便秘情况":"偶尔",
19
- "性生活":"正常",
20
- "自杀倾向":"无自杀倾向",
21
- }
22
- 当你和用户交谈时,你需要【主动】向用户提问,并【围绕】用户的【基本情况】展开,【负面】的基本情况需要【着重】展开。
 
 
 
23
  首先,你需要根据用户的基���情况【展开详细的咨询】,但是【不能一下抛出所有问题,需要逐条提问】,主动向用户【提问】相关的问题并基于相应的【建议】。
24
  询问完后后,你需要生成一个【咨询报告】,包含【用户情况】、【相应建议】、【最终总结】,先以Markdown格式输出,再以JSON格式输出。
25
- 最后你需要告诉用户,诊断已结束,你不会主动提问,但受咨询者可以继续向你提问感兴趣的问题,你会作出回答。
26
- """
 
 
27
 
28
 
 
29
  def predict(message, history):
 
30
  history_openai_format = []
31
  history_openai_format.append({"role": "assistant", "content":initial_prompt})
32
  for human, assistant in history:
@@ -44,20 +86,71 @@ def predict(message, history):
44
  if chunk.choices[0].delta.content is not None:
45
  partial_message = partial_message + chunk.choices[0].delta.content
46
  yield partial_message
 
47
 
48
- SCALE_N_CONSULT=gr.ChatInterface(
 
49
  predict,
50
  chatbot=gr.Chatbot(
51
  height=400,
52
  bubble_full_width=False,
53
- avatar_images=(os.path.join(os.path.dirname(__file__), "patient_ava.png"), os.path.join(os.path.dirname(__file__), "docter_ava.png")),
54
  likeable=True,
55
  ),
56
- # textbox=gr.Textbox(placeholder="在此书输入消息...",),
57
  retry_btn="🔄重新生成",
58
  undo_btn="↩️撤回信息",
59
  clear_btn="🗑️清空信息",
60
  stop_btn="停止生成",
61
  submit_btn="发送",
62
 
63
- )
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  import os
2
+
3
  import gradio as gr
4
+ from openai import OpenAI
5
 
6
  OpenAI.api_key = os.getenv("OPENAI_API_KEY")
7
  api_key = os.getenv("OPENAI_API_KEY")
8
  client = OpenAI(api_key=api_key)
9
+ os.environ["no_proxy"] = "localhost,127.0.0.1,::1"
10
+ ###量表函数###
11
+ def visibility():
12
+ return gr.Column(visible=True)
13
+
14
+ def scale2json(choice1,choice2,choice3,choice4,choice5,choice6,choice7,choice8,choice9,choice10,choice11,choice12,choice13,choice14,choice15,choice16,choice17,choice18,choice19,choice20):
15
+ score = 0
16
+ global initial_prompt
17
+ choices = [choice1,choice2,choice3,choice4,choice5,choice6,choice7,choice8,choice9,choice10,choice11,choice12,choice13,choice14,choice15,choice16,choice17,choice18,choice19,choice20]
18
+ if None in choices:
19
+ gr.Warning("您有未勾选的题目,请确认后再次提交")
20
+ else:
21
+ for i in range(len(choices)):
22
+ match i:
23
+ case 1|4|5|10|11|13|15|16|17|19:
24
+ score += 4 - choices[i]
25
+ case _:
26
+ score += choices[i] + 1
27
+ s = round(1.25*score, 0)
28
+ DEPRESS="无抑郁体验" if s<53 else "可能有轻度抑郁倾向" if s<=62 else "可能有中度抑郁倾向" if s<=72 else "可能有重度抑郁倾向"
29
+ SLEEP="夜间睡眠良好"if choice4==0 else "有时夜间睡眠不好" if choice4==1 else "经常夜间睡眠不好" if choice4==2 else "总是夜间睡眠不好"
30
+ EAT="饮食状态差,不如平时" if choice5==0 else "饮食状态经常不如平时" if choice5==1 else "饮食状态正常" if choice5==2 else "饮食状态良好"
31
+ WEIGHT="体重正常" if choice7==0 else "有时体重会减轻" if choice7==1 else "体重经常会减轻" if choice7==2 else "体重相较于平时总是减轻"
32
+ MOOD1="很少感到沮丧郁闷" if choice1==0 else "有时感到沮丧郁闷" if choice1==1 else "经常感到沮丧郁闷" if choice1==2 else "总是感到沮丧郁闷"
33
+ MOOD2="几乎没有想哭的感觉" if choice3==0 else "有时会有想哭的感觉" if choice3==1 else "经常会有想哭的感觉" if choice3==2 else "总是会想哭"
34
+ MOOD3="不容易发怒" if choice15==0 else "有时容易发怒" if choice15==1 else "经常容易发怒" if choice15==2 else "总是容易发怒"
35
+ MOOD=MOOD1+", "+MOOD2+", "+MOOD3
36
+ TIRED="很少感到疲劳" if choice10==0 else "有时会感到疲劳" if choice10==1 else "经常会感到疲劳" if choice10==2 else "总是感到疲劳"
37
+ ANXIETY="几乎不会烦躁" if choice13==0 else "有时会坐立不安、难以平静" if choice13==1 else "经常会坐立不安、难以平静" if choice13==2 else"总是坐立不安、感觉难以平静"
38
+ PHYSICAL=TIRED+", "+ANXIETY
39
+ VALUE1="从来不觉得自己有用、不可或缺" if choice17==0 else "只有有时会觉得自己有用、不可或缺" if choice17==1 else "觉得自己是有用的、不可或缺的"
40
+ VALUE2="很少觉得自己的生活有意义" if choice18==0 else "有时才会觉得自己的生活有意义" if choice18==1 else "觉得自己的生活是有意义的"
41
+ VALUE=VALUE1+", "+VALUE2
42
+ SUICIDE="无自杀倾向" if choice19==0 else "有时会觉得自己死了别人会过得更好" if choice19==1 else "经常会觉得自己死了别人会过得更好" if choice19==2 else "总觉得自己死了别人会过得更好"
43
 
44
+ json_info=r"""
45
+ {{
46
+ "睡眠状况":"{}",
47
+ "饮食状况":"{}",
48
+ "体重状况":"{}",
49
+ "心情状况":"{}",
50
+ "日常生理状况":"{}",
51
+ "价值感":"{}",
52
+ "自杀倾向":"{}",
53
+ "抑郁情况":"{}",
54
+ }}
55
+ """.format(SLEEP,EAT,WEIGHT,MOOD,PHYSICAL,VALUE,SUICIDE,DEPRESS)
56
+
57
+ if choice19>=2:
58
+ gr.Info("如果你感到难以坚持下去,想要结束自己的生命,请一定不要灰心,请通过电话联系我们(4000-100-525, 再拨2),我们会陪伴在你身边!")
59
+
60
+ initial_prompt="""你是一名【专业的心理咨询师】,以下是你的用户的【基本情况】,由JSON格式给出:"""+json_info+"""当你和用户交谈时,你需要【主动】向用户提问,并【围绕】用户的【基本情况】展开,【负面】的基本情况需要【着重】展开。
61
  首先,你需要根据用户的基���情况【展开详细的咨询】,但是【不能一下抛出所有问题,需要逐条提问】,主动向用户【提问】相关的问题并基于相应的【建议】。
62
  询问完后后,你需要生成一个【咨询报告】,包含【用户情况】、【相应建议】、【最终总结】,先以Markdown格式输出,再以JSON格式输出。
63
+ 最后你需要告诉用户,诊断已结束,你不会主动提问,但受咨询者可以继续向你提问感兴趣的问题,你会作出回答。"""
64
+
65
+ return gr.Column(visible=True),s,initial_prompt
66
+ ############
67
 
68
 
69
+ ###Chatbot函数###
70
  def predict(message, history):
71
+ global initial_prompt
72
  history_openai_format = []
73
  history_openai_format.append({"role": "assistant", "content":initial_prompt})
74
  for human, assistant in history:
 
86
  if chunk.choices[0].delta.content is not None:
87
  partial_message = partial_message + chunk.choices[0].delta.content
88
  yield partial_message
89
+ ##############
90
 
91
+
92
+ CHAT_SECTION=gr.ChatInterface(
93
  predict,
94
  chatbot=gr.Chatbot(
95
  height=400,
96
  bubble_full_width=False,
97
+ #avatar_images=(os.path.join(os.path.dirname(__file__), "patient_ava.png"), os.path.join(os.path.dirname(__file__), "docter_ava.png")),
98
  likeable=True,
99
  ),
100
+ # textbox=gr.Textbox(placeholder="在此输入消息...",),
101
  retry_btn="🔄重新生成",
102
  undo_btn="↩️撤回信息",
103
  clear_btn="🗑️清空信息",
104
  stop_btn="停止生成",
105
  submit_btn="发送",
106
 
107
+ )
108
+
109
+ with gr.Blocks() as SCALE_AND_CONSULT:
110
+ ###量表环节
111
+ with gr.Column():
112
+ gr.Markdown("**在此项检测模式中,用户需要首先填写一份量表,随后系统将根据量表的填写情况对用户进行更细致的咨询,最终结合用户的回答状况给出诊断结果。**")
113
+ gr.Markdown("首先进行量表填写。本评定量表为临床上常用于抑郁症检测的SDS(Self-rating depression scale)量表,共有20个项目,请您根据最近一星期以来的实际感受,选择与您的情况最相符的答案。")
114
+ gr.Markdown("A:从无或偶尔(过去一周内,出现这类情况的日子不超过一天)")
115
+ gr.Markdown("B:有时(过去一周内,有1-2天有过这类情况)")
116
+ gr.Markdown("C:经常(过去一周内,有3-4天有过这类情况)")
117
+ gr.Markdown("D:总是如此(过去一周内,有5-7天有过类似情况)")
118
+ # gr.Markdown("评分范围与标准:")
119
+ # gr.Markdown("0-52: 无抑郁体验&emsp;&emsp;53-62: 轻度抑郁&emsp;&emsp;63-72: 中度抑郁&emsp;&emsp;72-80: 重度抑郁")
120
+ btn = gr.Button("继续")
121
+ with gr.Column(visible=False) as question:
122
+ r1 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "1.我感到心里沮丧,郁闷",type = "index")
123
+ r2 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "2.我感到早晨心情最好",type = "index")
124
+ r3 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "3.我要哭或想哭",type = "index")
125
+ r4 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "4.我夜间睡眠不好",type = "index")
126
+ r5 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "5.我吃饭像平常一样多",type = "index")
127
+ r6 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "6.我的性功能正常",type = "index")
128
+ r7 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "7.我感到体重减轻",type = "index")
129
+ r8 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "8.我为便秘烦恼",type = "index")
130
+ r9 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "9.我的心跳比平时快",type = "index")
131
+ r10 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "10.我无故感到疲劳",type = "index")
132
+ r11 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "11.我的头脑像往常一样清楚",type = "index")
133
+ r12 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "12.我做事情像平时一样不感到困难",type = "index")
134
+ r13 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "13.我坐卧不安,难以保持平静",type = "index")
135
+ r14 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "14.我对未来感到有希望",type = "index")
136
+ r15 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "15.我比平时更容易激怒",type = "index")
137
+ r16 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "16.我觉得决定什么事情很容易",type = "index")
138
+ r17 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "17.我感到自己是有用的和不可缺少的人",type = "index")
139
+ r18 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "18.我的生活很有意义",type = "index")
140
+ r19 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "19.假若我死了别人会过得更好",type = "index")
141
+ r20 = gr.Radio(["A.从无或偶尔","B.有时","C.经常","D.总是如此"],label = "20.我仍旧喜爱自己平时喜爱的东西",type = "index")
142
+ # btn2 = gr.Button("提交")
143
+ btn_json=gr.Button("提交问卷并进入咨询")
144
+ with gr.Column(visible=False) as JSON:
145
+ with gr.Row():
146
+ score = gr.Textbox(label="得分",visible=False)
147
+ with gr.Row():
148
+ output_json=gr.Textbox(label="scale2jsonprompt",visible=True)
149
+ with gr.Row():
150
+ with gr.Column():
151
+ CHAT_SECTION.render()
152
+ with gr.Row():
153
+ generate=gr.Button("结束聊天,生成最终结果(待开发)")
154
+
155
+ btn.click(visibility,outputs=question)
156
+ btn_json.click(scale2json,[r1,r2,r3,r4,r5,r6,r7,r8,r9,r10,r11,r12,r13,r14,r15,r16,r17,r18,r19,r20],[JSON,score,output_json])