Hugging Face's logo

Spaces:
shengjh
/
bianque2.0
Runtime error

App Files Community
bianque2.0
File size: 5,975 Bytes 
bc4af1f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
# coding=utf-8
# Copyright 2023 South China University of Technology and 
# Engineering Research Ceter of Ministry of Education on Human Body Perception.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


# Author: Chen Yirong <eeyirongchen@mail.scut.edu.cn>
# Date: 2023.06.07

''' 运行方式
```bash
pip install streamlit # 第一次运行需要安装streamlit
pip install streamlit_chat # 第一次运行需要安装streamlit_chat
streamlit run bianque_v2_app.py --server.port 9005
```

## 测试访问

http://<your_ip>:9005

'''


import os
import torch
import streamlit as st
from streamlit_chat import message
from transformers import AutoModel, AutoTokenizer


os.environ['CUDA_VISIBLE_DEVICES'] = '0' # 默认使用0号显卡，避免Windows用户忘记修改该处
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

# 指定模型名称或路径
model_name_or_path = "scutcyr/BianQue-2"

tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)


def answer(user_history, bot_history, sample=True, top_p=0.7, temperature=0.95):
    '''sample：是否抽样。生成任务，可以设置为True;
    top_p=0.7, temperature=0.95时的生成效果较好
    top_p=1, temperature=0.7时提问能力会提升
    top_p：0-1之间，生成的内容越多样
    max_new_tokens=512 lost...'''

    if len(bot_history)>0:
        context = "\n".join([f"病人：{user_history[i]}\n医生：{bot_history[i]}" for i in range(len(bot_history))])
        input_text = context + "\n病人：" + user_history[-1] + "\n医生："
    else:
        input_text = "病人：" + user_history[-1] + "\n医生："
        #if user_history[-1] =="你好" or user_history[-1] =="你好！":
        return "我是利用人工智能技术，结合大数据训练得到的智能医疗问答模型扁鹊，你可以向我提问。"
            #return "我是生活空间健康对话大模型扁鹊，欢迎向我提问。"
    
    print(input_text)

    if not sample:
        response, history = model.chat(tokenizer, query=input_text, history=None, max_length=2048, num_beams=1, do_sample=False, top_p=top_p, temperature=temperature, logits_processor=None)
    else:
        response, history = model.chat(tokenizer, query=input_text, history=None, max_length=2048, num_beams=1, do_sample=True, top_p=top_p, temperature=temperature, logits_processor=None)

    print('医生: '+response)

    return response

st.set_page_config(
    page_title="扁鹊健康大模型（BianQue-2.0）",
    page_icon="🧊",
    layout="wide",
    initial_sidebar_state="expanded",
    menu_items={
        'About': """     
-   版本：扁鹊健康大模型（BianQue） V2.0.0 Beta
-   机构：广东省数字孪生人重点实验室
-   作者：陈艺荣、王振宇、徐志沛、方凱、李思航、王骏宏、邢晓芬、徐向民
	    """
    }
)

st.header("扁鹊健康大模型（BianQue-2.0）")

with st.expander("ℹ️ - 关于我们", expanded=False):
    st.write(
        """     
-   版本：扁鹊健康大模型（BianQue） V2.0.0 Beta
-   机构：广东省数字孪生人重点实验室
-   作者：陈艺荣、王振宇、徐志沛、方凱、李思航、王骏宏、邢晓芬、徐向民
	    """
    )

# https://docs.streamlit.io/library/api-reference/performance/st.cache_resource

@st.cache_resource
def load_model():
    model = AutoModel.from_pretrained(model_name_or_path, trust_remote_code=True).half()
    model.to(device)
    print('Model Load done!')
    return model

@st.cache_resource
def load_tokenizer():
    tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
    print('Tokenizer Load done!')
    return tokenizer

model = load_model()
tokenizer = load_tokenizer()

if 'generated' not in st.session_state:
    st.session_state['generated'] = []

if 'past' not in st.session_state:
    st.session_state['past'] = []


user_col, ensure_col = st.columns([5, 1])

def get_text():
    input_text = user_col.text_area("请在下列文本框输入您的咨询内容：","", key="input", placeholder="请输入您的咨询内容，并且点击Ctrl+Enter(或者发送按钮)确认内容")
    if ensure_col.button("发送", use_container_width=True):
        if input_text:
            return input_text  

user_input = get_text()

if user_input:
    st.session_state.past.append(user_input)
    output = answer(st.session_state['past'],st.session_state["generated"])
    st.session_state.generated.append(output)

if st.session_state['generated']:
    for i in range(len(st.session_state['generated'])):
        if i == 0:
            # 
            message(st.session_state['past'][i], is_user=True, key=str(i) + '_user', avatar_style="avataaars", seed=26)
            message(st.session_state["generated"][i]+"\n\n------------------\n以下回答由扁鹊健康模型自动生成，仅供参考！", key=str(i), avatar_style="avataaars", seed=5)
        else:
            message(st.session_state['past'][i], is_user=True, key=str(i) + '_user', avatar_style="avataaars", seed=26)
            #message(st.session_state["generated"][i], key=str(i))
            message(st.session_state["generated"][i], key=str(i), avatar_style="avataaars", seed=5)

if st.button("清理对话缓存"):
    # Clear values from *all* all in-memory and on-disk data caches:
    # i.e. clear values from both square and cube
    st.session_state['generated'] = []
    st.session_state['past'] = []