init

app.py

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+# 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 <[email protected]>
+# 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'] = []

requirements.txt

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+protobuf
+transformers==4.28.0
+cpm_kernels
+torch>=1.10
+gradio
+mdtex2html
+sentencepiece
+accelerate