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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 <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 | |
| 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 | |
| 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'] = [] | |