|
|
from transformers import AutoModel, AutoTokenizer
|
|
|
import streamlit as st
|
|
|
from streamlit_chat import message
|
|
|
|
|
|
|
|
|
st.set_page_config(
|
|
|
page_title="ChatGLM2-6b 演示",
|
|
|
page_icon=":robot:",
|
|
|
layout='wide'
|
|
|
)
|
|
|
|
|
|
|
|
|
@st.cache_resource
|
|
|
def get_model():
|
|
|
tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
|
|
|
model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).cuda()
|
|
|
# 多显卡支持，使用下面两行代替上面一行，将num_gpus改为你实际的显卡数量
|
|
|
# from utils import load_model_on_gpus
|
|
|
# model = load_model_on_gpus("THUDM/chatglm2-6b", num_gpus=2)
|
|
|
model = model.eval()
|
|
|
return tokenizer, model
|
|
|
|
|
|
|
|
|
MAX_TURNS = 20
|
|
|
MAX_BOXES = MAX_TURNS * 2
|
|
|
|
|
|
|
|
|
def predict(input, max_length, top_p, temperature, history=None):
|
|
|
tokenizer, model = get_model()
|
|
|
if history is None:
|
|
|
history = []
|
|
|
|
|
|
with container:
|
|
|
if len(history) > 0:
|
|
|
if len(history)>MAX_BOXES:
|
|
|
history = history[-MAX_TURNS:]
|
|
|
for i, (query, response) in enumerate(history):
|
|
|
message(query, avatar_style="big-smile", key=str(i) + "_user")
|
|
|
message(response, avatar_style="bottts", key=str(i))
|
|
|
|
|
|
message(input, avatar_style="big-smile", key=str(len(history)) + "_user")
|
|
|
st.write("AI正在回复:")
|
|
|
with st.empty():
|
|
|
for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
|
|
|
temperature=temperature):
|
|
|
query, response = history[-1]
|
|
|
st.write(response)
|
|
|
|
|
|
return history
|
|
|
|
|
|
|
|
|
container = st.container()
|
|
|
|
|
|
# create a prompt text for the text generation
|
|
|
prompt_text = st.text_area(label="用户命令输入",
|
|
|
height = 100,
|
|
|
placeholder="请在这儿输入您的命令")
|
|
|
|
|
|
max_length = st.sidebar.slider(
|
|
|
'max_length', 0, 32768, 8192, step=1
|
|
|
)
|
|
|
top_p = st.sidebar.slider(
|
|
|
'top_p', 0.0, 1.0, 0.8, step=0.01
|
|
|
)
|
|
|
temperature = st.sidebar.slider(
|
|
|
'temperature', 0.0, 1.0, 0.95, step=0.01
|
|
|
)
|
|
|
|
|
|
if 'state' not in st.session_state:
|
|
|
st.session_state['state'] = []
|
|
|
|
|
|
if st.button("发送", key="predict"):
|
|
|
with st.spinner("AI正在思考，请稍等........"):
|
|
|
# text generation
|
|
|
st.session_state["state"] = predict(prompt_text, max_length, top_p, temperature, st.session_state["state"])
|
