Update web demo
This commit is contained in:
parent
34a25f9064
commit
9e18d611fc
22
README.md
22
README.md
@ -137,7 +137,11 @@ git clone https://github.com/THUDM/ChatGLM2-6B
|
|||||||
cd ChatGLM2-6B
|
cd ChatGLM2-6B
|
||||||
```
|
```
|
||||||
|
|
||||||
然后使用 pip 安装依赖:`pip install -r requirements.txt`,其中 `transformers` 库版本推荐为 `4.30.2`,`torch` 推荐使用 2.0 以上的版本,以获得最佳的推理性能。
|
然后使用 pip 安装依赖:
|
||||||
|
```
|
||||||
|
pip install -r requirements.txt
|
||||||
|
```
|
||||||
|
其中 `transformers` 库版本推荐为 `4.30.2`,`torch` 推荐使用 2.0 及以上的版本,以获得最佳的推理性能。
|
||||||
|
|
||||||
### 代码调用
|
### 代码调用
|
||||||
|
|
||||||
@ -188,23 +192,17 @@ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/THUDM/chatglm2-6b
|
|||||||
|
|
||||||
![web-demo](resources/web-demo.gif)
|
![web-demo](resources/web-demo.gif)
|
||||||
|
|
||||||
首先安装 Gradio:`pip install gradio`,然后运行仓库中的 [web_demo.py](web_demo.py):
|
可以通过以下命令启动基于 Streamlit 的网页版 demo:
|
||||||
|
|
||||||
```shell
|
```shell
|
||||||
python web_demo.py
|
streamlit run web_demo2.py
|
||||||
```
|
```
|
||||||
|
|
||||||
程序会运行一个 Web Server,并输出地址。在浏览器中打开输出的地址即可使用。
|
程序会运行一个 Web Server,并输出地址。在浏览器中打开输出的地址即可使用。
|
||||||
> 默认使用了 `share=False` 启动,不会生成公网链接。如有需要公网访问的需求,可以修改为 `share=True` 启动。
|
|
||||||
>
|
|
||||||
|
|
||||||
感谢 [@AdamBear](https://github.com/AdamBear) 实现了基于 Streamlit 的网页版 Demo `web_demo2.py`。使用时首先需要额外安装以下依赖:
|
|
||||||
|
[web_demo.py](./web_demo.py) 中提供了旧版基于 Gradio 的 web demo,可以通过如下命令运行:
|
||||||
```shell
|
```shell
|
||||||
pip install streamlit streamlit-chat
|
python web_demo.py
|
||||||
```
|
|
||||||
然后通过以下命令运行:
|
|
||||||
```shell
|
|
||||||
streamlit run web_demo2.py
|
|
||||||
```
|
```
|
||||||
经测试,如果输入的 prompt 较长的话,使用基于 Streamlit 的网页版 Demo 会更流畅。
|
经测试,如果输入的 prompt 较长的话,使用基于 Streamlit 的网页版 Demo 会更流畅。
|
||||||
|
|
||||||
|
@ -7,3 +7,4 @@ mdtex2html
|
|||||||
sentencepiece
|
sentencepiece
|
||||||
accelerate
|
accelerate
|
||||||
sse-starlette
|
sse-starlette
|
||||||
|
streamlit>=1.24.0
|
Binary file not shown.
Before Width: | Height: | Size: 2.2 MiB After Width: | Height: | Size: 2.6 MiB |
75
web_demo2.py
75
web_demo2.py
@ -1,6 +1,5 @@
|
|||||||
from transformers import AutoModel, AutoTokenizer
|
from transformers import AutoModel, AutoTokenizer
|
||||||
import streamlit as st
|
import streamlit as st
|
||||||
from streamlit_chat import message
|
|
||||||
|
|
||||||
|
|
||||||
st.set_page_config(
|
st.set_page_config(
|
||||||
@ -21,40 +20,9 @@ def get_model():
|
|||||||
return tokenizer, model
|
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()
|
tokenizer, model = get_model()
|
||||||
if history is None:
|
|
||||||
history = []
|
|
||||||
|
|
||||||
with container:
|
st.title("ChatGLM2-6B")
|
||||||
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 = st.sidebar.slider(
|
||||||
'max_length', 0, 32768, 8192, step=1
|
'max_length', 0, 32768, 8192, step=1
|
||||||
@ -63,13 +31,40 @@ top_p = st.sidebar.slider(
|
|||||||
'top_p', 0.0, 1.0, 0.8, step=0.01
|
'top_p', 0.0, 1.0, 0.8, step=0.01
|
||||||
)
|
)
|
||||||
temperature = st.sidebar.slider(
|
temperature = st.sidebar.slider(
|
||||||
'temperature', 0.0, 1.0, 0.95, step=0.01
|
'temperature', 0.0, 1.0, 0.8, step=0.01
|
||||||
)
|
)
|
||||||
|
|
||||||
if 'state' not in st.session_state:
|
if 'history' not in st.session_state:
|
||||||
st.session_state['state'] = []
|
st.session_state.history = []
|
||||||
|
|
||||||
if st.button("发送", key="predict"):
|
if 'past_key_values' not in st.session_state:
|
||||||
with st.spinner("AI正在思考,请稍等........"):
|
st.session_state.past_key_values = None
|
||||||
# text generation
|
|
||||||
st.session_state["state"] = predict(prompt_text, max_length, top_p, temperature, st.session_state["state"])
|
for i, (query, response) in enumerate(st.session_state.history):
|
||||||
|
with st.chat_message(name="user", avatar="user"):
|
||||||
|
st.markdown(query)
|
||||||
|
with st.chat_message(name="assistant", avatar="assistant"):
|
||||||
|
st.markdown(response)
|
||||||
|
with st.chat_message(name="user", avatar="user"):
|
||||||
|
input_placeholder = st.empty()
|
||||||
|
with st.chat_message(name="assistant", avatar="assistant"):
|
||||||
|
message_placeholder = st.empty()
|
||||||
|
|
||||||
|
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")
|
||||||
|
|
||||||
|
button = st.button("发送", key="predict")
|
||||||
|
|
||||||
|
if button:
|
||||||
|
input_placeholder.markdown(prompt_text)
|
||||||
|
history, past_key_values = st.session_state.history, st.session_state.past_key_values
|
||||||
|
for response, history, past_key_values in model.stream_chat(tokenizer, prompt_text, history,
|
||||||
|
past_key_values=past_key_values,
|
||||||
|
max_length=max_length, top_p=top_p,
|
||||||
|
temperature=temperature,
|
||||||
|
return_past_key_values=True):
|
||||||
|
message_placeholder.markdown(response)
|
||||||
|
|
||||||
|
st.session_state.history = history
|
||||||
|
st.session_state.past_key_values = past_key_values
|
||||||
|
Loading…
Reference in New Issue
Block a user