mirror of https://github.com/THUDM/ChatGLM-6B
Use chatbot web demo
duzx16
parent
40d83f32fe
commit
2833546339
104
web_demo.py
104
web_demo.py
|
|
@ -1,45 +1,101 @@
|
|||
from transformers import AutoModel, AutoTokenizer
|
||||
import gradio as gr
|
||||
import mdtex2html
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
|
||||
model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
|
||||
model = model.eval()
|
||||
|
||||
MAX_TURNS = 20
|
||||
MAX_BOXES = MAX_TURNS * 2
|
||||
"""Override Chatbot.postprocess"""
|
||||
|
||||
|
||||
def predict(input, max_length, top_p, temperature, history=None):
|
||||
if history is None:
|
||||
history = []
|
||||
def postprocess(self, y):
|
||||
if y is None:
|
||||
return []
|
||||
for i, (message, response) in enumerate(y):
|
||||
y[i] = (
|
||||
None if message is None else mdtex2html.convert((message)),
|
||||
None if response is None else mdtex2html.convert(response),
|
||||
)
|
||||
return y
|
||||
|
||||
|
||||
gr.Chatbot.postprocess = postprocess
|
||||
|
||||
|
||||
def parse_text(text):
|
||||
"""copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
|
||||
lines = text.split("\n")
|
||||
lines = [line for line in lines if line != ""]
|
||||
count = 0
|
||||
for i, line in enumerate(lines):
|
||||
if "```" in line:
|
||||
count += 1
|
||||
items = line.split('`')
|
||||
if count % 2 == 1:
|
||||
lines[i] = f'<pre><code class="language-{items[-1]}">'
|
||||
else:
|
||||
lines[i] = f'<br></code></pre>'
|
||||
else:
|
||||
if i > 0:
|
||||
if count % 2 == 1:
|
||||
line = line.replace("`", "\`")
|
||||
line = line.replace("<", "<")
|
||||
line = line.replace(">", ">")
|
||||
line = line.replace(" ", " ")
|
||||
line = line.replace("*", "*")
|
||||
line = line.replace("_", "_")
|
||||
line = line.replace("-", "-")
|
||||
line = line.replace(".", ".")
|
||||
line = line.replace("!", "!")
|
||||
line = line.replace("(", "(")
|
||||
line = line.replace(")", ")")
|
||||
line = line.replace("$", "$")
|
||||
lines[i] = "<br>"+line
|
||||
text = "".join(lines)
|
||||
return text
|
||||
|
||||
|
||||
def predict(input, chatbot, max_length, top_p, temperature, history):
|
||||
chatbot.append((parse_text(input), ""))
|
||||
for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
|
||||
temperature=temperature):
|
||||
updates = []
|
||||
for query, response in history:
|
||||
updates.append(gr.update(visible=True, value="用户：" + query))
|
||||
updates.append(gr.update(visible=True, value="ChatGLM-6B：" + response))
|
||||
if len(updates) < MAX_BOXES:
|
||||
updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
|
||||
yield [history] + updates
|
||||
chatbot[-1] = (parse_text(input), parse_text(response))
|
||||
|
||||
yield chatbot, history
|
||||
|
||||
|
||||
def reset_user_input():
|
||||
return gr.update(value='')
|
||||
|
||||
|
||||
def reset_state():
|
||||
return [], []
|
||||
|
||||
|
||||
with gr.Blocks() as demo:
|
||||
state = gr.State([])
|
||||
text_boxes = []
|
||||
for i in range(MAX_BOXES):
|
||||
if i % 2 == 0:
|
||||
text_boxes.append(gr.Markdown(visible=False, label="提问："))
|
||||
else:
|
||||
text_boxes.append(gr.Markdown(visible=False, label="回复："))
|
||||
gr.HTML("""<h1 align="center">ChatGLM</h1>""")
|
||||
|
||||
chatbot = gr.Chatbot()
|
||||
with gr.Row():
|
||||
with gr.Column(scale=4):
|
||||
txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter", lines=11).style(
|
||||
container=False)
|
||||
with gr.Column(scale=12):
|
||||
user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style(
|
||||
container=False)
|
||||
with gr.Column(min_width=32, scale=1):
|
||||
submitBtn = gr.Button("Submit", variant="primary")
|
||||
with gr.Column(scale=1):
|
||||
emptyBtn = gr.Button("Clear History")
|
||||
max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
|
||||
top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True)
|
||||
temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
|
||||
button = gr.Button("Generate")
|
||||
button.click(predict, [txt, max_length, top_p, temperature, state], [state] + text_boxes)
|
||||
demo.queue().launch(share=False, inbrowser=True)
|
||||
|
||||
history = gr.State([])
|
||||
|
||||
submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history], [chatbot, history],
|
||||
show_progress=True)
|
||||
submitBtn.click(reset_user_input, [], [user_input])
|
||||
|
||||
emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
|
||||
|
||||
demo.queue().launch(share=True, inbrowser=True)
|
||||
|
|
|
|||
101
web_demo3.py
101
web_demo3.py
|
|
@ -1,101 +0,0 @@
|
|||
from transformers import AutoModel, AutoTokenizer
|
||||
import gradio as gr
|
||||
import mdtex2html
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
|
||||
model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
|
||||
model = model.eval()
|
||||
|
||||
"""Override Chatbot.postprocess"""
|
||||
|
||||
|
||||
def postprocess(self, y):
|
||||
if y is None:
|
||||
return []
|
||||
for i, (message, response) in enumerate(y):
|
||||
y[i] = (
|
||||
None if message is None else mdtex2html.convert((message)),
|
||||
None if response is None else mdtex2html.convert(response),
|
||||
)
|
||||
return y
|
||||
|
||||
|
||||
gr.Chatbot.postprocess = postprocess
|
||||
|
||||
|
||||
def parse_text(text):
|
||||
"""copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
|
||||
lines = text.split("\n")
|
||||
lines = [line for line in lines if line != ""]
|
||||
count = 0
|
||||
for i, line in enumerate(lines):
|
||||
if "```" in line:
|
||||
count += 1
|
||||
items = line.split('`')
|
||||
if count % 2 == 1:
|
||||
lines[i] = f'<pre><code class="language-{items[-1]}">'
|
||||
else:
|
||||
lines[i] = f'<br></code></pre>'
|
||||
else:
|
||||
if i > 0:
|
||||
if count % 2 == 1:
|
||||
line = line.replace("`", "\`")
|
||||
line = line.replace("<", "<")
|
||||
line = line.replace(">", ">")
|
||||
line = line.replace(" ", " ")
|
||||
line = line.replace("*", "*")
|
||||
line = line.replace("_", "_")
|
||||
line = line.replace("-", "-")
|
||||
line = line.replace(".", ".")
|
||||
line = line.replace("!", "!")
|
||||
line = line.replace("(", "(")
|
||||
line = line.replace(")", ")")
|
||||
line = line.replace("$", "$")
|
||||
lines[i] = "<br>"+line
|
||||
text = "".join(lines)
|
||||
return text
|
||||
|
||||
|
||||
def predict(input, chatbot, max_length, top_p, temperature, history):
|
||||
chatbot.append((parse_text(input), ""))
|
||||
for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
|
||||
temperature=temperature):
|
||||
chatbot[-1] = (parse_text(input), parse_text(response))
|
||||
|
||||
yield chatbot, history
|
||||
|
||||
|
||||
def reset_user_input():
|
||||
return gr.update(value='')
|
||||
|
||||
|
||||
def reset_state():
|
||||
return [], []
|
||||
|
||||
|
||||
with gr.Blocks() as demo:
|
||||
gr.HTML("""<h1 align="center">ChatGLM</h1>""")
|
||||
|
||||
chatbot = gr.Chatbot()
|
||||
with gr.Row():
|
||||
with gr.Column(scale=4):
|
||||
with gr.Column(scale=12):
|
||||
user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style(
|
||||
container=False)
|
||||
with gr.Column(min_width=32, scale=1):
|
||||
submitBtn = gr.Button("Submit", variant="primary")
|
||||
with gr.Column(scale=1):
|
||||
emptyBtn = gr.Button("Clear History")
|
||||
max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
|
||||
top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True)
|
||||
temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
|
||||
|
||||
history = gr.State([])
|
||||
|
||||
submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history], [chatbot, history],
|
||||
show_progress=True)
|
||||
submitBtn.click(reset_user_input, [], [user_input])
|
||||
|
||||
emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
|
||||
|
||||
demo.queue().launch(share=True, inbrowser=True)
|
||||
|
|
@ -0,0 +1,45 @@
|
|||
from transformers import AutoModel, AutoTokenizer
|
||||
import gradio as gr
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
|
||||
model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
|
||||
model = model.eval()
|
||||
|
||||
MAX_TURNS = 20
|
||||
MAX_BOXES = MAX_TURNS * 2
|
||||
|
||||
|
||||
def predict(input, max_length, top_p, temperature, history=None):
|
||||
if history is None:
|
||||
history = []
|
||||
for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
|
||||
temperature=temperature):
|
||||
updates = []
|
||||
for query, response in history:
|
||||
updates.append(gr.update(visible=True, value="用户：" + query))
|
||||
updates.append(gr.update(visible=True, value="ChatGLM-6B：" + response))
|
||||
if len(updates) < MAX_BOXES:
|
||||
updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
|
||||
yield [history] + updates
|
||||
|
||||
|
||||
with gr.Blocks() as demo:
|
||||
state = gr.State([])
|
||||
text_boxes = []
|
||||
for i in range(MAX_BOXES):
|
||||
if i % 2 == 0:
|
||||
text_boxes.append(gr.Markdown(visible=False, label="提问："))
|
||||
else:
|
||||
text_boxes.append(gr.Markdown(visible=False, label="回复："))
|
||||
|
||||
with gr.Row():
|
||||
with gr.Column(scale=4):
|
||||
txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter", lines=11).style(
|
||||
container=False)
|
||||
with gr.Column(scale=1):
|
||||
max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
|
||||
top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True)
|
||||
temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
|
||||
button = gr.Button("Generate")
|
||||
button.click(predict, [txt, max_length, top_p, temperature, state], [state] + text_boxes)
|
||||
demo.queue().launch(share=False, inbrowser=True)
|
||||
Loading…
Reference in New Issue