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Update app_gradio.py
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@thomas-yanxin
thomas-yanxin authored Mar 31, 2023
1 parent 332db68 commit 2bd0052
Showing 1 changed file with 194 additions and 65 deletions.
259 changes: 194 additions & 65 deletions app_gradio.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,62 3,131 @@
import clueai
import torch
from transformers import T5Tokenizer, T5ForConditionalGeneration

tokenizer = T5Tokenizer.from_pretrained("ClueAI/ChatYuan-large-v2")
model = T5ForConditionalGeneration.from_pretrained("ClueAI/ChatYuan-large-v2")
# 该加载方式，在最大长度为512时 大约需要6G多显存
# 如显存不够，可采用以下方式加载，进一步减少显存需求，约为3G，但是请注意您的显卡是否支持此种推理方式
# model = T5ForConditionalGeneration.from_pretrained("ClueAI/ChatYuan-large-v2").half()
# 使用
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model.to(device)
model.half()

base_info = ""


base_info = "用户：你是谁？\n小元：我是元语智能公司研发的AI智能助手, 在不违反原则的情况下，我可以回答你的任何问题。\n"
def preprocess(text):
text = f"{base_info}{text}"
text = text.replace("\n", "\\n").replace("\t", "\\t")
return text
text = f"{base_info}{text}"
text = text.replace("\n", "\\n").replace("\t", "\\t")
return text


def postprocess(text):
return text.replace("\\n", "\n").replace("\\t", "\t").replace(' ',' ')#.replace(" ", " ")
return text.replace("\\n", "\n").replace("\\t", "\t").replace(
' ', ' ') #.replace(" ", " ")


generate_config = {
'do_sample': True,
'top_p': 0.9,
'top_k': 50,
'temperature': 0.7,
'num_beams': 1,
'max_length': 1024,
'min_length': 3,
'no_repeat_ngram_size': 5,
'length_penalty': 0.6,
'return_dict_in_generate': True,
'output_scores': True
}


generate_config = {'do_sample': True, 'top_p': 0.9, 'top_k': 50, 'temperature': 0.7,
'num_beams': 1, 'max_length': 1024, 'min_length': 3, 'no_repeat_ngram_size': 5,
'length_penalty': 0.6, 'return_dict_in_generate': True, 'output_scores': True}
def answer(text, sample=True, top_p=0.9, temperature=0.7):
'''sample：是否抽样。生成任务，可以设置为True;
def answer(
text,
top_p,
temperature,
sample=True,
):
'''sample：是否抽样。生成任务，可以设置为True;
top_p：0-1之间，生成的内容越多样'''
text = preprocess(text)
encoding = tokenizer(text=[text], truncation=True, padding=True, max_length=1024, return_tensors="pt").to(device)
if not sample:
out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=1024, num_beams=1, length_penalty=0.6)
else:
out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=1024, do_sample=True, top_p=top_p, temperature=temperature, no_repeat_ngram_size=12)
#out=model.generate(**encoding, **generate_config)
out_text = tokenizer.batch_decode(out["sequences"], skip_special_tokens=True)
return postprocess(out_text[0])
text = preprocess(text)
encoding = tokenizer(text=[text],
truncation=True,
padding=True,
max_length=1024,
return_tensors="pt").to(device)
if not sample:
out = model.generate(**encoding,
return_dict_in_generate=True,
output_scores=False,
max_new_tokens=1024,
num_beams=1,
length_penalty=0.6)
else:
out = model.generate(**encoding,
return_dict_in_generate=True,
output_scores=False,
max_new_tokens=1024,
do_sample=True,
top_p=top_p,
temperature=temperature,
no_repeat_ngram_size=12)
#out=model.generate(**encoding, **generate_config)
out_text = tokenizer.batch_decode(out["sequences"],
skip_special_tokens=True)
return postprocess(out_text[0])


def clear_session():
return '', None

def chatyuan_bot(input, history):

def chatyuan_bot(input, history, top_p, temperature, num):
history = history or []
if len(history) > 5:
history = history[-5:]
if len(history) > num:
history = history[-num:]

context = "\n".join([f"用户：{input_text}\n小元：{answer_text}" for input_text, answer_text in history])
context = "\n".join([
f"用户：{input_text}\n小元：{answer_text}"
for input_text, answer_text in history
])
#print(context)

input_text = context "\n用户：" input "\n小元："
input_text = input_text.strip()
output_text = answer(input_text)
output_text = answer(input_text, top_p, temperature)
print("open_model".center(20, "="))
print(f"{input_text}\n{output_text}")
#print("="*20)
history.append((input, output_text))
#print(history)
return history, history
return '', history, history


def chatyuan_bot_regenerate(input, history, top_p, temperature, num):

history = history or []

if history:
input = history[-1][0]
history = history[:-1]

if len(history) > num:
history = history[-num:]

context = "\n".join([
f"用户：{input_text}\n小元：{answer_text}"
for input_text, answer_text in history
])
#print(context)

input_text = context "\n用户：" input "\n小元："
input_text = input_text.strip()
output_text = answer(input_text, top_p, temperature)
print("open_model".center(20, "="))
print(f"{input_text}\n{output_text}")
history.append((input, output_text))
#print(history)
return '', history, history


block = gr.Blocks()

Expand All @@ -67,24 136,58 @@ def chatyuan_bot(input, history):
<font size=4>回答来自ChatYuan, 是模型生成的结果, 请谨慎辨别和参考, 不代表任何人观点 | Answer generated by ChatYuan model</font>
<font size=4>注意：gradio对markdown代码格式展示有限</font>
""")
chatbot = gr.Chatbot(label='ChatYuan')
with gr.Row():
with gr.Column(scale=3):
chatbot = gr.Chatbot(label='ChatYuan').style(height=400)

with gr.Column(scale=1):

num = gr.Slider(minimum=4,
maximum=10,
label="最大的对话轮数",
value=5,
step=1)
top_p = gr.Slider(minimum=0,
maximum=1,
label="top_p",
value=1,
step=0.1)
temperature = gr.Slider(minimum=0,
maximum=1,
label="temperature",
value=0.7,
step=0.1)
clear_history = gr.Button("👋 清除历史对话 | Clear History")
send = gr.Button("🚀 发送 | Send")
regenerate = gr.Button("🚀 重新生成本次结果 | regenerate")
message = gr.Textbox()
state = gr.State()
message.submit(chatyuan_bot, inputs=[message, state], outputs=[chatbot, state])
with gr.Row():
clear_history = gr.Button("👋 清除历史对话 | Clear")
clear = gr.Button('🧹 清除发送框 | Clear Input')
send = gr.Button("🚀 发送 | Send")

send.click(chatyuan_bot, inputs=[message, state], outputs=[chatbot, state])
clear.click(lambda: None, None, message, queue=False)
clear_history.click(fn=clear_session , inputs=[], outputs=[chatbot, state], queue=False)

message.submit(chatyuan_bot,
inputs=[message, state, top_p, temperature, num],
outputs=[message, chatbot, state])
regenerate.click(chatyuan_bot_regenerate,
inputs=[message, state, top_p, temperature, num],
outputs=[message, chatbot, state])
send.click(chatyuan_bot,
inputs=[message, state, top_p, temperature, num],
outputs=[message, chatbot, state])

clear_history.click(fn=clear_session,
inputs=[],
outputs=[chatbot, state],
queue=False)

def ChatYuan(api_key, text_prompt):

cl = clueai.Client(api_key,
check_api_key=True)
def ChatYuan(api_key, text_prompt, top_p):
generate_config = {
"do_sample": True,
"top_p": top_p,
"max_length": 128,
"min_length": 10,
"length_penalty": 1.0,
"num_beams": 1
}
cl = clueai.Client(api_key, check_api_key=True)
# generate a prediction for a prompt
# 需要返回得分的话，指定return_likelihoods="GENERATION"
prediction = cl.generate(model_name='ChatYuan-large', prompt=text_prompt)
Expand All @@ -95,25 198,29 @@ def ChatYuan(api_key, text_prompt):
response = "很抱歉，我无法回答这个问题"

return response

def chatyuan_bot_api(api_key, input, history):


def chatyuan_bot_api(api_key, input, history, top_p, num):
history = history or []

if len(history) > 5:
history = history[-5:]
if len(history) > num:
history = history[-num:]

context = "\n".join([f"用户：{input_text}\n小元：{answer_text}" for input_text, answer_text in history])
#print(context)
context = "\n".join([
f"用户：{input_text}\n小元：{answer_text}"
for input_text, answer_text in history
])

input_text = context "\n用户：" input "\n小元："
input_text = input_text.strip()
output_text = ChatYuan(api_key, input_text)
output_text = ChatYuan(api_key, input_text, top_p)
print("api".center(20, "="))
print(f"api_key:{api_key}\n{input_text}\n{output_text}")
#print("="*20)

history.append((input, output_text))
#print(history)
return history, history

return '', history, history


block = gr.Blocks()

Expand All @@ -123,19 230,40 @@ def chatyuan_bot_api(api_key, input, history):
<font size=4>注意：gradio对markdown代码格式展示有限</font>
<font size=4>在使用此功能前，你需要有个API key. API key 可以通过这个<a href='https://www.clueai.cn/' target="_blank">平台</a>获取</font>
""")
api_key = gr.inputs.Textbox(label="请输入你的api-key(必填)", default="", type='password')
chatbot = gr.Chatbot(label='ChatYuan')
with gr.Row():
with gr.Column(scale=3):
chatbot = gr.Chatbot(label='ChatYuan').style(height=400)

with gr.Column(scale=1):
api_key = gr.inputs.Textbox(label="请输入你的api-key(必填)",
default="",
type='password')
num = gr.Slider(minimum=4,
maximum=10,
label="最大的对话轮数",
value=5,
step=1)
top_p = gr.Slider(minimum=0,
maximum=1,
label="top_p",
value=1,
step=0.1)
clear_history = gr.Button("👋 清除历史对话 | Clear History")
send = gr.Button("🚀 发送 | Send")

message = gr.Textbox()
state = gr.State()
message.submit(chatyuan_bot_api, inputs=[api_key,message, state], outputs=[chatbot, state])
with gr.Row():
clear_history = gr.Button("👋 清除历史对话 | Clear Context")
clear = gr.Button('🧹 清除发送框 | Clear Input')
send = gr.Button("🚀 发送 | Send")
message.submit(chatyuan_bot_api,
inputs=[api_key, message, state, top_p, num],
outputs=[message, chatbot, state])

send.click(chatyuan_bot_api, inputs=[api_key,message, state], outputs=[chatbot, state])
clear.click(lambda: None, None, message, queue=False)
clear_history.click(fn=clear_session , inputs=[], outputs=[chatbot, state], queue=False)
send.click(chatyuan_bot_api,
inputs=[api_key, message, state, top_p, num],
outputs=[message, chatbot, state])
clear_history.click(fn=clear_session,
inputs=[],
outputs=[chatbot, state],
queue=False)

block = gr.Blocks()
with block as introduction:
Expand Down Expand Up @@ -176,6 304,7 @@ def chatyuan_bot_api(api_key, input, history):
<center><a href="https://clustrmaps.com/site/1bts0" title="Visit tracker"><img src="//www.clustrmaps.com/map_v2.png?d=ycVCe17noTYFDs30w7AmkFaE-TwabMBukDP1802_Lts&cl=ffffff" /></a></center>
""")


gui = gr.TabbedInterface(interface_list=[introduction,demo, demo_1], tab_names=["相关介绍","开源模型", "API调用"])
gui.launch(quiet=True,show_api=False, share = False)
gui = gr.TabbedInterface(
interface_list=[introduction, demo, demo_1],
tab_names=["相关介绍 | Introduction", "开源模型 | Online Demo", "API调用"])
gui.launch(quiet=True, show_api=False, share=True)

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