You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
240 lines
9.2 KiB
240 lines
9.2 KiB
2 years ago
|
# Copyright (c) Alibaba Cloud.
|
||
|
|
#
|
||
|
|
# This source code is licensed under the license found in the
|
||
|
|
# LICENSE file in the root directory of this source tree.
|
||
|
|
|
||
|
|
"""A simple web interactive chat demo based on gradio."""
|
||
|
|
|
||
|
|
from argparse import ArgumentParser
|
||
|
|
from pathlib import Path
|
||
|
|
|
||
|
|
import copy
|
||
|
|
import gradio as gr
|
||
|
|
import os
|
||
|
|
import re
|
||
|
|
import secrets
|
||
|
|
import tempfile
|
||
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||
|
|
from transformers.generation import GenerationConfig
|
||
|
|
|
||
|
|
DEFAULT_CKPT_PATH = 'Qwen/Qwen-VL-Chat'
|
||
|
|
BOX_TAG_PATTERN = r"<box>([\s\S]*?)</box>"
|
||
|
|
PUNCTUATION = "！？。＂＃＄％＆＇（）＊＋，－／：；＜＝＞＠［＼］＾＿｀｛｜｝～｟｠｢｣､、〃》「」『』【】〔〕〖〗〘〙〚〛〜〝〞〟〰〾〿–—‘’‛“”„‟…‧﹏."
|
||
|
|
|
||
|
|
|
||
|
|
def _get_args():
|
||
|
|
parser = ArgumentParser()
|
||
|
|
parser.add_argument("-c", "--checkpoint-path", type=str, default=DEFAULT_CKPT_PATH,
|
||
|
|
help="Checkpoint name or path, default to %(default)r")
|
||
|
|
parser.add_argument("--cpu-only", action="store_true", help="Run demo with CPU only")
|
||
|
|
|
||
|
|
parser.add_argument("--share", action="store_true", default=False,
|
||
|
|
help="Create a publicly shareable link for the interface.")
|
||
|
|
parser.add_argument("--inbrowser", action="store_true", default=False,
|
||
|
|
help="Automatically launch the interface in a new tab on the default browser.")
|
||
|
|
parser.add_argument("--server-port", type=int, default=8000,
|
||
|
|
help="Demo server port.")
|
||
|
|
parser.add_argument("--server-name", type=str, default="127.0.0.1",
|
||
|
|
help="Demo server name.")
|
||
|
|
|
||
|
|
args = parser.parse_args()
|
||
|
|
return args
|
||
|
|
|
||
|
|
|
||
|
|
def _load_model_tokenizer(args):
|
||
|
|
tokenizer = AutoTokenizer.from_pretrained(
|
||
|
|
args.checkpoint_path, trust_remote_code=True, resume_download=True,
|
||
|
|
)
|
||
|
|
|
||
|
|
if args.cpu_only:
|
||
|
|
device_map = "cpu"
|
||
|
|
else:
|
||
|
|
device_map = "cuda"
|
||
|
|
|
||
|
|
model = AutoModelForCausalLM.from_pretrained(
|
||
|
|
args.checkpoint_path,
|
||
|
|
device_map=device_map,
|
||
|
|
trust_remote_code=True,
|
||
|
|
resume_download=True,
|
||
|
|
).eval()
|
||
|
|
model.generation_config = GenerationConfig.from_pretrained(
|
||
|
|
args.checkpoint_path, trust_remote_code=True, resume_download=True,
|
||
|
|
)
|
||
|
|
|
||
|
|
return model, tokenizer
|
||
|
|
|
||
|
|
|
||
|
|
def _parse_text(text):
|
||
|
|
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("`", r"\`")
|
||
|
|
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 _launch_demo(args, model, tokenizer):
|
||
|
|
uploaded_file_dir = os.environ.get("GRADIO_TEMP_DIR") or str(
|
||
|
|
Path(tempfile.gettempdir()) / "gradio"
|
||
|
|
)
|
||
|
|
|
||
|
|
def predict(_chatbot, task_history):
|
||
|
|
chat_query = _chatbot[-1][0]
|
||
|
|
query = task_history[-1][0]
|
||
|
|
print("User: " + _parse_text(query))
|
||
|
|
history_cp = copy.deepcopy(task_history)
|
||
|
|
full_response = ""
|
||
|
|
|
||
|
|
history_filter = []
|
||
|
|
pic_idx = 1
|
||
|
|
pre = ""
|
||
|
|
for i, (q, a) in enumerate(history_cp):
|
||
|
|
if isinstance(q, (tuple, list)):
|
||
|
|
q = f'Picture {pic_idx}: <img>{q[0]}</img>'
|
||
|
|
pre += q + '\n'
|
||
|
|
pic_idx += 1
|
||
|
|
else:
|
||
|
|
pre += q
|
||
|
|
history_filter.append((pre, a))
|
||
|
|
pre = ""
|
||
|
|
history, message = history_filter[:-1], history_filter[-1][0]
|
||
|
|
response, history = model.chat(tokenizer, message, history=history)
|
||
|
|
image = tokenizer.draw_bbox_on_latest_picture(response, history)
|
||
|
|
if image is not None:
|
||
|
|
temp_dir = secrets.token_hex(20)
|
||
|
|
temp_dir = Path(uploaded_file_dir) / temp_dir
|
||
|
|
temp_dir.mkdir(exist_ok=True, parents=True)
|
||
|
|
name = f"tmp{secrets.token_hex(5)}.jpg"
|
||
|
|
filename = temp_dir / name
|
||
|
|
image.save(str(filename))
|
||
|
|
_chatbot[-1] = (_parse_text(chat_query), (str(filename),))
|
||
|
|
chat_response = response.replace("<ref>", "")
|
||
|
|
chat_response = chat_response.replace(r"</ref>", "")
|
||
|
|
chat_response = re.sub(BOX_TAG_PATTERN, "", chat_response)
|
||
|
|
if chat_response != "":
|
||
|
|
_chatbot.append((None, chat_response))
|
||
|
|
else:
|
||
|
|
_chatbot[-1] = (_parse_text(chat_query), response)
|
||
|
|
full_response = _parse_text(response)
|
||
|
|
|
||
|
|
task_history[-1] = (query, full_response)
|
||
|
|
print("Qwen-VL-Chat: " + _parse_text(full_response))
|
||
|
|
return _chatbot
|
||
|
|
|
||
|
|
def regenerate(_chatbot, task_history):
|
||
|
|
if not task_history:
|
||
|
|
return _chatbot
|
||
|
|
item = task_history[-1]
|
||
|
|
if item[1] is None:
|
||
|
|
return _chatbot
|
||
|
|
task_history[-1] = (item[0], None)
|
||
|
|
chatbot_item = _chatbot.pop(-1)
|
||
|
|
if chatbot_item[0] is None:
|
||
|
|
_chatbot[-1] = (_chatbot[-1][0], None)
|
||
|
|
else:
|
||
|
|
_chatbot.append((chatbot_item[0], None))
|
||
|
|
return predict(_chatbot, task_history)
|
||
|
|
|
||
|
|
def add_text(history, task_history, text):
|
||
|
|
task_text = text
|
||
|
|
if len(text) >= 2 and text[-1] in PUNCTUATION and text[-2] not in PUNCTUATION:
|
||
|
|
task_text = text[:-1]
|
||
|
|
history = history + [(_parse_text(text), None)]
|
||
|
|
task_history = task_history + [(task_text, None)]
|
||
|
|
return history, task_history, ""
|
||
|
|
|
||
|
|
def add_file(history, task_history, file):
|
||
|
|
history = history + [((file.name,), None)]
|
||
|
|
task_history = task_history + [((file.name,), None)]
|
||
|
|
return history, task_history
|
||
|
|
|
||
|
|
def reset_user_input():
|
||
|
|
return gr.update(value="")
|
||
|
|
|
||
|
|
def reset_state(task_history):
|
||
|
|
task_history.clear()
|
||
|
|
return []
|
||
|
|
|
||
|
|
with gr.Blocks() as demo:
|
||
|
|
gr.Markdown("""\
|
||
|
|
<p align="center"><img src="https://modelscope.cn/api/v1/models/qwen/Qwen-7B-Chat/repo?
|
||
|
|
Revision=master&FilePath=assets/logo.jpeg&View=true" style="height: 80px"/><p>""")
|
||
|
|
gr.Markdown("""<center><font size=8>Qwen-VL-Chat Bot</center>""")
|
||
|
|
gr.Markdown(
|
||
|
|
"""\
|
||
|
|
<center><font size=3>This WebUI is based on Qwen-VL-Chat, developed by Alibaba Cloud. \
|
||
|
|
(本WebUI基于Qwen-VL-Chat打造，实现聊天机器人功能。)</center>""")
|
||
|
|
gr.Markdown("""\
|
||
|
|
<center><font size=4>Qwen-VL <a href="https://modelscope.cn/models/qwen/Qwen-VL/summary">🤖 </a>
|
||
|
|
| <a href="https://huggingface.co/Qwen/Qwen-VL">🤗</a>  ｜
|
||
|
|
Qwen-VL-Chat <a href="https://modelscope.cn/models/qwen/Qwen-VL-Chat/summary">🤖 </a> |
|
||
|
|
<a href="https://huggingface.co/Qwen/Qwen-VL-Chat">🤗</a>  ｜
|
||
|
|
 <a href="https://github.com/QwenLM/Qwen-VL">Github</a></center>""")
|
||
|
|
|
||
|
|
chatbot = gr.Chatbot(label='Qwen-VL-Chat', elem_classes="control-height", height=750)
|
||
|
|
query = gr.Textbox(lines=2, label='Input')
|
||
|
|
task_history = gr.State([])
|
||
|
|
|
||
|
|
with gr.Row():
|
||
|
|
empty_bin = gr.Button("🧹 Clear History (清除历史)")
|
||
|
|
submit_btn = gr.Button("🚀 Submit (发送)")
|
||
|
|
regen_btn = gr.Button("🤔️ Regenerate (重试)")
|
||
|
|
addfile_btn = gr.UploadButton("📁 Upload (上传文件)", file_types=["image"])
|
||
|
|
|
||
|
|
submit_btn.click(add_text, [chatbot, task_history, query], [chatbot, task_history]).then(
|
||
|
|
predict, [chatbot, task_history], [chatbot], show_progress=True
|
||
|
|
)
|
||
|
|
submit_btn.click(reset_user_input, [], [query])
|
||
|
|
empty_bin.click(reset_state, [task_history], [chatbot], show_progress=True)
|
||
|
|
regen_btn.click(regenerate, [chatbot, task_history], [chatbot], show_progress=True)
|
||
|
|
addfile_btn.upload(add_file, [chatbot, task_history, addfile_btn], [chatbot, task_history], show_progress=True)
|
||
|
|
|
||
|
|
gr.Markdown("""\
|
||
|
|
<font size=2>Note: This demo is governed by the original license of Qwen-VL. \
|
||
|
|
We strongly advise users not to knowingly generate or allow others to knowingly generate harmful content, \
|
||
|
|
including hate speech, violence, pornography, deception, etc. \
|
||
|
|
(注：本演示受Qwen-VL的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，\
|
||
|
|
包括但不限于仇恨言论、暴力、色情、欺诈相关的有害信息。)""")
|
||
|
|
|
||
|
|
demo.queue().launch(
|
||
|
|
share=args.share,
|
||
|
|
inbrowser=args.inbrowser,
|
||
|
|
server_port=args.server_port,
|
||
|
|
server_name=args.server_name,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def main():
|
||
|
|
args = _get_args()
|
||
|
|
|
||
|
|
model, tokenizer = _load_model_tokenizer(args)
|
||
|
|
|
||
|
|
_launch_demo(args, model, tokenizer)
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == '__main__':
|
||
|
|
main()
|