import os import numpy as np import re import secrets import tempfile import requests from http import HTTPStatus from argparse import ArgumentParser from pathlib import Path import gradio as gr import oss2 from dashscope import MultiModalConversation import dashscope # Install required packages os.system('pip install dashscope modelscope oss2 -U') # Load environment variables API_KEY = os.environ['API_KEY'] ENDPOINT = os.environ['ENDPOINT'] AK_ID = os.environ['AK_ID'] AK = os.environ['AK'] BUCKET_NAME = os.environ['BUCKET_NAME'] dashscope.api_key = API_KEY endpoint = ENDPOINT auth = oss2.Auth(AK_ID, AK) bucket = oss2.Bucket(auth, endpoint, BUCKET_NAME) REVISION = 'v1.0.4' BOX_TAG_PATTERN = r"([\s\S]*?)" PUNCTUATION = "！？。＂＃＄％＆＇（）＊＋，－／：；＜＝＞＠［＼］＾＿｀｛｜｝～｟｠｢｣､、〃》「」『』【】〔〕〖〗〘〙〚〛〜〝〞〟〰〾〿–—‘’‛“”„‟…‧﹏." def _get_args(): parser = ArgumentParser() parser.add_argument("--revision", type=str, default=REVISION) 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=7860, help="Demo server port.") parser.add_argument("--server-name", type=str, default="127.0.0.1", help="Demo server name.") return parser.parse_args() 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'
'
            else:
                lines[i] = "
" else: if i > 0 and count % 2 == 1: line = re.sub(r'[<>]', lambda x: f'&{x.group(0)};', line) line = line.replace(" ", " ") lines[i] = "
" + line return "".join(lines) def _remove_image_special(text): text = text.replace('', '').replace('', '') return re.sub(r'.*?(|$)', '', text) def is_video_file(filename): video_extensions = ['.mp4', '.avi', '.mkv', '.mov', '.wmv', '.flv', '.webm', '.mpeg'] return any(filename.lower().endswith(ext) for ext in video_extensions) def _launch_demo(args): 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] if not chat_query: _chatbot.pop() task_history.pop() return _chatbot print("User: " + _parse_text(query)) history_cp = copy.deepcopy(task_history) full_response = "" messages = [] content = [] for q, a in history_cp: if isinstance(q, (tuple, list)): if is_video_file(q[0]): key = q[0].split(os.sep)[-2] bucket.put_object_from_file(key, q[0]) url = bucket.sign_url('GET', key, 3600) content.append({'video': url}) else: content.append({'image': f'file://{q[0]}'}) else: content.append({'text': q}) messages.append({'role': 'user', 'content': content}) messages.append({'role': 'assistant', 'content': [{'text': a}]}) content = [] messages.pop() responses = MultiModalConversation.call(model='qwen-vl-max-0809', messages=messages, stream=True) for response in responses: if response.status_code != HTTPStatus.OK: raise HTTPError(f'response.code: {response.code}\nresponse.message: {response.message}') response_content = response.output.choices[0].message.content response_text = [ele.get('text', '') for ele in response_content] response_text = ''.join(response_text) _chatbot[-1] = (_parse_text(chat_query), _remove_image_special(response_text)) yield _chatbot if len(response_content) > 1: result_image = response_content[-1]['result_image'] resp = requests.get(result_image) os.makedirs(uploaded_file_dir, exist_ok=True) filename = os.path.join(uploaded_file_dir, f"tmp{secrets.token_hex(20)}.jpg") with open(filename, 'wb') as f: f.write(resp.content) response_text = ''.join(r.get('box', '') for r in response_content[:-1]) _chatbot.append((None, (filename,))) else: response_text = response_content[0]['text'] _chatbot[-1] = (_parse_text(chat_query), response_text) full_response = _parse_text(response_text) task_history[-1] = (query, full_response) print("Qwen2-VL-Chat: " + _parse_text(full_response)) yield _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)) _chatbot_gen = predict(_chatbot, task_history) for _chatbot in _chatbot_gen: yield _chatbot def add_text(history, task_history, text): task_text = text history = history or [] task_history = task_history or [] history.append((_parse_text(text), None)) task_history.append((task_text, None)) return history, task_history, "" def add_file(history, task_history, file): history = history or [] task_history = task_history or [] history.append(((file.name,), None)) task_history.append(((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("""

""") gr.Markdown("""
Qwen2-VL-72B
""") gr.Markdown("""
This WebUI is based on Qwen2-VL-72B, developed by Alibaba Cloud.
""") gr.Markdown("""
本WebUI基于Qwen2-VL-72B。
""") chatbot = gr.Chatbot(label='Qwen2-VL-72B', elem_classes="control-height", height=500) query = gr.Textbox(lines=2, label='Input') task_history = gr.State([]) with gr.Row(): addfile_btn = gr.UploadButton("📁 Upload (上传文件)", file_types=["image", "video"]) submit_btn = gr.Button("🚀 Submit (发送)") regen_btn = gr.Button("🤔️ Regenerate (重试)") empty_bin = gr.Button("🧹 Clear History (清除历史)") submit_btn.click(add_text, [chatbot, task_history, query], [chatbot, task_history], concurrency_limit=40).then( predict, [chatbot, task_history], [chatbot], show_progress=True ) submit_btn.click(reset_user_input, [], [query], concurrency_limit=40) empty_bin.click(reset_state, [task_history], [chatbot], show_progress=True, concurrency_limit=40) regen_btn.click(regenerate, [chatbot, task_history], [chatbot], show_progress=True, concurrency_limit=40) addfile_btn.upload(add_file, [chatbot, task_history, addfile_btn], [chatbot, task_history], show_progress=True, concurrency_limit=40) gr.Markdown("""Note: This demo is governed by the original license of Qwen2-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Qwen2-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(api_open=False, default_concurrency_limit=40).launch( share=args.share, max_threads=40, # Uncomment if needed: # inbrowser=args.inbrowser, # server_port=args.server_port, # server_name=args.server_name, ) def main(): args = _get_args() _launch_demo(args) if __name__ == '__main__': main()