import os import json import gradio as gr import requests import csv import argparse import shutil from vlog4chat import Vlogger4chat from vlog4debate import Debate from utils import download_video #prompt_templates = {"Default ChatGPT": ""} parser = argparse.ArgumentParser() parser.add_argument('--video_path', default='./training.mp4') parser.add_argument('--alpha', default=10, type=int, help='Determine the maximum segment number for KTS algorithm, the larger the value, the fewer segments.') parser.add_argument('--beta', default=1, type=int, help='The smallest time gap between successive clips, in seconds.') parser.add_argument('--data_dir', default='./', type=str, help='Directory for saving videos and logs.') parser.add_argument('--tmp_dir', default='./', type=str, help='Directory for saving intermediate files.') # * Models settings * parser.add_argument('--openai_api_key', default='xxx', type=str, help='OpenAI API key') parser.add_argument('--image_caption', action='store_true', dest='image_caption', default=True, help='Set this flag to True if you want to use BLIP Image Caption') parser.add_argument('--dense_caption', action='store_true', dest='dense_caption', default=True, help='Set this flag to True if you want to use Dense Caption') parser.add_argument('--feature_extractor', default='./clip-vit-base-patch32', help='Select the feature extractor model for video segmentation') parser.add_argument('--feature_extractor_device', choices=['cuda', 'cpu'], default='cuda', help='Select the device: cuda or cpu') parser.add_argument('--image_captioner', choices=['blip2-opt', 'blip2-flan-t5', 'blip'], dest='captioner_base_model', default='blip2-opt', help='blip2 requires 15G GPU memory, blip requires 6G GPU memory') parser.add_argument('--image_captioner_device', choices=['cuda', 'cpu'], default='cuda', help='Select the device: cuda or cpu, gpu memory larger than 14G is recommended') parser.add_argument('--dense_captioner_device', choices=['cuda', 'cpu'], default='cuda', help='Select the device: cuda or cpu, < 6G GPU is not recommended>') parser.add_argument('--audio_translator', default='large') parser.add_argument('--audio_translator_device', choices=['cuda', 'cpu'], default='cuda') parser.add_argument('--gpt_version', choices=['gpt-3.5-turbo'], default='gpt-3.5-turbo') args = parser.parse_args() vlogger = Vlogger4chat(args) def get_empty_state(): return {"total_tokens": 0, "messages": []} def submit_message(prompt, state): history = state['messages'] if not prompt: return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], state prompt_msg = { "role": "user", "content": prompt } try: history.append(prompt_msg) answer = vlogger.chat2video(prompt) history.append({"role": "system", "content": answer}) except Exception as e: history.append(prompt_msg) history.append({ "role": "system", "content": f"Error: {e}" }) chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)] return '', chat_messages, state def submit_message_debate(prompt, state): history = state['messages'] if not prompt: return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], state prompt_msg = { "role": "user", "content": prompt } try: history.append(prompt_msg) debate_topic = "" while debate_topic == "": debate_topic = prompt config = json.load(open("./config4all.json", "r")) config['debate_topic'] = debate_topic debate = Debate(num_players=3, config=config, temperature=0, sleep_time=0) answer = debate.run() #chat_messages = [(res["debate_topic"]), (res["base_answer"]), (res["debate_answer"]), (res["Reason"])] history.append({"role": "system", "content": answer}) except Exception as e: history.append(prompt_msg) history.append({ "role": "system", "content": f"Error: {e}" }) chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)] return '', chat_messages, state def clear_conversation(): vlogger.clean_history() return gr.update(value=None, visible=True), gr.update(value=None, visible=True), gr.update(value=None, interactive=True), None, gr.update(value=None, visible=True), get_empty_state() # download video from any online URL def subvid_fn(vid): print(vid) save_path = download_video(vid) return gr.update(value=save_path) # 本地上传,适用于Running on local URL: http://127.0.0.1:6006 def uploaded_video(video_file): UPLOAD_FOLDER = "./" if not os.path.exists(UPLOAD_FOLDER): os.mkdir(UPLOAD_FOLDER) shutil.copy(video_file, UPLOAD_FOLDER) gr.Info("File Uploaded!!!") save_path = os.path.join(UPLOAD_FOLDER, os.path.basename(video_file)) return gr.update(value=save_path) def vlog_fn(vid_path): print(vid_path) if vid_path is None: log_text = "====== Please choose existing video from the library or provide video URL 🤔=====" else: log_list = vlogger.video2log(vid_path) log_text = "\n".join(log_list) return gr.update(value=log_text, visible=True) # 初始化一个空的答案记录字典 answers = {} # 定义处理用户选择的函数 def submit_answers_pretest(question1, question2, question3, question4, question5, question6, question7, question8, question9, question10): answers['Question 1'] = question1 answers['Question 2'] = question2 answers['Question 3'] = question3 answers['Question 4'] = question4 answers['Question 5'] = question5 answers['Question 6'] = question6 answers['Question 7'] = question7 answers['Question 8'] = question8 answers['Question 9'] = question9 answers['Question 10'] = question10 # 可以将结果保存到文件 with open('answers4pretest.txt', 'a') as f: f.write(f"Question 1: {question1}\n") f.write(f"Question 2: {question2}\n") f.write(f"Question 3: {question3}\n") f.write(f"Question 4: {question4}\n") f.write(f"Question 5: {question5}\n") f.write(f"Question 6: {question6}\n") f.write(f"Question 7: {question7}\n") f.write(f"Question 8: {question8}\n") f.write(f"Question 9: {question9}\n") f.write(f"Question 10: {question10}\n\n") # 返回一个确认消息 return "谢谢你提交答案!" def submit_answers_posttest(question1, question2, question3, question4, question5, question6, question7, question8, question9, question10): answers['Question 1'] = question1 answers['Question 2'] = question2 answers['Question 3'] = question3 answers['Question 4'] = question4 answers['Question 5'] = question5 answers['Question 6'] = question6 answers['Question 7'] = question7 answers['Question 8'] = question8 answers['Question 9'] = question9 answers['Question 10'] = question10 # 可以将结果保存到文件 with open('answers4posttest.txt', 'a') as f: f.write(f"Question 1: {question1}\n") f.write(f"Question 2: {question2}\n") f.write(f"Question 3: {question3}\n") f.write(f"Question 4: {question4}\n") f.write(f"Question 5: {question5}\n") f.write(f"Question 6: {question6}\n") f.write(f"Question 7: {question7}\n") f.write(f"Question 8: {question8}\n") f.write(f"Question 9: {question9}\n") f.write(f"Question 10: {question10}\n\n") # 返回一个确认消息 return "谢谢你提交答案!" css = """ #col-container {max-width: 80%; margin-left: auto; margin-right: auto;} #video_inp {min-height: 100px} #chatbox {min-height: 100px;} #header {text-align: center;} #hint {font-size: 1.0em; padding: 0.5em; margin: 0;} .message { font-size: 1.2em; } """ with gr.Blocks(css=css) as demo: with gr.Tabs(): # 第一个标签页 with gr.TabItem("第一步(预先测试)"): gr.Markdown("## Survey: Please answer the following questions") # 问题1 question1 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="1. What is your favorite color?", ) # 问题2 question2 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="2. What is your preferred mode of transport?", ) # 问题3 question3 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="3. Which type of cuisine do you prefer?", ) # 问题4 question4 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="4. What is your favorite color?", ) # 问题5 question5 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="5. What is your preferred mode of transport?", ) # 问题6 question6 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="6. Which type of cuisine do you prefer?", ) # 问题7 question7 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="7. Which type of cuisine do you prefer?", ) # 问题8 question8 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="8. What is your favorite color?", ) # 问题9 question9 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="9. What is your preferred mode of transport?", ) # 问题10 question10 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="10. Which type of cuisine do you prefer?", ) # 提交按钮 submit_button = gr.Button("Submit Answers") # 显示结果 output = gr.Textbox(label="Message") # 点击提交按钮时,调用submit_answers函数 submit_button.click( submit_answers_pretest, inputs=[question1, question2, question3, question4, question5, question6, question7, question8, question9, question10], outputs=output ) # 第二个标签页 with gr.TabItem("第二步(VLog使用)"): state = gr.State(get_empty_state()) with gr.Column(elem_id="col-container"): gr.Markdown("""## 🎞️ 视频Chat: Powered by CLIP, BLIP2, GRIT, RAM++, PaddleOCR, Whisper, Custom LLMs and LangChain""", elem_id="header") with gr.Row(): with gr.Column(): video_inp = gr.Video(label="video_input") # 设置点击事件,点击按钮后保存上传的视频 #save_btn = gr.Button("Upload Video") # 本地上传,适用于Running on local URL: http://127.0.0.1:6006 #save_btn.click(uploaded_video, [video_inp], [video_inp]) gr.Markdown("请在下方输入需要播放的视频完整网址, *e.g.* *B站地址*", elem_id="hint") with gr.Row(): video_id = gr.Textbox(value="", placeholder="Download video url", show_label=False) vidsub_btn = gr.Button("上传网站视频") chatbot = gr.Chatbot(elem_id="chatbox") input_message = gr.Textbox(show_label=False, placeholder="输入文字并按回车", visible=True) btn_submit = gr.Button("提问视频内容") gr.Markdown("如果对上面的回答不满意,请在下方输入需要辩论的问题, *e.g.* *方差越小越好?*", elem_id="hint") #chatbot_debate = gr.Chatbot(elem_id="chatbox") input_message_debate = gr.Textbox(show_label=False, placeholder="输入文字并按回车", visible=True) btn_submit_debate = gr.Button("发起问题辩论") btn_clear_conversation = gr.Button("🔃 开始新的对话") with gr.Column(): vlog_btn = gr.Button("点击此处,生成视频日志") vlog_outp = gr.Textbox(label="Document output", lines=60) total_tokens_str = gr.Markdown(elem_id="total_tokens_str") gr.Markdown("请点击下方视频(任意选择一个视频进行播放)", elem_id="hint") examples = gr.Examples( examples=[ ["BV11H4y1F7uH.mp4"], ], inputs=[video_inp], ) gr.HTML('''


You can duplicate this Space to skip the queue:Duplicate Space
''') btn_submit.click(submit_message, [input_message, state], [input_message, chatbot]) input_message.submit(submit_message, [input_message, state], [input_message, chatbot]) btn_submit_debate.click(submit_message_debate, [input_message_debate, state], [input_message_debate, chatbot]) input_message_debate.submit(submit_message_debate, [input_message_debate, state], [input_message_debate, chatbot]) btn_clear_conversation.click(clear_conversation, [], [input_message, input_message_debate, video_inp, chatbot, vlog_outp, state]) vlog_btn.click(vlog_fn, [video_inp], [vlog_outp]) vidsub_btn.click(subvid_fn, [video_id], [video_inp]) # 第三个标签页 with gr.TabItem("第三步(再次测试)"): gr.Markdown("## Survey: Please answer the following questions") # 问题1 question1 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="1. What is your favorite color?", ) # 问题2 question2 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="2. What is your preferred mode of transport?", ) # 问题3 question3 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="3. Which type of cuisine do you prefer?", ) # 问题4 question4 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="4. What is your favorite color?", ) # 问题5 question5 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="5. What is your preferred mode of transport?", ) # 问题6 question6 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="6. Which type of cuisine do you prefer?", ) # 问题7 question7 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="7. Which type of cuisine do you prefer?", ) # 问题8 question8 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="8. What is your favorite color?", ) # 问题9 question9 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="9. What is your preferred mode of transport?", ) # 问题10 question10 = gr.Radio( choices=["1", "2", "3", "4", "5"], label="10. Which type of cuisine do you prefer?", ) # 提交按钮 submit_button = gr.Button("Submit Answers") # 显示结果 output = gr.Textbox(label="Message") # 点击提交按钮时,调用submit_answers函数 submit_button.click( submit_answers_posttest, inputs=[question1, question2, question3, question4, question5, question6, question7, question8, question9, question10], outputs=output ) demo.load(queue=False) demo.queue() if __name__ == "__main__": demo.launch(share=True)