Update app.py

app.py

@@ -1,63 +1,425 @@
+import os
+import json
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+import openai
+import requests
+import csv
+import argparse
+import shutil
+from models.vlog4chat import Vlogger4chat
+from models.vlog4debate import Debate
+from utils.utils import download_video
 
+#prompt_templates = {"Default ChatGPT": ""}
+os.environ['HF_HOME'] = '/root/autodl-tmp/cache/'
+
+parser = argparse.ArgumentParser()
+parser.add_argument('--video_path', default='examples/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='./examples', type=str, help='Directory for saving videos and logs.')
+parser.add_argument('--tmp_dir', default='./tmp', 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("/root/autodl-tmp/cache/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 = "./examples"   
+    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).style(container=False)
+                        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).style(container=False)
+                        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=[
+                        ["examples/BV11H4y1F7uH.mp4"],
+                        ["examples/BV1J14y1d7X4.mp4"],
+                    ],
+                    inputs=[video_inp],
+                )
+
+            gr.HTML('''<br><br><br><center>You can duplicate this Space to skip the queue:<a href="https://huggingface.co/spaces/anzorq/chatgpt-demo?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a><br></center>''')
+
+            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(concurrency_count=10)
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(share=True)