use gr.State() to define global variables

README.md

@@ -8,7 +8,6 @@ colorTo: blue
 app_file: app.py
 pinned: false
 short_description: A self-healing ChatBot to comfort yourself.
-header: mini
 models: 
 - stabilityai/stable-diffusion-xl-base-1.0
 ---

app.py

@@ -1,5 +1,7 @@
 import spaces
 import os
+import jieba
+import pandas as pd
 import gradio as gr
 import torch
 import numpy as np
@@ -11,6 +13,7 @@ from openai import OpenAI
 from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, EulerAncestralDiscreteScheduler
 from peft import PeftModel
 from transformers import AutoModel
+import asyncio
 
 # OpenAI API
 api_key = os.getenv('OPENAI_API_KEY')
@@ -27,24 +30,12 @@ lora_path = "./tbh368-sdxl.safetensors"
 pipe_t2i.load_lora_weights(lora_path, adapter_name="milton-glaser")
 pipe_t2i.set_adapters(["milton-glaser"], adapter_weights=[1.0])
 
-import jieba
-import numpy as np
-import pandas as pd
-
-valence_scores = []
-arousal_scores = []
-conversation_times = 0
-
 # 載入 CVAW Corpus 資料
 cvaw_data = pd.read_csv('./CVAW_all_SD.csv', delimiter='\t')
 cvaw_dict = dict(zip(cvaw_data['Word'], zip(cvaw_data['Valence_Mean'], cvaw_data['Arousal_Mean'])))
 
-def analyze_sentiment_corpus(text):
+def analyze_sentiment_corpus(text, conversation_times, valence_scores, arousal_scores):
   words = jieba.cut(text)
-  global conversation_times
-  global valence_scores
-  global arousal_scores
-
   conversation_times += 1
 
   for word in words:
@@ -57,11 +48,11 @@ def analyze_sentiment_corpus(text):
         arousal_scores = arousal_scores[-3:]
 
   if conversation_times < 4: # 當對話次數<4的時候，返回10，代表不會進入放鬆模式
-    return 10, 10
+    return 10, 10, conversation_times, valence_scores, arousal_scores
   else:
     avg_valence = np.mean(valence_scores)
     avg_arousal = np.mean(arousal_scores)
-    return avg_valence, avg_arousal
+    return avg_valence, avg_arousal, conversation_times, valence_scores, arousal_scores
 
 def call_gpt(input_text, history):
   messages = [{"role":"system", "content":"對話請以繁體中文進行：你是一位熟悉現象學的諮商實習生，擅長引導使用者描述他當下的所知覺到的事物。回答問題的時候必須有同理心，請同理使用者說的內容，再繼續回答，且不要超過20個字。"}]
@@ -80,33 +71,29 @@ def call_gpt(input_text, history):
 
   return chat_reply.choices[0].message.content
 
-# Testing meditation function
-meditation_flag = True # 判斷是否進入放鬆模式
-
-def chat_with_bot(input_text, history):
-  global meditation_flag
+def chat_with_bot(input_text, history, conversation_times, valence_scores, arousal_scores, meditation_flag):
   response = ""
   med_confirm_layout = False # 是否顯示放鬆選項
   jump2med_btn = True # 是否允許跳轉到放鬆介面
 
   # 進行情感分析
-  valence, arousal = analyze_sentiment_corpus(input_text)
+  valence, arousal, conversation_times, valence_scores, arousal_scores = analyze_sentiment_corpus(input_text, conversation_times, valence_scores, arousal_scores)
 
   # 判斷是否建議放鬆練習
   if 3 <= arousal <= 4 and meditation_flag is True:  # 詢問是否進行放鬆練習
     response = "我知道你的處境了\n我有一個建議，我們來進行一個可以讓自己放鬆的呼吸覺察練習好嗎？"
     history.append((input_text, response))
     med_confirm_layout = True
-    return history, med_confirm_layout, jump2med_btn
+    return history, med_confirm_layout, jump2med_btn, conversation_times, valence_scores, arousal_scores, meditation_flag
   elif meditation_flag is False:  # 已經放鬆過，不顯示跳轉按鈕
     response = call_gpt(input_text, history)
     history.append((input_text, response))
     jump2med_btn = False
-    return history, med_confirm_layout, jump2med_btn
+    return history, med_confirm_layout, jump2med_btn, conversation_times, valence_scores, arousal_scores, meditation_flag
   else: # 繼續對話
     response = call_gpt(input_text, history)
     history.append((input_text, response))
-    return history, med_confirm_layout, jump2med_btn
+    return history, med_confirm_layout, jump2med_btn, conversation_times, valence_scores, arousal_scores, meditation_flag
 
 def translate_to_english(text):
   character = "You are a professional text to image prompt generator, please use the following text to generate prompt in English. It's very important to summarize it in 70 tokens."
@@ -120,16 +107,10 @@ def translate_to_english(text):
 
   return chat_reply.choices[0].message.content
 
-generated_images = None
-last_genimg_times = 0
-
 @spaces.GPU(duration=120)
-def generate_images(history):
-  global generated_images  # 使用全域變數來儲存圖片
-  global last_genimg_times
-
+def generate_images(history, conversation_times, last_genimg_times, generated_images):
   if generated_images is not None and last_genimg_times == conversation_times:
-    return generated_images  # 如果圖片已生成，直接返回
+    return conversation_times, last_genimg_times, *generated_images  # 如果圖片已生成，直接返回
 
   user_story = " ".join([h[0] for h in history])
   prompt = translate_to_english(user_story)
@@ -152,7 +133,7 @@ def generate_images(history):
     images.append(img)
 
   generated_images = images  # 儲存生成的圖片
-  return images
+  return conversation_times, last_genimg_times, *images
 
 def select_image(choice, img1, img2, img3, img4):
   index = int(choice.split()[-1]) - 1
@@ -190,8 +171,8 @@ def chat_about_image(input_text, history, selected_image):
 audio_file = "./meditation_v2.mp3"
 
 # UI handle functions
-def handle_chat(input_text, history):
-  updated_history, meditation, jump2med_btn = chat_with_bot(input_text, history)
+def handle_chat(input_text, history, conversation_times, valence_scores, arousal_scores, meditation_flag):
+  updated_history, meditation, jump2med_btn, conversation_times, valence_scores, arousal_scores, meditation_flag = chat_with_bot(input_text, history, conversation_times, valence_scores, arousal_scores, meditation_flag)
   if meditation:
     return (
         updated_history,
@@ -199,7 +180,8 @@ def handle_chat(input_text, history):
         gr.update(visible=False), # submit
         gr.update(visible=False), # jump_to_med
         gr.update(visible=True), # meditation_buttons
-        gr.update(visible=False) # clear
+        gr.update(visible=False), # clear
+        conversation_times, valence_scores, arousal_scores, meditation_flag
       )
   elif jump2med_btn is False:
     return (
@@ -208,7 +190,8 @@ def handle_chat(input_text, history):
         gr.update(visible=True),  # submit
         gr.update(visible=False), # jump_to_med
         gr.update(visible=False), # meditation_buttons
-        gr.update(visible=True)  # clear
+        gr.update(visible=True),  # clear
+        conversation_times, valence_scores, arousal_scores, meditation_flag
       )
   else:
     return (
@@ -217,15 +200,14 @@ def handle_chat(input_text, history):
         gr.update(visible=True),  # submit
         gr.update(visible=True), # jump_to_med
         gr.update(visible=False), # meditation_buttons
-        gr.update(visible=True)  # clear
+        gr.update(visible=True),  # clear
+        conversation_times, valence_scores, arousal_scores, meditation_flag
       )
 
-def start_meditation(history):
-  global meditation_flag
+def start_meditation(meditation_flag):
   meditation_flag = False
-  audio = audio_file
   return (
-    audio
+    audio_file, meditation_flag
   )
 
 def continue_chat():
@@ -252,8 +234,6 @@ def return_to_chat():
     gr.update(visible=False) # jump_to_med
   )
 
-import asyncio
-
 async def show_loading():
   # 顯示載入訊息
   yield (gr.update(visible=True), # loading_message
@@ -268,7 +248,6 @@ async def show_loading():
         gr.update(visible=False), # main_interface
         gr.update(visible=True)) # audio_interface
 
-# Testing meditation function
 theme = gr.themes.Base(
     primary_hue="amber",
     secondary_hue="sky",
@@ -303,6 +282,13 @@ css = """
 """
 
 with gr.Blocks(theme=theme, css=css) as demo:
+  generated_images = gr.State(value=None)
+  meditation_flag = gr.State(value=True)
+  last_genimg_times = gr.State(value=0)
+  conversation_times = gr.State(value=0)
+  valence_scores = gr.State(value=[])
+  arousal_scores = gr.State(value=[])
+
   loading_message = gr.Textbox(visible=False, show_label=False)
   with gr.Column(visible=False) as audio_interface:
     audio_player = gr.Audio(label="呼吸覺察練習", show_download_button=False, interactive=False)
@@ -314,8 +300,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
       msg = gr.Textbox(show_label=False, placeholder="今天想要跟我分享什麼呢？", autofocus=True, scale=2)
       with gr.Row():
         submit = gr.Button("送出", variant="primary", scale=2)
-        jump_to_med = gr.Button("我想要現在進行呼吸覺察練習", scale=2)
-        gen_other_img = gr.Button("結合聯想生成更多圖像", scale=2, visible=False)
+        jump_to_med = gr.Button("我想要現在進行呼吸覺察練習", variant="secondary", scale=2)
+        gen_other_img = gr.Button("結合聯想生成更多圖像", variant="secondary", scale=2, visible=False)
         clear = gr.Button("清除對話紀錄", scale=1)
       with gr.Row(visible=False) as meditation_buttons:
         relax_yes = gr.Button("好", variant="primary")
@@ -329,19 +315,19 @@ with gr.Blocks(theme=theme, css=css) as demo:
       image_chat_button = gr.Button("與聊天機器人分享", variant="primary")
 
   # chatbot events handle
-  submit.click(handle_chat, [msg, chatbot], [chatbot, msg, submit, jump_to_med, meditation_buttons, clear])
-  msg.submit(handle_chat, [msg, chatbot], [chatbot, msg, submit, jump_to_med, meditation_buttons, clear])
+  submit.click(handle_chat, [msg, chatbot, conversation_times, valence_scores, arousal_scores, meditation_flag], [chatbot, msg, submit, jump_to_med, meditation_buttons, clear, conversation_times, valence_scores, arousal_scores, meditation_flag])
+  msg.submit(handle_chat, [msg, chatbot, conversation_times, valence_scores, arousal_scores, meditation_flag], [chatbot, msg, submit, jump_to_med, meditation_buttons, clear, conversation_times, valence_scores, arousal_scores, meditation_flag])
   clear.click(lambda: None, None, chatbot, queue=False)
 
   # going to meditation events handle
-  jump_to_med.click(start_meditation, [chatbot], audio_player)
-  relax_yes.click(start_meditation, [chatbot], audio_player)
+  jump_to_med.click(start_meditation, meditation_flag, [audio_player, meditation_flag])
+  relax_yes.click(start_meditation, meditation_flag, [audio_player, meditation_flag])
   relax_no.click(continue_chat, None, [msg, submit, jump_to_med, meditation_buttons, clear])
 
   # meditation events handle
   jump_to_med.click(show_loading, None, [loading_message, loading_message, main_interface, audio_interface])
   relax_yes.click(show_loading, None, [loading_message, loading_message, main_interface, audio_interface])
-  audio_player.play(generate_images, [chatbot], image_outputs)
+  audio_player.play(generate_images, [chatbot, conversation_times, last_genimg_times, generated_images], [conversation_times, last_genimg_times] + image_outputs)
   audio_player.stop(return_to_chat, None, [audio_player, main_interface, chatbot_interface, selected_image_interface, audio_interface, msg, submit, clear, meditation_buttons, gen_other_img, jump_to_med])
   back_to_chat.click(return_to_chat, None, [audio_player, main_interface, chatbot_interface, selected_image_interface, audio_interface, msg, submit, clear, meditation_buttons, gen_other_img, jump_to_med])
 
@@ -351,18 +337,8 @@ with gr.Blocks(theme=theme, css=css) as demo:
   image_chat_button.click(chat_about_image, [image_chat_input, chatbot, selected_image], [chatbot, chatbot, chatbot_interface]).then(lambda: None, None, image_chat_input , queue=False)
 
   # generate other images event handle
-  gen_other_img.click(generate_images, [chatbot], image_outputs)
+  gen_other_img.click(generate_images, [chatbot, conversation_times, last_genimg_times, generated_images], [conversation_times, last_genimg_times] + image_outputs)
 
 if __name__ == "__main__":
-  # initialize the variables
-  torch.cuda.empty_cache()
-  generated_images = None
-  meditation_flag = True
-  last_genimg_times = 0
-  conversation_times = 0
-  valence_scores = []
-  arousal_scores = []
-  print("variables initialized")
-
   demo.queue(max_size=20)
   demo.launch(show_api=False)