update theme and predict fun

app.py

@@ -15,13 +15,6 @@ from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
 model_chtoen = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
 tokenizer_chtoen = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
 
-# Define function to generate model predictions and update the history
-def predict_glm(input, history=[]):
-    response, history = model_glm.chat(tokenizer_glm, input, history)
-    # translate Chinese to English
-    history = [(query, translate_Chinese_English(response)) for query, response in history]
-    return history, history #[history] + updates
-
 def translate_Chinese_English(chinese_text): 
     # translate Chinese to English
     tokenizer_chtoen.src_lang = "zh"
@@ -30,45 +23,21 @@ def translate_Chinese_English(chinese_text):
     trans_eng_text = tokenizer_chtoen.batch_decode(generated_tokens, skip_special_tokens=True)
     return trans_eng_text[0]
 
-# Define generator to stream model predictions 
-def predict_glm_stream_old(input, history=[]): #, top_p, temperature):
-    top_p = 1.0
-    temperature = 1.0
-    for response, history in model_glm.stream_chat(tokenizer_glm, input, history, top_p=1.0, temperature=1.0):   #max_length=max_length,
-        print(f"In for loop resonse is ^^- {response}")
-        print(f"In for loop history is ^^- {history}")
-        # translate Chinese to English
-        history = [(query, translate_Chinese_English(response)) for query, response in history]
-        print(f"In for loop translated history is ^^- {history}")
-        yield history, history #[history] + updates
     
 # Define function to generate model predictions and update the history
-def predict_glm_stream(input, history=[]): #, top_p, temperature):
-    for response, updates in model_glm.stream_chat(tokenizer_glm, input, history[-1] if history else history, top_p=1.0, temperature=1.0):   #history
+def predict_glm_stream(input, top_p, temperature, history=[]): #, top_p, temperature):
+    print(f"1 outside for loop OG history is ^^- {history}")
+    history = list(map(tuple, history))
+    print(f"2 outside for loop OG history is ^^- {history}")
+    for response, updates in model_glm.stream_chat(tokenizer_glm, input, history, top_p=top_p, temperature=temperature):   #history
         print(f"In for loop resonse is ^^- {response}")
         print(f"In for loop updates is ^^- {updates}")
         # translate Chinese to English
         #history = [(query, translate_Chinese_English(response)) for query, response in history]
-        print(f"In for loop OG history is ^^- {history}")
-        print(f"In for loop translated history is ^^- {history+updates}")
-        yield history+updates
-
-
-"""    
-def predict(input, max_length, top_p, temperature, history=None):
-    if history is None:
-        history = []
-    for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
-                                               temperature=temperature):
-        updates = []
-        for query, response in history:
-            updates.append(gr.update(visible=True, value="user：" + query))  #用户
-            updates.append(gr.update(visible=True, value="ChatGLM-6B：" + response))
-        if len(updates) < MAX_BOXES:
-            updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
-        yield [history] + updates
-"""
+        print(f"*******")
+        yield updates #history+updates
 
+    
 def reset_textbox():
     return gr.update(value="")
 
@@ -79,23 +48,24 @@ def reset_chat(chatbot, state):
     return None, []
 
 
-#title = """<h1 align="center">🔥🔥Comparison: ChatGPT & OpenChatKit </h1><br><h3 align="center">🚀A Gradio Streaming Demo</h3><br>Official Demo: <a href="https://huggingface.co/spaces/togethercomputer/OpenChatKit">OpenChatKit feedback app</a>"""
-title = """<h1 align="center">🔥🔥Comparison: ChatGPT & Open Sourced CHatGLM-6B </h1><br><h3 align="center">🚀A Gradio Chatbot Demo</h3>"""
-description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
-```
-User: <utterance>
-Assistant: <utterance>
-User: <utterance>
-Assistant: <utterance>
-...
-```
-In this app, you can explore the outputs of multiple LLMs when prompted in similar ways.
+title = """<h1 align="center"> 🚀CHatGLM-6B - A Streaming Chatbot with Gradio</h1>
+<h2 align="center">Enhance User Experience with Streaming and customizable Gradio Themes</h2>"""
+header = """<center>Find on Huggingface at <a href="https://huggingface.co/THUDM/chatglm-6b" target="_blank">THUDM/chatglm-6b</a>, and <a href="https://github.com/THUDM/ChatGLM-6B" target="_blank">here</a> on Github.<center>"""
+description = """
+ChatGLM-6B is an open-source, Chinese-English bilingual dialogue language model based on the General Language Model (GLM) architecture with 6.2 billion parameters. 
+
+However, due to the small size of ChatGLM-6B, it is currently known to have considerable limitations, such as factual/mathematical logic errors, possible generation of harmful/biased content, weak contextual ability, self-awareness confusion, and Generate content that completely contradicts Chinese instructions for English instructions. Please understand these issues before use to avoid misunderstandings. A larger ChatGLM based on the 130 billion parameter GLM-130B is under development in internal testing.
 """
 
+theme = gr.themes.Default(#color contructors
+                          primary_hue="violet", 
+                          secondary_hue="indigo",
+                          neutral_hue="purple") 
+                           
 with gr.Blocks(css="""#col_container {margin-left: auto; margin-right: auto;}
-                #chatglm {height: 520px; overflow: auto;} """ ) as demo:
+                #chatglm {height: 520px; overflow: auto;} """, theme=theme ) as demo:
     gr.HTML(title)
-    #with gr.Row():
+    gr.HTML(header)
     with gr.Column(): #(scale=10):
         with gr.Box():
             with gr.Row():
@@ -110,27 +80,24 @@ with gr.Blocks(css="""#col_container {margin-left: auto; margin-right: auto;}
         with gr.Box():
             chatbot_glm = gr.Chatbot(elem_id="chatglm", label='THUDM-ChatGLM6B')
           
-    #with gr.Column(): #(scale=2, elem_id='parameters'):
         with gr.Box():
             gr.HTML("Parameters for ChatGLM-6B", visible=True)
-            top_p = gr.Slider(minimum=-0, maximum=1.0,value=0.25, step=0.05,interactive=True, label="Top-p", visible=False)
-            temperature = gr.Slider(minimum=-0, maximum=5.0, value=0.6, step=0.1, interactive=True, label="Temperature",  visible=False)
-            #top_k = gr.Slider( minimum=1, maximum=50, value=50, step=1, interactive=True, label="Top-k", visible=False)
-            #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.01, step=0.01, interactive=True, label="Repetition Penalty", visible=False)
+            top_p = gr.Slider(minimum=-0, maximum=1.0,value=1, step=0.05,interactive=True, label="Top-p", visible=True)
+            temperature = gr.Slider(minimum=-0, maximum=5.0, value=1, step=0.1, interactive=True, label="Temperature", visible=True)
 
+    inputs.submit( predict_glm_stream,
+                [inputs, top_p, temperature, chatbot_glm ],
+                [chatbot_glm],)
     inputs.submit(reset_textbox, [], [inputs])
-    
 
-    inputs.submit( predict_glm_stream,
-                [inputs, chatbot_glm, ], #[inputs, state_glm, ],
-                [chatbot_glm],) #[chatbot_glm, state_glm],)
     b1.click( predict_glm_stream,
-                [inputs, chatbot_glm, ], #[inputs, state_glm, ],
-                [chatbot_glm],) #[chatbot_glm, state_glm],)
+                [inputs, top_p, temperature, chatbot_glm ],
+                [chatbot_glm],)
+    b1.click(reset_textbox, [], [inputs])
 
-    #b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
-    b2.click(reset_chat, [chatbot_glm, state_glm], [chatbot_glm, state_glm])
+    #b2.click(reset_chat, [chatbot_glm, state_glm], [chatbot_glm, state_glm])
+    b2.click(lambda: None, None, chatbot_glm, queue=False)
     
-    gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/OpenChatKit_ChatGPT_Comparison?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
+    gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/ChatGLM-6b_Gradio_Streaming?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
     gr.Markdown(description)
     demo.queue(concurrency_count=16).launch(height= 800, debug=True)