update streaming function

removed other chatbot components

app.py

@@ -15,84 +15,6 @@ from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
 model_chtoen = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
 tokenizer_chtoen = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
 
-#Predict function for CHATGPT
-def predict_chatgpt(inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):  
-    #Define payload and header for chatgpt API
-    payload = {
-    "model": "gpt-3.5-turbo",
-    "messages": [{"role": "user", "content": f"{inputs}"}],
-    "temperature" : 1.0,
-    "top_p":1.0,
-    "n" : 1,
-    "stream": True,
-    "presence_penalty":0,
-    "frequency_penalty":0,
-    }
-
-    headers = {
-    "Content-Type": "application/json",
-    "Authorization": f"Bearer {openai_api_key}"
-    }
-    #debug
-    #print(f"chat_counter_chatgpt - {chat_counter_chatgpt}")
-    
-    #Handling the different roles for ChatGPT
-    if chat_counter_chatgpt != 0 :
-        messages=[]
-        for data in chatbot_chatgpt:
-          temp1 = {}
-          temp1["role"] = "user" 
-          temp1["content"] = data[0] 
-          temp2 = {}
-          temp2["role"] = "assistant" 
-          temp2["content"] = data[1]
-          messages.append(temp1)
-          messages.append(temp2)
-        temp3 = {}
-        temp3["role"] = "user" 
-        temp3["content"] = inputs
-        messages.append(temp3)
-        payload = {
-        "model": "gpt-3.5-turbo",
-        "messages": messages, #[{"role": "user", "content": f"{inputs}"}],
-        "temperature" : temperature_chatgpt, #1.0,
-        "top_p": top_p_chatgpt, #1.0,
-        "n" : 1,
-        "stream": True,
-        "presence_penalty":0,
-        "frequency_penalty":0,
-        }
-
-    chat_counter_chatgpt+=1
-
-    history.append(inputs)
-
-    # make a POST request to the API endpoint using the requests.post method, passing in stream=True
-    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
-    token_counter = 0 
-    partial_words = ""  
-
-    counter=0
-    for chunk in response.iter_lines():
-        #Skipping the first chunk
-        if counter == 0:
-          counter+=1
-          continue
-        # check whether each line is non-empty
-        if chunk.decode() :
-          chunk = chunk.decode()
-          # decode each line as response data is in bytes
-          if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
-              partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
-              if token_counter == 0:
-                history.append(" " + partial_words)
-              else:
-                history[-1] = partial_words
-              chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
-              token_counter+=1
-              yield chat, history, chat_counter_chatgpt  # this resembles {chatbot: chat, state: history}  
-
-
 # Define function to generate model predictions and update the history
 def predict_glm(input, history=[]):
     response, history = model_glm.chat(tokenizer_glm, input, history)
@@ -108,21 +30,18 @@ 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 function to generate model predictions and update the history
+# Define generator to stream model predictions 
 def predict_glm_stream(input, history=[]): #, top_p, temperature):
-    response, history = model_glm.chat(tokenizer_glm, input, history)
-    print(f"outside for loop resonse is ^^- {response}")
-    print(f"outside for loop history is ^^- {history}")
     top_p = 1.0
     temperature = 1.0
-    for response, history in model.stream_chat(tokenizer_glm, input, history, top_p=1.0, temperature=1.0):   #max_length=max_length,
+    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
-
+    
     
 """    
 def predict(input, max_length, top_p, temperature, history=None):
@@ -162,76 +81,45 @@ Assistant: <utterance>
 In this app, you can explore the outputs of multiple LLMs when prompted in similar ways.
 """
 
-with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
-                #chatgpt {height: 520px; overflow: auto;}
+with gr.Blocks(css="""#col_container {margin-left: auto; margin-right: auto;}
                 #chatglm {height: 520px; overflow: auto;} """ ) as demo:
-                #chattogether {height: 520px; overflow: auto;} """ ) as demo:
-                #clear {width: 100px; height:50px; font-size:12px}""") as demo:
     gr.HTML(title)
-    with gr.Row():
-      with gr.Column(scale=14):
-          with gr.Box():
-              with gr.Row():
-                  with gr.Column(scale=13):
-                    openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here for ChatGPT")
+    #with gr.Row():
+    with gr.Column(): #(scale=10):
+        with gr.Box():
+            with gr.Row():
+                with gr.Column(scale=8):
                     inputs = gr.Textbox(placeholder="Hi there!", label="Type an input and press Enter ⤵️ " )
-                  with gr.Column(scale=1):
-                      b1 = gr.Button('🏃Run', elem_id = 'run').style(full_width=True)
-                      b2 = gr.Button('🔄Clear up Chatbots!', elem_id = 'clear').style(full_width=True)
-                  state_chatgpt = gr.State([])
-                  #state_together = gr.State([])
-                  state_glm = gr.State([])
-
-          with gr.Box():
-              with gr.Row():
-                  chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label='ChatGPT API - OPENAI')
-                  #chatbot_together = gr.Chatbot(elem_id="chattogether", label='OpenChatKit - Text Generation')
-                  chatbot_glm = gr.Chatbot(elem_id="chatglm", label='THUDM-ChatGLM6B')
+                with gr.Column(scale=1):
+                    b1 = gr.Button('🏃Run', elem_id = 'run').style(full_width=True)
+                with gr.Column(scale=1):
+                    b2 = gr.Button('🔄Clear up Chatbots!', elem_id = 'clear').style(full_width=True)
+                    state_glm = gr.State([])
+
+        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 #OpenCHAtKit", visible=False)
-              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)
-              watermark = gr.Checkbox(value=True, label="Text watermarking",  visible=False)
-              model = gr.CheckboxGroup(value="Rallio67/joi2_20B_instruct_alpha",
-                  choices=["togethercomputer/GPT-NeoXT-Chat-Base-20B", "Rallio67/joi2_20B_instruct_alpha", "google/flan-t5-xxl", "google/flan-ul2", "bigscience/bloomz", "EleutherAI/gpt-neox-20b",],
-                  label="Model",visible=False,) 
-              temp_textbox_together = gr.Textbox(value=model.choices[0], visible=False) 
-
-          with gr.Box():
-              gr.HTML("Parameters for OpenAI's ChatGPT")
-              top_p_chatgpt = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p",)
-              temperature_chatgpt = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
-              chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
+    #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)
 
     inputs.submit(reset_textbox, [], [inputs])
     
-    inputs.submit( predict_chatgpt, 
-                [inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt], 
-                [chatbot_chatgpt, state_chatgpt, chat_counter_chatgpt],)
-   #inputs.submit( predict_glm,
-   #            [inputs, state_glm, ],
-   #            [chatbot_glm, state_glm],)
-   #b1.click( predict_glm,
-   #            [inputs, state_glm, ],
-   #            [chatbot_glm, state_glm],)
+
     inputs.submit( predict_glm_stream,
                 [inputs, state_glm, ],
                 [chatbot_glm, state_glm],)
     b1.click( predict_glm_stream,
                 [inputs, state_glm, ],
                 [chatbot_glm, state_glm],)
-    b1.click( predict_chatgpt, 
-                [inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt], 
-                [chatbot_chatgpt, state_chatgpt, chat_counter_chatgpt],)
 
-    b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
-    #b2.click(reset_chat, [chatbot_together, state_together], [chatbot_together, state_together])
+    #b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
     b2.click(reset_chat, [chatbot_glm, state_glm], [chatbot_glm, state_glm])
     
     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.Markdown(description)
-    demo.queue(concurrency_count=16).launch(height= 2500, debug=True)
+    demo.queue(concurrency_count=16).launch(height= 800, debug=True)