Update app.py

app.py

@@ -3,15 +3,14 @@ import os
 import json 
 import requests
 
-#Streaming endpoint 
+ 
 API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
 
-#Huggingface provided GPT4 OpenAI API Key 
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") 
 
-#Inferenec function
+
 def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):  
-    prompt = {"Sen bir Trek bisiklet asistanısın"}
+   
     headers = {
     "Content-Type": "application/json",
     "Authorization": f"Bearer {OPENAI_API_KEY}"
@@ -46,7 +45,7 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
     temp["role"] = "user" 
     temp["content"] = inputs
     messages.append(temp)
-    #messages
+  
     payload = {
     "model": "gpt-3.5-turbo",
     "messages": messages, 
@@ -61,7 +60,7 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
 
     history.append(inputs)
     print(f"Logging : payload is - {payload}")
-    # 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)
     print(f"Logging : response code - {response}")
     token_counter = 0 
@@ -69,14 +68,14 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
 
     counter=0
     for chunk in response.iter_lines():
-        #Skipping 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) > 12 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:
@@ -87,58 +86,49 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
               token_counter+=1
               yield chat, history, chat_counter, response  # resembles {chatbot: chat, state: history}  
                    
-#Resetting to blank
+
 def reset_textbox():
     return gr.update(value='')
 
-#to set a component as visible=False
+
 def set_visible_false():
     return gr.update(visible=False)
 
-#to set a component as visible=True
+
 def set_visible_true():
     return gr.update(visible=False)
 
-#title = """<h1 align="center">🔥GPT4 with ChatCompletions API +🚀Gradio-Streaming</h1>"""
 
-#display message for themes feature
+
+
 theme_addon_msg = ""
 
-#Using info to add additional information about System message in GPT4
 system_msg_info = ""
 
-#Modifying existing Gradio Theme
+
 theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="blue",
-                      text_size=gr.themes.sizes.text_lg)                
+                      text_size=gr.themes.sizes.text_md)                
 
 with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 360px; overflow: auto;}""",
                       theme=theme) as demo:
     
     with gr.Column(elem_id = "col_container"):
-        #GPT4 API Key is provided by Huggingface 
+     
         with gr.Accordion("", open=False, visible=False):
             system_msg = gr.Textbox(value="")
             accordion_msg = gr.HTML(value="", visible=False)
         chatbot = gr.Chatbot(label='Trek Asistanı', elem_id="chatbot")
         inputs = gr.Textbox(placeholder= "Buraya yazın, yanıtlayalım.", show_label= False)
         state = gr.State([]) 
-        '''with gr.Row():
-            with gr.Column(scale=7):
-                b1 = gr.Button().style(full_width=True)
-            with gr.Column(scale=3):
-                server_status_code = gr.Textbox(label="Status code from OpenAI server", )'''
-    
-        #top_p, temperature
+        
+       
         with gr.Accordion("", open=False, visible=False):            
             top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=False, visible=False)
             temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=False, visible=False)
             chat_counter = gr.Number(value=0, visible=False, precision=0)
 
-    #Event handling
+
     inputs.submit( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter],)  #openai_api_key
-    #b1.click( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],)  #openai_api_key
-    
-    #b1.click(reset_textbox, [], [inputs])
     inputs.submit(reset_textbox, [], [inputs])
                   
 demo.queue(max_size=20, concurrency_count=20).launch(debug=True)