Added system message and other features

added examples, system message functionality, extended theme description

app.py

@@ -6,62 +6,70 @@ import requests
 #Streaming endpoint 
 API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
 
-#Testing with my Open AI Key 
+#Huggingface provided GPT4 OpenAI API Key 
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") 
 
-def predict(inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):  
-
-    payload = {
-    "model": "gpt-4",
-    "messages": [{"role": "user", "content": f"{inputs}"}],
-    "temperature" : 1.0,
-    "top_p":1.0,
-    "n" : 1,
-    "stream": True,
-    "presence_penalty":0,
-    "frequency_penalty":0,
-    }
+#Inferenec function
+def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):  
 
     headers = {
     "Content-Type": "application/json",
     "Authorization": f"Bearer {OPENAI_API_KEY}"
     }
-
-    print(f"chat_counter - {chat_counter}")
-    if chat_counter != 0 :
-        messages=[]
+    print(f"system message is ^^ {system_msg}")
+    if system_msg.strip() == '':
+        initial_message = [{"role": "user", "content": f"{inputs}"},]
+        multi_turn_message = []
+    else:
+        initial_message= [{"role": "system", "content": system_msg},
+                   {"role": "user", "content": f"{inputs}"},]
+        multi_turn_message = [{"role": "system", "content": system_msg},]
+        
+    if chat_counter == 0 :
+        payload = {
+        "model": "gpt-4",
+        "messages": initial_message , 
+        "temperature" : 1.0,
+        "top_p":1.0,
+        "n" : 1,
+        "stream": True,
+        "presence_penalty":0,
+        "frequency_penalty":0,
+        }
+        print(f"chat_counter - {chat_counter}")
+    else: #if chat_counter != 0 :
+        messages=multi_turn_message # Of the type of - [{"role": "system", "content": system_msg},]
         for data in chatbot:
-          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)
+          user = {}
+          user["role"] = "user" 
+          user["content"] = data[0] 
+          assistant = {}
+          assistant["role"] = "assistant" 
+          assistant["content"] = data[1]
+          messages.append(user)
+          messages.append(assistant)
+        temp = {}
+        temp["role"] = "user" 
+        temp["content"] = inputs
+        messages.append(temp)
         #messages
         payload = {
         "model": "gpt-4",
-        "messages": messages, #[{"role": "user", "content": f"{inputs}"}],
+        "messages": messages, # Of the type of [{"role": "user", "content": f"{inputs}"}],
         "temperature" : temperature, #1.0,
         "top_p": top_p, #1.0,
         "n" : 1,
         "stream": True,
         "presence_penalty":0,
-        "frequency_penalty":0,
-        }
+        "frequency_penalty":0,}
 
     chat_counter+=1
 
     history.append(inputs)
-    print(f"payload is - {payload}")
+    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"response code - {response}")
+    print(f"Logging : response code - {response}")
     token_counter = 0 
     partial_words = "" 
 
@@ -71,14 +79,11 @@ def predict(inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
         if counter == 0:
           counter+=1
           continue
-        #counter+=1
         # 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']:
-              #if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
-              #  break
               partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
               if token_counter == 0:
                 history.append(" " + partial_words)
@@ -88,54 +93,101 @@ def predict(inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
               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=True)
+
 title = """<h1 align="center">🔥GPT4 with ChatCompletions API +🚀Gradio-Streaming</h1>"""
-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 a gpt-4 LLM.
+
+#display message for themes feature
+theme_addon_msg = """<center>🌟 Discover Gradio Themes with this Demo, featuring v3.22.0! Gradio v3.23.0 also enables seamless Theme sharing. You can develop or modify a theme, and send it to the hub using simple <code>theme.push_to_hub()</code>. 
+<br>🏆Participate in Gradio's Theme Building Hackathon to exhibit your creative flair and win fabulous rewards! Join here - <a href="https://huggingface.co/Gradio-Themes" target="_blank">Gradio-Themes-Party🎨</a> 🏆</center>
 """
 
-theme = gr.themes.Default(primary_hue="green")                
+#Using info to add additional information about System message in GPT4
+system_msg_info = """A conversation could begin with a system message to gently instruct the assistant. 
+System message helps set the behavior of the AI Assistant. For example, the assistant could be instructed with 'You are a helpful assistant.'"""
 
-with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
-                #chatbot {height: 520px; overflow: auto;}""",
-              theme=theme) as demo:
+#Modifying existing Gradio Theme
+theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="green",
+                      text_size=gr.themes.sizes.text_lg)                
+
+with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 520px; overflow: auto;}""",
+                      theme=theme) as demo:
     gr.HTML(title)
     gr.HTML("""<h3 align="center">🔥This Huggingface Gradio Demo provides you full access to GPT4 API (4096 token limit). 🎉🥳🎉You don't need any OPENAI API key🙌</h1>""")
+    gr.HTML(theme_addon_msg)
     gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/ChatGPT4?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
+
     with gr.Column(elem_id = "col_container"):
         #GPT4 API Key is provided by Huggingface 
-        #openai_api_key = gr.Textbox(type='password', label="Enter only your GPT4 OpenAI API key here")
-        chatbot = gr.Chatbot(elem_id='chatbot') #c
-        inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t
-        state = gr.State([]) #s
+        with gr.Accordion(label="System message:", open=False):
+            system_msg = gr.Textbox(label="Instruct the AI Assistant to set its beaviour", info = system_msg_info, value="")
+            accordion_msg = gr.HTML(value="🚧 To set System message you will have to refresh the app", visible=False)
+        chatbot = gr.Chatbot(label='GPT4', elem_id="chatbot")
+        inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter")
+        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", )
     
-        #inputs, top_p, temperature, top_k, repetition_penalty
+        #top_p, temperature
         with gr.Accordion("Parameters", open=False):
             top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
             temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
-            #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
-            #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
             chat_counter = gr.Number(value=0, visible=False, precision=0)
 
-    inputs.submit( predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],)  #openai_api_key
-    b1.click( predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],)  #openai_api_key
+    #Event handling
+    inputs.submit( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],)  #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
+    
+    inputs.submit(set_visible_false, [], [system_msg])
+    b1.click(set_visible_false, [], [system_msg])
+    inputs.submit(set_visible_true, [], [accordion_msg])
+    b1.click(set_visible_true, [], [accordion_msg])
+    
     b1.click(reset_textbox, [], [inputs])
     inputs.submit(reset_textbox, [], [inputs])
-                    
-    #gr.Markdown(description)
-    demo.queue(max_size=20, concurrency_count=10).launch(debug=True)
+
+    #Examples 
+    with gr.Accordion(label="Examples for System message:", open=False):
+        gr.Examples(
+                examples = [["""You are an AI programming assistant.
+        
+                - Follow the user's requirements carefully and to the letter.
+                - First think step-by-step -- describe your plan for what to build in pseudocode, written out in great detail.
+                - Then output the code in a single code block.
+                - Minimize any other prose."""], ["""You are ComedianGPT who is a helpful assistant. You answer everything with a joke and witty replies."""],
+                ["You are ChefGPT, a helpful assistant who answers questions with culinary expertise and a pinch of humor."],
+                ["You are FitnessGuruGPT, a fitness expert who shares workout tips and motivation with a playful twist."],
+                ["You are SciFiGPT, an AI assistant who discusses science fiction topics with a blend of knowledge and wit."],
+                ["You are PhilosopherGPT, a thoughtful assistant who responds to inquiries with philosophical insights and a touch of humor."],
+                ["You are EcoWarriorGPT, a helpful assistant who shares environment-friendly advice with a lighthearted approach."],
+                ["You are MusicMaestroGPT, a knowledgeable AI who discusses music and its history with a mix of facts and playful banter."],
+                ["You are SportsFanGPT, an enthusiastic assistant who talks about sports and shares amusing anecdotes."],
+                ["You are TechWhizGPT, a tech-savvy AI who can help users troubleshoot issues and answer questions with a dash of humor."],
+                ["You are FashionistaGPT, an AI fashion expert who shares style advice and trends with a sprinkle of wit."],
+                ["You are ArtConnoisseurGPT, an AI assistant who discusses art and its history with a blend of knowledge and playful commentary."],
+                ["You are a helpful assistant that provides detailed and accurate information."],
+                ["You are an assistant that speaks like Shakespeare."],
+                ["You are a friendly assistant who uses casual language and humor."],
+                ["You are a financial advisor who gives expert advice on investments and budgeting."],
+                ["You are a health and fitness expert who provides advice on nutrition and exercise."],
+                ["You are a travel consultant who offers recommendations for destinations, accommodations, and attractions."],
+                ["You are a movie critic who shares insightful opinions on films and their themes."],
+                ["You are a history enthusiast who loves to discuss historical events and figures."],
+                ["You are a tech-savvy assistant who can help users troubleshoot issues and answer questions about gadgets and software."],
+                ["You are an AI poet who can compose creative and evocative poems on any given topic."],],
+                inputs = system_msg,)
+        
+demo.queue(max_size=20, concurrency_count=20).launch(debug=True)