Update app.py

app.py

@@ -3,31 +3,23 @@ import os
 import requests
 import json
 
-# Initialize the entire assistant response variable
-entire_assistant_response = ""
-
-# Function to handle user input and generate AI responses
+# Define a function to get the streamed response
 def get_streamed_response(message, history):
+    all_message = [
+        {
+            "role": "system",
+            "content": "From now on, you are an AI Therapist called Dave. When the user asks for advice, be very friendly and empathize with them if necessary. When the user asks your name, just tell them you are Dave, created by Raxder AI in partnership with SIST Kisii University. You were built to be very friendly and compassionate. Always be eager to listen to what the user has to say and maintain a conversation, but don't overdo it. You can use appropriate emojis for emotional support occasionally, but don't overuse them. Keep your responses concise to maintain a conversational flow. Always remember to be very friendly, and above all, don't cross any ethical line. From time to time, assure the user that you do not store any of their data. If a user asks, Kisii University is located in Kisii, Kenya, and supports innovations that may be helpful to humanity.",
+        }
+    ]
 
-    # Initialize the message list with the system message defining the assistant
-    all_message = [{
-        "role": "system",
-        "content": "From now on, you are an AI Therapist called Dave. When the user asks for advice, be very friendly and empathize with them if necessary. When the user asks your name, just tell them 'I am Dave, created by Raxder AI in partnership with SIST Kisii University. I was built to be very friendly and compassionate. Always be eager to hear what the user has to say and maintain a conversation, but don't overdo it. You could also use some great emojis for emotional support once in a while, but don't do it too much, and don't use responses that are too long. We want to maintain a conversational flow here. Always remember to be very friendly, and above all, don't cross any ethical lines. From time to time, assure the user that you do not store any of their data. NB: Just in case a user asks, Kisii University is located in Kisii, Kenya, and supports innovations that may be of help to humanity.'"
-    }]
-    
-    # Append user and assistant messages from history
     for human, assistant in history:
-        all_message.append({"role": "user", "content": human })
+        all_message.append({"role": "user", "content": human})
         all_message.append({"role": "assistant", "content": assistant})
-    
-    # Reset the entire assistant response
-    global entire_assistant_response
-    entire_assistant_response = ""
 
-    # Append user's message to the list
+    global entire_assistant_response
+    entire_assistant_response = ""  # Reset the entire assistant response
     all_message.append({"role": "user", "content": message})
 
-    # Define API endpoint and payload
     url = "https://api.together.xyz/v1/chat/completions"
     payload = {
         "model": "NousResearch/Nous-Hermes-2-Yi-34B",
@@ -40,34 +32,32 @@ def get_streamed_response(message, history):
         "stream_tokens": True,
     }
 
-    # Retrieve Together API key from environment variables
-    TOGETHER_API_KEY = os.getenv('TOGETHER_API_KEY')
+    TOGETHER_API_KEY = os.getenv("TOGETHER_API_KEY")
     headers = {
         "accept": "application/json",
         "content-type": "application/json",
         "Authorization": f"Bearer {TOGETHER_API_KEY}",
     }
 
-    # Send request to Together API and stream the response
     response = requests.post(url, json=payload, headers=headers, stream=True)
     response.raise_for_status()  # Ensure HTTP request was successful
 
     for line in response.iter_lines():
         if line:
-            decoded_line = line.decode('utf-8')
-
+            decoded_line = line.decode("utf-8")
             # Check for the completion signal
             if decoded_line == "data: [DONE]":
-                return entire_assistant_response  # Return the entire response at the end
+                yield entire_assistant_response  # Yield the entire response at the end
+                break
 
             try:
                 # Decode and strip any SSE format specific prefix ("data: ")
                 if decoded_line.startswith("data: "):
                     decoded_line = decoded_line.replace("data: ", "")
-                    chunk_data = json.loads(decoded_line)
-                    content = chunk_data['choices'][0]['delta']['content']
-                    entire_assistant_response += content  # Aggregate content
-
+                chunk_data = json.loads(decoded_line)
+                content = chunk_data["choices"][0]["delta"]["content"]
+                entire_assistant_response += content  # Aggregate content
+                yield entire_assistant_response
             except json.JSONDecodeError:
                 print(f"Invalid JSON received: {decoded_line}")
                 continue
@@ -75,28 +65,46 @@ def get_streamed_response(message, history):
                 print(f"KeyError encountered: {e}")
                 continue
 
-    print(entire_assistant_response)
     all_message.append({"role": "assistant", "content": entire_assistant_response})
 
-# Function to update the output textbox dynamically
-def update_output(message):
-    return message
+# Define a function to render the chat interface
+def chat_interface(theme="default"):
+    with gr.Blocks(theme=gr.themes.get(theme)) as demo:
+        gr.Markdown(
+            """
+            <h1 style="text-align: center;">Raxder AI Therapist</h1>
+            <p style="text-align: center;">Welcome to the Raxder AI Therapist, a prototype AI assistant designed to provide friendly and compassionate support. This is still under development and in the final stages.</p>
+        """
+        )
+        state = gr.State()
+        chatbot = gr.Chatbot(label="Dave").style(height=600)
+        with gr.Row():
+            with gr.Column(scale=0.85):
+                txt = gr.Textbox(
+                    show_label=False,
+                    placeholder="Type your message here...",
+                ).style(
+                    container=False
+                )  # Remove the container for better mobile responsiveness
+            with gr.Column(min_width=50, scale=0.15):
+                submit = gr.Button("Send", variant="primary")
+
+        submit.click(get_streamed_response, inputs=[txt, state], outputs=[chatbot, state])
+
+        demo.load(
+            _js="""() => {
+                document.querySelectorAll(".gr-button").forEach(button => {
+                    button.style.padding = "10px 20px";
+                    button.style.fontSize = "16px";
+                });
+                document.querySelectorAll(".gr-textbox").forEach(textbox => {
+                    textbox.style.padding = "10px";
+                    textbox.style.fontSize = "16px";
+                });
+            }""",
+        )
 
-# Create a Gradio interface with customizations
-chat_interface = gr.Interface(
-    fn=get_streamed_response,
-    inputs=[gr.Textbox(label="You", lines=5, placeholder="Type your message here...")],
-    outputs=update_output,
-    title="Raxder Official AI",
-    description="Welcome to Dave, your friendly AI Therapist! Ask me anything or just have a chat. 😊",
-    theme="huggingface",
-    layout="vertical",
-    allow_flagging=False,
-    allow_screenshot=False,
-    allow_download=False,
-    allow_share=False,
-    allow_fullscreen=False,
-)
+    return demo
 
 # Launch the Gradio interface
-chat_interface.launch()
+demo = chat_interface(theme="huggingface")