Update app.py

app.py

@@ -1,23 +1,34 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from dotenv import load_dotenv
+import os
 
-client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta")
+# Load environment variables from .env file
+load_dotenv()
+
+# Get the system message from environment variables
+system_message = os.getenv("SYSTEM_MESSAGE")
 
-system_message = "You are MUSK-1, developed by a 14 year old AI engineer, Arjun Singh at Elieon."
+client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta")
 
 def respond(message, history, max_tokens, temperature, top_p):
+    # Prepare the initial message list with the system message
     messages = [{"role": "system", "content": system_message}]
 
+    # Add the conversation history to the messages list
     for user_msg, assistant_msg in history:
         if user_msg:
             messages.append({"role": "user", "content": user_msg})
         if assistant_msg:
             messages.append({"role": "assistant", "content": assistant_msg})
 
+    # Add the latest user message to the messages list
     messages.append({"role": "user", "content": message})
 
+    # Initialize an empty response string
     response = ""
 
+    # Generate the response using the Hugging Face InferenceClient
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -29,6 +40,7 @@ def respond(message, history, max_tokens, temperature, top_p):
         response += token
         yield response
 
+# Define the Gradio interface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -38,5 +50,6 @@ demo = gr.ChatInterface(
     ]
 )
 
+# Launch the Gradio app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()