Update app.py

app.py

@@ -4,74 +4,75 @@ from transformers import pipeline
 # Initialize the conversational model pipeline
 chatbot_pipeline = pipeline("text-generation", model="Aditya0619/Medbot")
 
-# Function to manage history and generate responses
+# Chatbot response function
 def respond(message, history, system_message, max_tokens, temperature, top_p):
-    # Initialize history if it's None
     if history is None:
         history = []
 
-    # Build input by concatenating past messages
+    # Build conversation context
     chat_input = ""
     for user_input, bot_response in history:
         chat_input += f"User: {user_input}\nBot: {bot_response}\n"
     chat_input += f"User: {message}\nBot:"
 
-    # Generate a response using the pipeline
+    # Generate response
     response = chatbot_pipeline(
         chat_input,
         max_length=max_tokens,
         temperature=temperature,
         top_p=top_p,
-        pad_token_id=50256  # Avoid padding issues for models like GPT-2 variants
+        pad_token_id=50256  # Avoid padding issues with GPT-2 models
     )[0]["generated_text"].split("Bot:")[-1].strip()
 
-    # Update the conversation history
+    # Update history
     history.append((message, response))
-
-    # Return the updated chat history
     return history, history
 
-# Define the Gradio app layout
+# API function to expose chatbot responses programmatically
+def api_chat(message, history=None):
+    if history is None:
+        history = []
+    updated_history, _ = respond(
+        message, history, "", max_tokens=250, temperature=0.7, top_p=0.9
+    )
+    return {"response": updated_history[-1][1], "history": updated_history}
+
+# Gradio UI layout
 with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 AI Chatbot with Memory\nChat with me! I’ll remember your messages.")
+    gr.Markdown("# 🤖 AI Chatbot with API Access\nChat with AI or use the API!")
 
-    # Taskbar with configurable parameters
+    # Configurable parameters in an accordion menu
     with gr.Row():
         with gr.Accordion("⚙️ Configure Chatbot Settings", open=False):
-            system_message = gr.Textbox(
-                label="System Message (Optional)",
-                placeholder="e.g., You are a helpful assistant."
-            )
-            max_tokens = gr.Slider(
-                label="Max Tokens", minimum=50, maximum=500, value=250, step=10
-            )
-            temperature = gr.Slider(
-                label="Temperature", minimum=0.0, maximum=1.0, value=0.7, step=0.1
-            )
-            top_p = gr.Slider(
-                label="Top P", minimum=0.0, maximum=1.0, value=0.9, step=0.1
-            )
+            system_message = gr.Textbox(label="System Message (Optional)", placeholder="e.g., You are a helpful assistant.")
+            max_tokens = gr.Slider(label="Max Tokens", minimum=50, maximum=500, value=250, step=10)
+            temperature = gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.7, step=0.1)
+            top_p = gr.Slider(label="Top P", minimum=0.0, maximum=1.0, value=0.9, step=0.1)
 
-    # Chatbot and user input section
+    # Chatbot interface and user input field
     chatbot = gr.Chatbot(label="Chat with AI")
     user_input = gr.Textbox(label="Your Message", placeholder="Type a message...", lines=2)
-
-    # Hidden state to store the conversation history
-    state = gr.State([])
-
-    # Submit button
+    state = gr.State([])  # Store conversation history
     submit = gr.Button("Send")
 
-    # Connect user input to the chatbot response function
+    # Link input to chatbot response
     submit.click(
         respond,
         inputs=[user_input, state, system_message, max_tokens, temperature, top_p],
         outputs=[chatbot, state]
     )
 
-    # Display an initial greeting message
+    # Initial greeting message
     demo.load(lambda: [("Hi! How can I assist you today?", "")], outputs=chatbot)
 
-# Launch the Gradio app
-demo.launch()
+# Launch Gradio app and print the hosted link in terminal
+print("Launching the Gradio app...")
+
+ui_url = demo.launch(share=True, server_name="0.0.0.0", server_port=7860)
+print(f"App hosted at: {ui_url}")
+
+# API endpoint setup with Gradio
+api = gr.Interface(fn=api_chat, inputs=[gr.Textbox(), gr.State([])], outputs="json")
+api_url = api.launch(share=True, server_name="0.0.0.0", server_port=7861)
+print(f"API hosted at: {api_url}")