Update app.py

app.py

@@ -1,27 +1,51 @@
 import gradio as gr
-import random
-
-def chat(message, history):
-    history = history or []
-    message_lower = message.lower()
-
-    if "hello" in message_lower or "hi" in message_lower:
-        response = random.choice(["Hello! How can I help you?", "Hi there!", "Hey! What’s up?"])
-    elif "how are you" in message_lower:
-        response = random.choice(["I'm good! Thanks for asking.", "Doing great, how about you?", "All good here!"])
-    elif "your name" in message_lower:
-        response = "I'm your AI chatbot built with Gradio."
-    elif "bye" in message_lower:
-        response = "Goodbye! Have a great day!"
-    else:
-        response = "I'm not sure how to respond to that, but I'm learning!"
-
-    history.append((message, response))
-    return history, history
-
-gr.ChatInterface(
-    fn=chat,
-    title="AI Chatbot",
-    description="A friendly chatbot built with Gradio",
-    theme="soft"
-).launch()
+import torch
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+model_name = "facebook/blenderbot-400M-distill"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name).to(device)
+
+system_preamble = (
+    "You are a friendly, energetic motivational coach. "
+    "Keep answers concise, positive, and actionable. "
+    "When the user asks for exercises or steps, provide a short numbered list. "
+)
+
+def generate_response(history, user_message):
+    conversation = ""
+    for u, r in history:
+        conversation += "User: " + u + "\nCoach: " + r + "\n"
+    conversation += "User: " + user_message + "\nCoach:"
+    prompt = system_preamble + "\n" + conversation
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=1024).to(device)
+    out = model.generate(**inputs, max_new_tokens=256, do_sample=True, top_p=0.9, temperature=0.8)
+    reply = tokenizer.decode(out[0], skip_special_tokens=True).strip()
+    return reply
+
+def chat(user_message, chat_history):
+    if chat_history is None:
+        chat_history = []
+    reply = generate_response(chat_history, user_message)
+    chat_history.append((user_message, reply))
+    return chat_history, chat_history
+
+with gr.Blocks(title="Motivational Coach") as demo:
+    gr.Markdown("<h2 style='text-align:center'>Motivational Coach — powered by BlenderBot</h2>")
+    with gr.Row():
+        chatbot = gr.Chatbot(elem_id="chatbot", label="Coach")
+        with gr.Column(scale=0.3):
+            clear_btn = gr.Button("Clear")
+    msg = gr.Textbox(placeholder="Write your message here...", show_label=False)
+    state = gr.State([])
+
+    def submit_message(message, state):
+        new_history, state_out = chat(message, state)
+        return "", new_history, state_out
+
+    msg.submit(submit_message, inputs=[msg, state], outputs=[msg, chatbot, state])
+    clear_btn.click(lambda: ([], []), None, [chatbot, state])
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)