Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the text-generation pipeline
+pipe = pipeline(
+    "text-generation",
+    model="ibm-granite/granite-3.3-2b-instruct",
+)
+
+def chat(user_input, history):
+    # Convert chat history to Granite-compatible message format
+    messages = []
+    for user_msg, bot_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        messages.append({"role": "assistant", "content": bot_msg})
+
+    messages.append({"role": "user", "content": user_input})
+
+    # Generate response
+    output = pipe(
+        messages,
+        max_new_tokens=256,
+        do_sample=True,
+        temperature=0.7,
+        top_p=0.9,
+    )
+
+    # Extract assistant reply
+    assistant_reply = output[0]["generated_text"][-1]["content"]
+
+    return assistant_reply
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🤖 IBM Granite 3.3 Chatbot")
+    gr.Markdown("Powered by **ibm-granite/granite-3.3-2b-instruct**")
+
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(
+        placeholder="Ask me anything...",
+        label="Your message"
+    )
+    clear = gr.Button("Clear")
+
+    def respond(message, chat_history):
+        bot_message = chat(message, chat_history)
+        chat_history.append((message, bot_message))
+        return "", chat_history
+
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    clear.click(lambda: [], None, chatbot)
+
+demo.launch()