Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# -------------------------
+# HuggingFace model to use
+# -------------------------
+MODEL_NAME = "tiiuae/falcon-7b-instruct"  # you can change to any hosted model
+
+# -------------------------
+# Load model and tokenizer
+# -------------------------
+print("Loading model...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
+
+# -------------------------
+# System prompt
+# -------------------------
+SYSTEM_PROMPT = (
+    "You are a helpful, creative AI assistant. "
+    "Your creator is Austin. Answer clearly and politely."
+)
+
+# -------------------------
+# Chat function
+# -------------------------
+def chat_with_ai(user_input, history=[]):
+    full_prompt = SYSTEM_PROMPT + "\n"
+    for i, (u, r) in enumerate(history):
+        full_prompt += f"User: {u}\nAI: {r}\n"
+    full_prompt += f"User: {user_input}\nAI:"
+
+    inputs = tokenizer(full_prompt, return_tensors="pt").to(device)
+    outputs = model.generate(**inputs, max_new_tokens=200)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = response.split("AI:")[-1].strip()
+
+    history.append((user_input, response))
+    return response, history
+
+# -------------------------
+# Build Gradio GUI
+# -------------------------
+with gr.Blocks() as demo:
+    gr.Markdown("# Austin's AI Chatbot")
+    gr.Markdown("This chatbot was created by **Austin**. Chat with it below!")
+
+    chatbot = gr.Chatbot()
+    user_input = gr.Textbox(placeholder="Type your message here...")
+    submit_btn = gr.Button("Send")
+    history_state = gr.State([])
+
+    submit_btn.click(
+        chat_with_ai,
+        inputs=[user_input, history_state],
+        outputs=[chatbot, history_state]
+    )
+
+# Launch app
+demo.launch()