Create app.py

app.py

@@ -0,0 +1,45 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Load model and tokenizer
+model_name = "Smilyai-labs/Sam-large-v1-speacil"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+# Chat function
+def respond(message, history):
+    history = history or []
+    chat_prompt = ""
+    for user, bot in history:
+        chat_prompt += f"User: {user}\nSam: {bot}\n"
+    chat_prompt += f"User: {message}\nSam:"
+
+    inputs = tokenizer(chat_prompt, return_tensors="pt").to(device)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=128,
+        temperature=0.7,
+        top_p=0.9,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    reply = response[len(chat_prompt):].split("\n")[0].strip()
+
+    history.append((message, reply))
+    return history, history
+
+# Gradio interface
+chatbot = gr.Chatbot()
+demo = gr.Interface(
+    fn=respond,
+    inputs=[gr.Textbox(label="Your message"), gr.State()],
+    outputs=[chatbot, gr.State()],
+    title="🧠 Sam Chatbot",
+    description="A demo of Sam-large-v1-speacil: chaotic, aligned, and fun."
+)
+
+demo.launch()