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app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model and tokenizer
+model_name_or_path = "tencent/Hunyuan-MT-7B"
+print("Loading model... This may take a few minutes.")
+
+tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name_or_path,
+    torch_dtype=torch.bfloat16 if torch.cuda.is_available() else torch.float32,
+    device_map="auto"
+)
+
+def respond(message, history, system_message, max_tokens, temperature, top_p):
+    """
+    Generate response from Hunyuan-MT model
+    """
+    # Build conversation history
+    messages = []
+    
+    # Add system message if provided
+    if system_message:
+        messages.append({"role": "system", "content": system_message})
+    
+    # Add conversation history
+    for user_msg, assistant_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        if assistant_msg:
+            messages.append({"role": "assistant", "content": assistant_msg})
+    
+    # Add current message
+    messages.append({"role": "user", "content": message})
+    
+    # Tokenize the conversation
+    tokenized_chat = tokenizer.apply_chat_template(
+        messages,
+        tokenize=True,
+        add_generation_prompt=True,
+        return_tensors="pt"
+    )
+    
+    # Generate response
+    with torch.no_grad():
+        outputs = model.generate(
+            tokenized_chat.to(model.device),
+            max_new_tokens=max_tokens,
+            temperature=temperature,
+            top_p=top_p,
+            do_sample=True if temperature > 0 else False,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    
+    # Decode only the new tokens
+    response = tokenizer.decode(outputs[0][tokenized_chat.shape[-1]:], skip_special_tokens=True)
+    
+    return response
+
+# Create Gradio interface
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(
+            value="You are a helpful AI assistant.",
+            label="System Message",
+            lines=2
+        ),
+        gr.Slider(
+            minimum=1,
+            maximum=2048,
+            value=512,
+            step=1,
+            label="Max New Tokens"
+        ),
+        gr.Slider(
+            minimum=0,
+            maximum=2,
+            value=0.7,
+            step=0.1,
+            label="Temperature"
+        ),
+        gr.Slider(
+            minimum=0,
+            maximum=1,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)"
+        ),
+    ],
+    title="Hunyuan-MT-7B Chatbot",
+    description="Chat with Tencent's Hunyuan-MT-7B model. This model is particularly good at translation tasks.",
+    examples=[
+        ["Translate to Chinese: It's on the house."],
+        ["What are the main differences between Python and JavaScript?"],
+        ["Explain quantum computing in simple terms."],
+    ],
+    theme="soft"
+)
+
+if __name__ == "__main__":
+    demo.launch()