import gradio as gr from models import demo # Import the demo object from models.py # --- Chatbot function --- def chatbot(input_text, history, model_choice, system_message, max_new_tokens, temperature, top_p): history = history or [] # Create payload for the model payload = { "messages": [{"role": "user", "content": input_text}], "system": system_message, "max_tokens": max_new_tokens, "temperature": temperature, "top_p": top_p } # Run inference using the selected model try: response = demo(payload) # Use the demo object directly if isinstance(response, dict) and "choices" in response: assistant_response = response["choices"][0]["message"]["content"] else: assistant_response = "Unexpected model response format." except Exception as e: assistant_response = f"Error: {str(e)}" # Append user and assistant messages to history history.append((input_text, assistant_response)) return history, history, "" # --- Gradio Interface --- with gr.Blocks(theme=gr.themes.Soft(), title="DeepSeek Chatbot") as app: gr.Markdown( """ # DeepSeek Chatbot Created by [ruslanmv.com](https://ruslanmv.com/) This is a demo of different DeepSeek models. Select a model, type your message, and click "Submit". You can also adjust optional parameters like system message, max new tokens, temperature, and top-p. """ ) with gr.Row(): with gr.Column(): chatbot_output = gr.Chatbot(label="DeepSeek Chatbot", height=500) msg = gr.Textbox(label="Your Message", placeholder="Type your message here...") with gr.Row(): submit_btn = gr.Button("Submit", variant="primary") clear_btn = gr.ClearButton([msg, chatbot_output]) with gr.Row(): with gr.Accordion("Options", open=True): model_choice = gr.Radio( choices=["DeepSeek-R1-Distill-Qwen-32B", "DeepSeek-R1", "DeepSeek-R1-Zero"], label="Choose a Model", value="DeepSeek-R1" ) with gr.Accordion("Optional Parameters", open=False): system_message = gr.Textbox( label="System Message", value="You are a friendly Chatbot created by ruslanmv.com", lines=2, ) max_new_tokens = gr.Slider( minimum=1, maximum=4000, value=200, label="Max New Tokens" ) temperature = gr.Slider( minimum=0.10, maximum=4.00, value=0.70, label="Temperature" ) top_p = gr.Slider( minimum=0.10, maximum=1.00, value=0.90, label="Top-p (nucleus sampling)" ) chat_history = gr.State([]) # Event handling submit_btn.click( chatbot, [msg, chat_history, model_choice, system_message, max_new_tokens, temperature, top_p], [chatbot_output, chat_history, msg] ) msg.submit( chatbot, [msg, chat_history, model_choice, system_message, max_new_tokens, temperature, top_p], [chatbot_output, chat_history, msg] ) if __name__ == "__main__": app.launch()