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import gradio as gr | |
# Placeholder for model loading (adjust as needed for your specific models) | |
# In a real application, these would load actual models | |
def load_model(model_name): | |
print(f"Loading {model_name}...") # Indicate model loading | |
# Simulate different model behaviors (replace with actual model logic) | |
if model_name == "DeepSeek-R1-Distill-Qwen-32B": | |
return lambda input_text, history: f"Distilled Model Response to: {input_text}" | |
elif model_name == "DeepSeek-R1": | |
return lambda input_text, history: f"Base Model Response to: {input_text}" | |
elif model_name == "DeepSeek-R1-Zero": | |
return lambda input_text, history: f"Zero Model Response to: {input_text}" | |
else: | |
return lambda input_text, history: f"Default Response to: {input_text}" | |
# Load the models (placeholder functions here) | |
deepseek_r1_distill = load_model("DeepSeek-R1-Distill-Qwen-32B") | |
deepseek_r1 = load_model("DeepSeek-R1") | |
deepseek_r1_zero = load_model("DeepSeek-R1-Zero") | |
# --- Chatbot function --- | |
def chatbot(input_text, history, model_choice, system_message, max_new_tokens, temperature, top_p): | |
history = history or [] | |
print(f"Input: {input_text}, History: {history}, Model: {model_choice}") | |
# Choose the model based on user selection | |
if model_choice == "DeepSeek-R1-Distill-Qwen-32B": | |
model_function = deepseek_r1_distill | |
elif model_choice == "DeepSeek-R1": | |
model_function = deepseek_r1 | |
elif model_choice == "DeepSeek-R1-Zero": | |
model_function = deepseek_r1_zero | |
else: | |
model_function = lambda x, h: "Please select a model." | |
# Simulate model response with parameters (replace with actual model inference) | |
# In a real application, you would pass these parameters to your model | |
response = model_function(input_text, history) | |
response = f"**System Message:** {system_message}\n\n**Model Response:** {response}\n\n" \ | |
f"**Parameters Used:**\n- Max New Tokens: {max_new_tokens}\n- Temperature: {temperature}\n- Top-p: {top_p}" | |
history.append((input_text, response)) | |
return history, history, "" # Update both chatbot output and state | |
# --- Gradio Interface --- | |
with gr.Blocks(theme=gr.themes.Soft()) as demo: # Apply a theme | |
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(scale=4): # Make chatbot take more space | |
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.Column(scale=1): | |
model_choice = gr.Radio( | |
choices=["DeepSeek-R1-Distill-Qwen-32B", "DeepSeek-R1", "DeepSeek-R1-Zero"], | |
label="Choose a Model", | |
value="DeepSeek-R1" # Default model | |
) | |
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)" | |
) | |
# Maintain chat history | |
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], | |
) | |
# Launch the demo | |
if __name__ == "__main__": | |
demo.launch() |