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import gradio as gr
# Placeholder for model loading (adjust as needed for your specific models)
def load_model(model_name):
# Replace this function with actual model loading code if needed
return lambda input_text: f"Response from {model_name}: {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")
# Disable API names for all functions (Gradio doesn't natively use `fns`)
# Adjust this section if specific API name disabling logic is required.
# Define the optional parameters section
def create_optional_parameters():
with gr.Accordion("Optional Parameters (Click to Expand)", 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)")
return system_message, max_new_tokens, temperature, top_p
# Define the main interface
def chat_interface(user_input, system_message, max_new_tokens, temperature, top_p):
# Placeholder response - integrate with actual model here
response = f"""**System Message**: {system_message}
**Your Input**: {user_input}
**Parameters Used**:
- Max New Tokens: {max_new_tokens}
- Temperature: {temperature}
- Top-p: {top_p}
*Note: Actual model integration required for real responses*"""
return response
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# DeepSeek Chatbot\nCreated by [ruslanmv.com](https://ruslanmv.com/)")
with gr.Row():
with gr.Column():
user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...", lines=3)
submit_button = gr.Button("Submit", variant="primary")
with gr.Column():
output = gr.Markdown(label="Chatbot Response")
# Add the optional parameters section
system_message, max_new_tokens, temperature, top_p = create_optional_parameters()
# Link the submit button to the chat interface
submit_button.click(
chat_interface,
inputs=[user_input, system_message, max_new_tokens, temperature, top_p],
outputs=output
)
# Launch the demo
if __name__ == "__main__":
demo.launch()
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