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import gradio as gr
from huggingface_hub import InferenceClient
# Define available models (update with your actual model IDs)
model_list = {
"Safe LM": "HuggingFaceH4/zephyr-7b-beta", # Replace with your Safe LM model ID
"Zephyr Beta": "HuggingFaceH4/zephyr-7b-beta",
"Another Model": "HuggingFaceH4/zephyr-7b-beta"
}
def respond(message, history, system_message, max_tokens, temperature, top_p, selected_model):
# Look up the model ID from our list based on the dropdown selection
model_id = model_list.get(selected_model, "HuggingFaceH4/zephyr-7b-beta")
# Create an InferenceClient for the selected model
client = InferenceClient(model_id)
# Build the conversation history into the message list
messages = [{"role": "system", "content": system_message}]
for user_msg, assistant_msg in history or []:
if user_msg:
messages.append({"role": "user", "content": user_msg})
if assistant_msg:
messages.append({"role": "assistant", "content": assistant_msg})
messages.append({"role": "user", "content": message})
response = ""
# Stream the response from the client
for token_message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = token_message.choices[0].delta.content
response += token
yield response
# CSS styling: pastel backgrounds, gentle light colors, and rounded corners for a safe vibe
css = """
body { background-color: #FAF3E0; }
.gradio-container { background-color: #FFFFFF; border-radius: 16px; padding: 20px; }
button, input, .gradio-dropdown, .gradio-slider, textarea { border-radius: 16px; }
.gradio-chat { border-radius: 16px; }
"""
with gr.Blocks(css=css) as demo:
with gr.Row():
# Left sidebar: Model selector
with gr.Column(scale=1):
gr.Markdown("## Models")
model_dropdown = gr.Dropdown(
choices=list(model_list.keys()),
label="Select Model",
value="Safe LM"
)
# Main area: Chat interface and settings
with gr.Column(scale=3):
gr.Markdown("## Chat Interface")
chatbot = gr.Chatbot(label="Chat with your Model")
user_input = gr.Textbox(placeholder="Enter your message...", label="Your Message")
with gr.Row():
send_button = gr.Button("Send")
clear_button = gr.Button("Clear Chat")
gr.Markdown("### Chat Settings")
system_message = gr.Textbox(value="You are a friendly Chatbot.", label="System Message")
max_tokens_slider = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens")
temperature_slider = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
# When "Send" is clicked, run the respond() function and update the chat interface.
send_button.click(
fn=respond,
inputs=[user_input, chatbot, system_message, max_tokens_slider, temperature_slider, top_p_slider, model_dropdown],
outputs=[user_input, chatbot],
)
# Clear the chat history when "Clear Chat" is clicked.
clear_button.click(lambda: None, None, chatbot, queue=False)
if __name__ == "__main__":
demo.launch()
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