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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
for user_text, assistant_text in history:
if user_text:
messages.append({"role": "user", "content": user_text})
if assistant_text:
messages.append({"role": "assistant", "content": assistant_text})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
# The additional_inputs are now hidden by setting visible=False.
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(
value="You are a friendly Chatbot. Respond only in bisaya language. No english translation.",
label="System message",
visible=False,
),
gr.Slider(
minimum=1,
maximum=2048,
value=512,
step=1,
label="Max new tokens",
visible=False,
),
gr.Slider(
minimum=0.1,
maximum=4.0,
value=0.7,
step=0.1,
label="Temperature",
visible=False,
),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
visible=False,
),
],
)
if __name__ == "__main__":
demo.launch()
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