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import gradio as gr
import asyncio
from huggingface_hub import InferenceClient
client = InferenceClient("microsoft/Phi-3.5-mini-instruct")
async def respond(
message,
history: list[dict],
system_message,
max_tokens,
temperature,
top_p,
):
# Ensure history is in OpenAI-style 'role' and 'content' format
messages = [{"role": "system", "content": system_message}]
messages.extend(history) # Add existing history
# Add the user's latest message
messages.append({"role": "user", "content": message})
response = ""
async 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
demo = gr.ChatInterface(
fn=respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
chatbot=gr.Chatbot(type="messages"), # Specify the 'messages' format
)
if __name__ == "__main__":
demo.queue().launch() # Simply call queue without `concurrency_count`
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