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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("hackergeek98/gemma-finetuned")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
# Preparing the messages list
messages = [{"role": "system", "content": system_message}]
# Adding conversation history
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
# Adding the new user message
messages.append({"role": "user", "content": message})
# Initialize the response string
response = ""
# Corrected method for chat completion
for message in client.chat_completion(
messages=messages, # Argument should be named 'messages'
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
stream=True # Stream the response
):
# Accumulate the response from the streaming output
token = message.choices[0].delta.content
response += token
yield response
# Gradio interface setup
demo = gr.ChatInterface(
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)"),
],
)
# Run the app
if __name__ == "__main__":
demo.launch()
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