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import gradio as gr
from huggingface_hub import InferenceClient
"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("R3troR0b/What-If-Explorer")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
# Prepare the prompt based on the message and history
prompt = system_message + "\n"
for val in history:
if val[0]:
prompt += "User: " + val[0] + "\n"
if val[1]:
prompt += "Assistant: " + val[1] + "\n"
prompt += "User: " + message + "\nAssistant:"
response = ""
# Use text-generation instead of chat-completion
for message in client.text_generation(
prompt=prompt,
max_new_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
stream=True,
):
token = message['generated_text'].replace(prompt, '')
response += token
yield response
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
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)",
),
],
)
if __name__ == "__main__":
demo.launch() |