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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("Qwen/Qwen2.5-Coder-32B-Instruct")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
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
# Custom CSS to change the title color and add logo
opq = """
.gradio-container h1 {
color: #6495ED !important;
display: flex;
align-items: center;
}
"""
# Custom HTML to inject the logo
custom_html = """
<div>
<h1> Welcome to Rxple Chat Bot 馃挰</h1>
</div>
"""
# Combined description with new lines
combined_description = """
Ghar ka ai this AI does not store any data you can use as much you want without logging<br>
-- Follow us on [Instagram](https://www.instagram.com/khellon_patel_21) --
"""
# Use the custom_html for the title
demo = gr.ChatInterface(
respond,
title=custom_html, # Use the custom HTML for the title
description=combined_description,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=2048, 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)",
),
],
css=opq # Add the custom CSS here
)
if __name__ == "__main__":
demo.launch(share=True) |