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 = """

Welcome to ChatRxple 💬

""" # 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
-- 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)