import gradio as gr from openai import OpenAI from openai import OpenAI from os import getenv client = OpenAI( base_url="https://openrouter.ai/api/v1", api_key=getenv("OPENROUTER_API_KEY"), ) 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 = "" completion = client.chat.completions.create( model="nvidia/llama-3.1-nemotron-70b-instruct", messages=messages, stream=True, # temperature=temperature, # top_p=top_p, # max_tokens=max_tokens, ) for message in completion: token = message.choices[0].delta.content response += token yield response """ For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface """ with gr.Blocks() as demo: credentials = gr.State("") print("CREDENTIALS:") print(credentials) @gr.render(inputs=credentials) def app(app_credentials): if app_credentials == getenv("PASSWORD"): 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)", # ), ], chatbot=gr.Chatbot(height=400) ) else: password = gr.Textbox(placeholder="Provide password...") def set_password(password): return password gr.Button("Login").click(set_password, [password], credentials) if __name__ == "__main__": demo.launch()