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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) | |
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() |