import gradio as gr | |
from datasets import load_dataset | |
dataset = load_dataset("ruslanmv/ai-medical-chatbot") | |
dataset = dataset.remove_columns("Description") | |
train_data = dataset["train"] | |
print(train_data) | |
# 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 | |
# """ | |
# 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() |