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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("microsoft/Phi-3.5-mini-instruct")
# Predefined prompts
prompts = [
"Tell me a joke about programming",
"Write a short story about a time-traveling robot",
"Explain quantum computing to a 5-year-old",
"Create a recipe for the most unusual pizza",
"Describe an alien civilization's first contact with Earth"
]
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.text_generation(
prompt="\n".join([m["content"] for m in messages]),
max_new_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.token.text
response += token
yield response
def update_textbox(prompt):
return gr.Textbox.update(value=prompt)
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.ClearButton([msg, chatbot])
with gr.Accordion("Advanced options", open=False):
system = gr.Textbox(value="You are a friendly Chatbot.", label="System message")
max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
prompt_dropdown = gr.Dropdown(choices=prompts, label="Select a premade prompt")
prompt_dropdown.change(update_textbox, inputs=[prompt_dropdown], outputs=[msg])
msg.submit(respond, [msg, chatbot, system, max_tokens, temperature, top_p], chatbot)
clear.click(lambda: None, None, chatbot, queue=False)
if __name__ == "__main__":
demo.launch() |