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from huggingface_hub import AsyncInferenceClient
import gradio as gr
client = AsyncInferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
def format_prompt(prompt: str, history: list[str], system_prompt: str) -> str:
if not history:
final_prompt = (
f"[INST] {system_prompt if system_prompt else ''}:\n{prompt} [/INST]"
)
else:
formatted_history = "".join(
f"[INST] {user_prompt} [/INST]{bot_response}</s> "
for user_prompt, bot_response in history
)
final_prompt = f"<s>{formatted_history}[INST] {prompt} [/INST]"
return final_prompt
async def generate(
prompt: str,
history: list[str],
system_prompt: str = "You're a helpful assistant.",
temperature: float = 0.3,
max_new_tokens: int = 4000,
top_p: float = 0.95,
repetition_penalty: float = 1.0,
):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=False,
seed=42,
)
formatted_prompt = format_prompt(
prompt=prompt, history=history, system_prompt=system_prompt
)
stream = await client.text_generation(
formatted_prompt,
**generate_kwargs,
stream=True,
details=True,
return_full_text=True,
)
output = f""
async for response in stream:
output += response.token.text
yield output
additional_inputs = [
gr.Textbox(
label="System Prompt (optional)",
value="You're a helpful assistant.",
info="This is experimental",
placeholder="system prompt",
),
gr.Slider(
label="Temperature",
value=0.9,
minimum=0.0,
maximum=1.0,
step=0.05,
interactive=True,
info="Higher values produce more diverse outputs",
),
gr.Slider(
label="Max new tokens",
value=256,
minimum=0,
maximum=1048,
step=64,
interactive=True,
info="The maximum numbers of new tokens",
),
gr.Slider(
label="Top-p (nucleus sampling)",
value=0.90,
minimum=0.0,
maximum=1,
step=0.05,
interactive=True,
info="Higher values sample more low-probability tokens",
),
gr.Slider(
label="Repetition penalty",
value=1.2,
minimum=1.0,
maximum=2.0,
step=0.05,
interactive=True,
info="Penalize repeated tokens",
),
]
chatbot = gr.Chatbot(
avatar_images=["./user.png", "./bot.png"],
bubble_full_width=False,
show_label=False,
show_copy_button=True,
likeable=True,
)
demo = gr.ChatInterface(
fn=generate,
additional_inputs=additional_inputs,
chatbot=chatbot,
title="🪷",
description="Mixtral-8x7B-Instruct-v0.1",
concurrency_limit=20,
)
demo.queue().launch()
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