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"""
cf https://huggingface.co/spaces/Nymbo/Qwen-2.5-72B-Instruct/blob/main/app.py
https://huggingface.co/spaces/prithivMLmods/Llama-3.1-8B-Instruct/blob/main/app.py
https://github.com/huggingface/huggingface-llama-recipes/blob/main/api_inference/inference-api.ipynb
"""
import gradio as gr
# from openai import OpenAI
from huggingface_hub import InferenceClient
import os
# ACCESS_TOKEN = os.getenv("HF_TOKEN")
_ = """
client = OpenAI(
base_url="https://api-inference.huggingface.co/v1/",
api_key=ACCESS_TOKEN,
)
# """
client = InferenceClient()
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 = ""
try:
_ = client.chat.completions.create(
model="Qwen/Qwen2.5-72B-Instruct",
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
messages=messages,
)
for message in _:
token = message.choices[0].delta.content
response += token
yield response
except Exception as e:
yield str(e)
chatbot = gr.Chatbot(height=600)
css = '''
.gradio-container{max-width: 1000px !important}
h1{text-align:center}
footer {
visibility: hidden
}
'''
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="", label="System message"),
# gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=1, maximum=32768 // 2 - 500, value=32768 // 2 - 500, 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",
),
],
fill_height=True,
chatbot=chatbot,
css=css,
# theme="allenai/gradio-theme",
# theme="Nymbo/Alyx_Theme",
)
if __name__ == "__main__":
demo.launch() |