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import gradio as gr
from huggingface_hub import InferenceClient
import os
# Khởi tạo client
client = InferenceClient(
"TheBloke/OpenHermes-2.5-Mistral-7B-GGUF",
)
def generate_text(prompt, system_prompt="", max_new_tokens=512, temperature=0.7, top_p=0.95):
# Chuẩn bị prompt theo định dạng mà mô hình yêu cầu
if system_prompt:
formatted_prompt = f"<|im_start|>system\n{system_prompt}<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
else:
formatted_prompt = f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
# Gọi API inference
response = client.text_generation(
formatted_prompt,
max_new_tokens=max_new_tokens,
temperature=temperature,
top_p=top_p,
stopping_words=["<|im_end|>"]
)
return response
# Tạo Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# OpenHermes-2.5-Mistral-7B API")
with gr.Row():
with gr.Column():
system_prompt = gr.Textbox(label="System Prompt (optional)", lines=2)
prompt = gr.Textbox(label="User Prompt", lines=4)
with gr.Row():
max_tokens = gr.Slider(minimum=64, maximum=2048, value=512, step=64, label="Max New Tokens")
temp = gr.Slider(minimum=0.1, maximum=1.5, 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")
submit_btn = gr.Button("Generate")
with gr.Column():
output = gr.Textbox(label="Generated Output", lines=10)
submit_btn.click(
generate_text,
inputs=[prompt, system_prompt, max_tokens, temp, top_p],
outputs=output
)
# Thêm API endpoint
demo.queue().launch(share=True) |