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import gradio as gr | |
import os | |
import requests | |
API_TOKEN = os.getenv("HF_READ_TOKEN") | |
headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
def gen(prompt, model='gpt'): | |
if prompt == "" or prompt == None: | |
return None | |
if model == 'gpt': | |
API_URL = "https://api-inference.huggingface.co/models/openchat/openchat_3.5" | |
payload = { | |
"inputs": prompt | |
} | |
response = requests.post(API_URL, headers=headers, json=payload) | |
if response.status_code != 200: | |
print(f"Ошибка: Не удалось получить ответ. Статус ответа: {response.status_code}") | |
print(f"Содержимое ответа: {response.text}") | |
return f"Произошла ошибка ({response.text})" | |
return response.json() | |
css = """ | |
footer {visibility: hidden !important;} | |
""" | |
with gr.Blocks(css=css) as ui: | |
with gr.Tab("Генерация"): | |
with gr.Row(): | |
prompt = gr.Textbox(label="Prompt", lines=3) | |
with gr.Tab("Параметры"): | |
with gr.Row(): | |
gr.Markdown("## Скоро...") | |
text_button = gr.Button("Генерация", variant='primary', elem_id="generate") | |
text_output = gr.Textbox(show_label=False, placeholder="Привет! Чем я могу вам помочь?") | |
text_button.click(gen, inputs=[prompt], outputs=text_output) | |
#end | |
ui.queue(api_open=False).launch() |