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import gradio as gr
import base64
import vertexai
from vertexai.generative_models import GenerativeModel, Part, FinishReason
import vertexai.preview.generative_models as generative_models
# Инициализация Vertex AI
vertexai.init(project="carbide-network-426214-b9", location="us-central1")
# Создание модели
model = GenerativeModel(
"gemini-1.5-pro-001",
)
# Конфигурации генерации и настройки безопасности
generation_config = {
"max_output_tokens": 8192,
"temperature": 1,
"top_p": 0.95,
}
safety_settings = {
generative_models.HarmCategory.HARM_CATEGORY_HATE_SPEECH: generative_models.HarmBlockThreshold.BLOCK_ONLY_HIGH,
generative_models.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: generative_models.HarmBlockThreshold.BLOCK_ONLY_HIGH,
generative_models.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: generative_models.HarmBlockThreshold.BLOCK_ONLY_HIGH,
generative_models.HarmCategory.HARM_CATEGORY_HARASSMENT: generative_models.HarmBlockThreshold.BLOCK_ONLY_HIGH,
}
# Функция генерации текста
def generate(prompt):
responses = model.generate_content(
[prompt],
generation_config=generation_config,
safety_settings=safety_settings,
stream=True,
)
output_text = "".join(response.text for response in responses)
return output_text
# Создание интерфейса Gradio
with gr.Blocks() as demo:
gr.Markdown("### Интерфейс для Hugging Face с использованием Gradio и Vertex AI")
prompt = gr.Textbox(label="Введите ваш запрос", placeholder="Привет! Кто ты?")
output = gr.Textbox(label="Ответ модели")
generate_button = gr.Button("Сгенерировать")
generate_button.click(fn=generate, inputs=prompt, outputs=output)
# Запуск интерфейса
demo.launch()
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