app.py

# app.py
# =============
# This is a complete app.py file for deploying the MTSAIR/Cotype-Nano model using Gradio and Hugging Face Transformers.

import gradio as gr
from transformers import pipeline

# Load the model and pipeline
model_name = "MTSAIR/Cotype-Nano"
pipe = pipeline("text-generation", model=model_name, device="cpu")

# Define the system prompt
system_prompt = {"role": "system", "content": "Ты — ИИ-помощник. Тебе дано задание: необходимо сгенерировать подробный и развернутый ответ."}

# Define the Gradio interface
def generate_response(user_input):
    messages = [
        system_prompt,
        {"role": "user", "content": user_input}
    ]
    response = pipe(messages, max_length=1024)
    return response[0]['generated_text']

# Create the Gradio interface
iface = gr.Interface(
    fn=generate_response,
    inputs=gr.inputs.Textbox(lines=2, placeholder="Введите ваш запрос здесь..."),
    outputs="text",
    title="Cotype-Nano Text Generation",
    description="Введите ваш запрос, и Cotype-Nano сгенерирует ответ."
)

# Launch the interface
if __name__ == "__main__":
    iface.launch()