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Update app.py
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app.py
CHANGED
@@ -2,7 +2,6 @@ from transformers import AutoTokenizer, T5ForConditionalGeneration
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import torch
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import gradio as gr
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import re
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import json
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tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base-multitask", legacy=False)
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model = T5ForConditionalGeneration.from_pretrained("cointegrated/rut5-base-multitask")
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@@ -13,16 +12,17 @@ def smart_truncate(text, max_len):
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return text[:text[:max_len+1].rfind(' ')].strip()
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def generate_meta(description):
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#
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prompt = f"""
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Create a title and description for product page.
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Product name: Fenix ARB-L18-4000U
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Description:
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Output format:
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{
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"""
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inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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@@ -31,36 +31,39 @@ Output format:
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early_stopping=True,
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no_repeat_ngram_size=2
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)
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try:
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result = tokenizer.decode(outputs[0], skip_special_tokens=True)
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json_data
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clean_text = re.sub(r'\s+', ' ', description)
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# Интерфейс
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with gr.Blocks() as app:
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gr.Markdown("## Генератор метатегов (контроль длины)")
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inp = gr.Textbox(label="Описание товара", lines=7)
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btn = gr.Button("Сгенерировать")
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with gr.Row():
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out_title = gr.Textbox(label="Title (до 60 символов)", interactive=False)
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out_desc = gr.Textbox(label="Description (до 160 символов)", lines=3, interactive=False)
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app.launch()
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import torch
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import gradio as gr
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import re
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tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base-multitask", legacy=False)
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model = T5ForConditionalGeneration.from_pretrained("cointegrated/rut5-base-multitask")
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return text[:text[:max_len+1].rfind(' ')].strip()
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def generate_meta(description):
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# Пример промта для модели
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prompt = f"""
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Create a title and description for product page.
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Product name: Fenix ARB-L18-4000U
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Description: {description.strip()}
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Output format:
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{"title": "SEO заголовок до 60 символов", "description": "SEO описание до 160 символов"}
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"""
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inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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early_stopping=True,
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no_repeat_ngram_size=2
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)
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try:
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result = tokenizer.decode(outputs[0], skip_special_tokens=True)
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json_match = re.search(r'\{.*\}', result, re.DOTALL)
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if json_match:
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json_data = json.loads(json_match.group())
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title = smart_truncate(json_data.get("title", ""), 60)
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desc = smart_truncate(json_data.get("description", ""), 160)
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else:
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clean_text = re.sub(r'\s+', ' ', description)
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title = smart_truncate(f"Аккумулятор Fenix {clean_text}", 60)
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desc = smart_truncate(clean_text, 160)
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except Exception as e:
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clean_text = re.sub(r'\s+', ' ', description)
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title = smart_truncate(f"Аккумулятор Fenix {clean_text}", 60)
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desc = smart_truncate(clean_text, 160)
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return title, desc # ✅ Здесь важно — возвращать 2 отдельные строки
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# Интерфейс
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with gr.Blocks() as app:
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gr.Markdown("## Генератор метатегов (контроль длины)")
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inp = gr.Textbox(label="Описание товара", lines=7)
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btn = gr.Button("Сгенерировать")
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with gr.Row():
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out_title = gr.Textbox(label="Title (до 60)", interactive=False)
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out_desc = gr.Textbox(label="Description (до 160)", lines=3, interactive=False)
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btn.click(fn=generate_meta, inputs=inp, outputs=[out_title, out_desc])
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app.launch()
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