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import streamlit as st
from transformers import pipeline
# تحميل النموذج
classifier = pipeline("zero-shot-classification", model="cross-encoder/nli-distilroberta-base")
# عنوان التطبيق
st.title("Text Classification App")
# إدخال الملف النصي
uploaded_file = st.file_uploader("Upload a text file containing keywords", type=["txt"])
if uploaded_file is not None:
# قراءة الملف النصي
content = uploaded_file.read().decode("utf-8")
keywords = [line.strip() for line in content.splitlines() if line.strip()]
# تحديد الفئات
categories = ["shopping", "gaming", "streaming"]
# قوائم لتخزين الكلمات حسب الفئة
shopping_words = []
gaming_words = []
streaming_words = []
# تصنيف الكلمات
for word in keywords:
result = classifier(word, categories)
best_category = result['labels'][0]
if best_category == "shopping":
shopping_words.append(word)
elif best_category == "gaming":
gaming_words.append(word)
elif best_category == "streaming":
streaming_words.append(word)
# عرض النتائج في مربعات نصية قابلة للنسخ
st.header("Shopping Keywords")
st.text_area("Copy the shopping keywords here:", value="\n".join(shopping_words), height=200)
st.header("Gaming Keywords")
st.text_area("Copy the gaming keywords here:", value="\n".join(gaming_words), height=200)
st.header("Streaming Keywords")
st.text_area("Copy the streaming keywords here:", value="\n".join(streaming_words), height=200)
else:
st.warning("Please upload a text file to classify the keywords.") |