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Update app.py
Browse files
app.py
CHANGED
@@ -19,10 +19,9 @@ def get_image_base64(path):
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@st.cache_resource # Кэширование модели для ускорения работы
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def load_model():
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return model
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@st.cache_resource
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class ModelWrapper(object):
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MODELS_DIR: str = "./new_models/"
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MODEL_NAME: str = "model"
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@@ -54,10 +53,9 @@ class ModelWrapper(object):
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) # output is logits for huggingfcae transformers
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predicted = torch.nn.functional.softmax(outputs.logits, dim=1)
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predicted_id = torch.argmax(predicted, dim=1).numpy()[0]
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return self.id2label[predicted_id]
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model_BERT=ModelWrapper()
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bin_str = get_image_base64("./билли.png")
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page_bg_img = '''
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@@ -112,41 +110,22 @@ model_type = st.radio(
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)
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def highlight_obscene_words(text, model_type):
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)
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else:
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st.markdown(
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"<span style='background:#ffcccc;'>{}|токсично</span>".format(text),
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unsafe_allow_html=True
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)
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elif model_type=="ru-BERT":
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label=model_BERT(text.lower())
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if label=='__label__positive':
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st.markdown(
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"<span style='background:#47916B;'>{}|приемлемо</span>".format(text),
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unsafe_allow_html=True
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)
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else:
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st.markdown(
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"<span style='background:#ffcccc;'>{}|токсично</span>".format(text),
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unsafe_allow_html=True
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)
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else:
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#ЗАГЛУШКА
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st.markdown(
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if st.button("Проверить текст"):
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if user_input.strip():
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st.subheader("Результат:")
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result = re.split(r'[.\n]+', user_input)
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result = [part for part in result if part.strip() != ""]
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if result!=[]:
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for text in result:
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@st.cache_resource # Кэширование модели для ускорения работы
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def load_model():
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return ModelWrapper()
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"""@st.cache_resource
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class ModelWrapper(object):
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MODELS_DIR: str = "./new_models/"
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MODEL_NAME: str = "model"
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) # output is logits for huggingfcae transformers
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predicted = torch.nn.functional.softmax(outputs.logits, dim=1)
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predicted_id = torch.argmax(predicted, dim=1).numpy()[0]
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return self.id2label[predicted_id]"""
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model_wrapper= load_model()
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bin_str = get_image_base64("./билли.png")
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page_bg_img = '''
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)
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def highlight_obscene_words(text, model_type):
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label=model_wrapper(text.lower(),model_type)
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if label=='__label__positive':
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st.markdown(
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"<span style='background:#47916B;'>{}|приемлемо</span>".format(text),
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unsafe_allow_html=True
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)
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else:
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st.markdown(
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"<span style='background:#ffcccc;'>{}|токсично</span>".format(text),
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unsafe_allow_html=True
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)
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if st.button("Проверить текст"):
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if user_input.strip():
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st.subheader("Результат:")
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result = re.split(r'[.\n!?]+', user_input)
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result = [part for part in result if part.strip() != ""]
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if result!=[]:
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for text in result:
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