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Update app.py
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app.py
CHANGED
@@ -11,7 +11,7 @@ from langchain.chains import ConversationalRetrievalChain
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from htmlTemplates import css, bot_template, user_template
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from langchain.llms import HuggingFaceHub
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from deep_translator import GoogleTranslator
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-
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# set this key as an environment variable
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os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets['huggingface_token']
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###########################################################################################
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@@ -142,6 +142,17 @@ def main():
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with st.sidebar:
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st.subheader("Your documents")
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pdf_docs = st.file_uploader(
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"Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
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@@ -163,6 +174,7 @@ def main():
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#compelete build model
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st.write("compelete build model")
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if __name__ == "__main__":
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main()
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from htmlTemplates import css, bot_template, user_template
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from langchain.llms import HuggingFaceHub
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from deep_translator import GoogleTranslator
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import pandas as pd
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# set this key as an environment variable
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os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets['huggingface_token']
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###########################################################################################
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with st.sidebar:
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# تعریف یک لیست خالی برای ذخیره رکوردها
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records = []
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# اضافه کردن ورودیها در Streamlit
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element_a = st.text_input('عنصر اول را وارد کنید')
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element_b = st.text_input('عنصر دوم را وارد کنید')
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# دکمه برای اضافه کردن رکورد به لیست و ذخیره در فایل اکسل
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if st.button('ذخیره رکورد'):
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records.append({'A': element_a, 'B': element_b})
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df = pd.DataFrame(records)
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df.to_excel('output.xlsx', index=False)
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st.success('رکورد با موفقیت ذخیره شد!')
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st.subheader("Your documents")
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pdf_docs = st.file_uploader(
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"Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
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#compelete build model
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st.write("compelete build model")
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if __name__ == "__main__":
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main()
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