Create app.py
Browse files
app.py
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from annotated_text import annotated_text
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import streamlit as st
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import openai
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# API ํค ์ค์ (์ค์ OpenAI API ํค๋ก ๋์ฒดํด์ผ ํจ)
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openai.api_key = "your-openai-api-key"
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# Streamlit ์ฑ ์์
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def app():
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st.title("ํค์๋ ๋ถ์")
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user_text = st.text_area("๋ถ์ํ ํ
์คํธ๋ฅผ ๋ถ์ฌ ๋ฃ์ผ์ธ์:", height=300)
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if st.button("ํค์๋ ๋ถ์"):
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# ํค์๋ ์ถ์ถ ๋ก์ง (GPT๋ฅผ ์ฌ์ฉ)
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task_description = "Identify key terms in the text."
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user_prompt = f"{user_text}"
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messages = [
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{"role": "system", "content": task_description},
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{"role": "user", "content": user_prompt},
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]
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response = openai.Completion.create(
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model="gpt-3.5-turbo",
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messages=messages,
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max_tokens=100,
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)
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# GPT๋ก๋ถํฐ ๋ฐ์ ์๋ต์ ํ์ฑํ์ฌ ํค์๋ ์ถ์ถ
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extracted_keywords = response['choices'][0]['message']['content'].split(", ")
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# ๋น ๋ฆฌ์คํธ๋ฅผ ์ด๊ธฐํํ์ฌ ์ฃผ์์ด ๋ฌ๋ฆฐ ํ
์คํธ๋ฅผ ์ ์ฅํฉ๋๋ค.
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annotated_list = []
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# ํ
์คํธ๋ฅผ ๋จ์ด๋ก ๋ถํ ํ๊ณ , ๊ฐ ๋จ์ด๋ฅผ ๊ฒ์ฌํ์ฌ ์ฃผ์์ ๋ต๋๋ค.
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for word in user_text.split():
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if word in extracted_keywords:
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annotated_list.append((word, 'Keyword'))
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else:
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annotated_list.append(word)
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annotated_list.append(" ") # ์๋์ ๊ณต๋ฐฑ์ ๋ณต์ํฉ๋๋ค.
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# ์ฃผ์์ด ๋ฌ๋ฆฐ ํ
์คํธ๋ฅผ ์ถ๋ ฅํฉ๋๋ค.
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annotated_text(*annotated_list)
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# Streamlit ์ฑ ์คํ
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if __name__ == "__main__":
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app()
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