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Update app.py
Browse files
app.py
CHANGED
@@ -2,31 +2,126 @@ import streamlit as st
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st.set_page_config(page_title="HAERAE Open Research Questions", layout="wide")
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example_question = """
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ํ๊ตญ์ ๋ณด์ ์ ๋ฌธ๊ฐ๊ฐ ๊ณ ๋ํ๋ ๋ฐ์ดํฐ ๋ณดํธ ์์คํ
์ ๊ฐ๋ฐํ๊ณ ์์ต๋๋ค. ์ด ์์คํ
์ 3์ฐจ์ ๊ธฐํํ์ ์ ๊ธ ๋ฉ์ปค๋์ฆ์ ์ฌ์ฉํ๋๋ฐ, ์ ๊ธ ์ฅ์น๋ ์๋ฟ ๋ชจ์์ผ๋ก ๋์ด ์๊ณ , ๋ฐ๋ฉด์ ๋ฐ์ง๋ฆ์ 6cm, ๋์ด๋ 8cm์
๋๋ค. ์ด ์๋ฟ ๋ชจ์์ ์ ๊ธ ์ฅ์น์๋ ์ํต ๋ชจ์์ ์ด์ ๊ฐ ๋ฑ ๋ง๊ฒ ๋ค์ด๊ฐ๊ฒ ์ค๊ณ๋์ด ์์ต๋๋ค.
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@@ -50,38 +145,17 @@ example_question = """
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st.code(example_question, language="markdown")
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st.header("
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st.write(""
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""
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st.
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st.write("""
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- Contribute to advancing Korean language model research
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- Gain access to a large, high-quality dataset of math instructions
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- Collaborate with HAERAE researchers
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- Receive recognition in the field of NLP and math education
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- Potential for co-authorship on related publications
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""")
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st.header("Contact Us")
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st.write("""
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For more information or to submit your results, please contact us at:
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[Your contact information or a link to a submission form]
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""")
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st.sidebar.title("About HAERAE")
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st.sidebar.info("""
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HAERAE is a non-profit research lab dedicated to advancing the field of
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Korean language model interpretability and evaluation. Our work focuses on
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creating insightful benchmarks and tools to push the boundaries of NLP research.
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""")
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st.set_page_config(page_title="HAERAE Open Research Questions", layout="wide")
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# Language selection
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lang = st.radio("Language / ์ธ์ด", ["English", "ํ๊ตญ์ด"])
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# Content in both languages
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content = {
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"English": {
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"title": "HAERAE Open Research Questions",
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"intro": """
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HAERAE is a non-profit research lab focused on the interpretability and evaluation of Korean language models.
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Our mission is to advance the field with insightful benchmarks and tools. Below is an overview of our projects.
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We've been doing most of our projects internally, but for those that have been unsolvable,
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we are planning to open them to get help from the open-source community.
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""",
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"challenge_title": "HAERAE-Math Challenge",
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"challenge_desc": """
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Today we are introducing our first challenge: HAERAE-Math. We've created high-quality instructions on math
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but don't have an idea on how to generate high-quality answers for them. We are looking for solutions that
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use open-source models with openly available licenses.
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We have created a total of 20,000 instructions already and are generating more. We've opened up a preview
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of 50 of them in this link: [HAERAE-Math Samples](https://huggingface.co/datasets/HAERAE-HUB/HAERAE-Math-samples)
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For those who generate answers for the 50 and share the methodology/results with us, we'll share the
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remaining instructions and credit for the resulting dataset.
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""",
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"example_title": "Example Question",
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"how_to_title": "How to Participate",
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"how_to": """
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1. Access the 50 sample questions from the provided Hugging Face dataset link.
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2. Generate high-quality answers for these questions using open-source models.
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3. Document your methodology and results.
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4. Share your findings with us through [contact information or submission form].
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5. If your approach is promising, we'll provide access to the full dataset of 20,000 instructions.
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6. Collaborate with us to refine and improve the answer generation process.
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7. Receive credit as a contributor to the final HAERAE-Math dataset.
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""",
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"why_title": "Why Participate?",
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"why": """
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- Contribute to advancing Korean language model research
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- Gain access to a large, high-quality dataset of math instructions
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- Collaborate with HAERAE researchers
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- Receive recognition in the field of NLP and math education
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- Potential for co-authorship on related publications
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""",
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"contact_title": "Contact Us",
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"contact": """
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For more information or to submit your results, please contact us at:
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[spthsrbwls123@yonsei.ac.kr](spthsrbwls123@yonsei.ac.kr)
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""",
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"sidebar_title": "About HAERAE",
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"sidebar_content": """
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HAERAE is a non-profit research lab dedicated to advancing the field of
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Korean language model interpretability and evaluation. Our work focuses on
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creating insightful benchmarks and tools to push the boundaries of NLP research.
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"""
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},
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"ํ๊ตญ์ด": {
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"title": "HAERAE ๊ณต๊ฐ ์ฐ๊ตฌ ์ง๋ฌธ",
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"intro": """
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HAERAE๋ ํ๊ตญ์ด ์ธ์ด ๋ชจ๋ธ์ ํด์ ๊ฐ๋ฅ์ฑ๊ณผ ํ๊ฐ์ ์ค์ ์ ๋ ๋น์๋ฆฌ ์ฐ๊ตฌ์์
๋๋ค.
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์ฐ๋ฆฌ์ ๋ฏธ์
์ ํต์ฐฐ๋ ฅ ์๋ ๋ฒค์น๋งํฌ์ ๋๊ตฌ๋ฅผ ํตํด ์ด ๋ถ์ผ๋ฅผ ๋ฐ์ ์ํค๋ ๊ฒ์
๋๋ค. ๋ค์์ ์ฐ๋ฆฌ ํ๋ก์ ํธ์ ๊ฐ์์
๋๋ค.
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๋๋ถ๋ถ์ ํ๋ก์ ํธ๋ฅผ ๋ด๋ถ์ ์ผ๋ก ์ํํด ์์ง๋ง, ํด๊ฒฐํ๊ธฐ ์ด๋ ค์ด ๋ฌธ์ ๋ค์ ๋ํด์๋
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์คํ ์์ค ์ปค๋ฎค๋ํฐ์ ๋์์ ๋ฐ๊ณ ์ ๊ณต๊ฐํ ๊ณํ์
๋๋ค.
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""",
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"challenge_title": "HAERAE-Math ์ฑ๋ฆฐ์ง",
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"challenge_desc": """
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์ค๋ ์ฐ๋ฆฌ๋ ์ฒซ ๋ฒ์งธ ์ฑ๋ฆฐ์ง์ธ HAERAE-Math๋ฅผ ์๊ฐํฉ๋๋ค. ์ฐ๋ฆฌ๋ ์ํ์ ๊ดํ ๊ณ ํ์ง ์ง์๋ฌธ์ ๋ง๋ค์์ง๋ง
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์ด์ ๋ํ ๊ณ ํ์ง ๋ต๋ณ์ ์์ฑํ๋ ๋ฐฉ๋ฒ์ ๋ํ ์์ด๋์ด๊ฐ ์์ต๋๋ค. ์ฐ๋ฆฌ๋ ๊ณต๊ฐ์ ์ผ๋ก ์ฌ์ฉ ๊ฐ๋ฅํ ๋ผ์ด์ ์ค๋ฅผ ๊ฐ์ง
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์คํ ์์ค ๋ชจ๋ธ์ ์ฌ์ฉํ๋ ์๋ฃจ์
์ ์ฐพ๊ณ ์์ต๋๋ค.
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์ฐ๋ฆฌ๋ ์ด๋ฏธ ์ด 20,000๊ฐ์ ์ง์๋ฌธ์ ๋ง๋ค์๊ณ ๋ ๋ง์ด ์์ฑํ๊ณ ์์ต๋๋ค. ์ฐ๋ฆฌ๋ ์ด ์ค 50๊ฐ์ ๋ฏธ๋ฆฌ๋ณด๊ธฐ๋ฅผ
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๋ค์ ๋งํฌ์์ ๊ณต๊ฐํ์ต๋๋ค: [HAERAE-Math ์ํ](https://huggingface.co/datasets/HAERAE-HUB/HAERAE-Math-samples)
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50๊ฐ์ ๋ํ ๋ต๋ณ์ ์์ฑํ๊ณ ๋ฐฉ๋ฒ๋ก /๊ฒฐ๊ณผ๋ฅผ ์ฐ๋ฆฌ์ ๊ณต์ ํ๋ ๋ถ๋ค์๊ฒ๋ ๋๋จธ์ง ์ง์๋ฌธ์ ๊ณต์ ํ๊ณ
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์ต์ข
๋ฐ์ดํฐ์
์ ๋ํ ํฌ๋ ๋ง์ ๊ณต์ ํ ๊ฒ์
๋๋ค.
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""",
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"example_title": "์์ ์ง๋ฌธ",
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"how_to_title": "์ฐธ์ฌ ๋ฐฉ๋ฒ",
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"how_to": """
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1. ์ ๊ณต๋ Hugging Face ๋ฐ์ดํฐ์
๋งํฌ์์ 50๊ฐ์ ์ํ ์ง๋ฌธ์ ์ ๊ทผํฉ๋๋ค.
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2. ์คํ ์์ค ๋ชจ๋ธ์ ์ฌ์ฉํ์ฌ ์ด ์ง๋ฌธ๋ค์ ๋ํ ๊ณ ํ์ง ๋ต๋ณ์ ์์ฑํฉ๋๋ค.
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3. ๋ฐฉ๋ฒ๋ก ๊ณผ ๊ฒฐ๊ณผ๋ฅผ ๋ฌธ์ํํฉ๋๋ค.
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4. [์ฐ๋ฝ์ฒ ์ ๋ณด ๋๋ ์ ์ถ ์์]์ ํตํด ๊ทํ์ ๊ฒฐ๊ณผ๋ฅผ ์ฐ๋ฆฌ์ ๊ณต์ ํฉ๋๋ค.
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5. ๊ทํ์ ์ ๊ทผ ๋ฐฉ์์ด ์ ๋งํ๋ค๋ฉด, 20,000๊ฐ์ ์ ์ฒด ์ง์๋ฌธ ๋ฐ์ดํฐ์
์ ๋ํ ์ ๊ทผ ๊ถํ์ ์ ๊ณตํ ๊ฒ์
๋๋ค.
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6. ๋ต๋ณ ์์ฑ ๊ณผ์ ์ ๊ฐ์ ํ๊ณ ๋ฐ์ ์ํค๊ธฐ ์ํด ์ฐ๋ฆฌ์ ํ๋ ฅํฉ๋๋ค.
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7. ์ต์ข
HAERAE-Math ๋ฐ์ดํฐ์
์ ๊ธฐ์ฌ์๋ก ์ธ์ ๋ฐ์ต๋๋ค.
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""",
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"why_title": "์ ์ฐธ์ฌํด์ผ ํ๋์?",
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"why": """
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- ํ๊ตญ์ด ์ธ์ด ๋ชจ๋ธ ์ฐ๊ตฌ ๋ฐ์ ์ ๊ธฐ์ฌ
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- ๋๊ท๋ชจ์ ๊ณ ํ์ง ์ํ ์ง์๋ฌธ ๋ฐ์ดํฐ์
์ ์ ๊ทผ
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- HAERAE ์ฐ๊ตฌ์๋ค๊ณผ ํ๋ ฅ
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- NLP ๋ฐ ์ํ ๊ต์ก ๋ถ์ผ์์ ์ธ์ ๋ฐ์ ๊ธฐํ
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- ๊ด๋ จ ์ถํ๋ฌผ์ ๊ณต๋ ์ ์๊ฐ ๋ ๊ฐ๋ฅ์ฑ
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""",
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"contact_title": "์ฐ๋ฝ์ฒ",
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"contact": """
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๋ ๋ง์ ์ ๋ณด๋ฅผ ์ํ์๊ฑฐ๋ ๊ฒฐ๊ณผ๋ฅผ ์ ์ถํ๋ ค๋ฉด ๋ค์ ์ฐ๋ฝ์ฒ๋ก ๋ฌธ์ํด ์ฃผ์ธ์:
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[spthsrbwls123@yonsei.ac.kr](spthsrbwls123@yonsei.ac.kr)
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""",
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"sidebar_title": "HAERAE ์๊ฐ",
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"sidebar_content": """
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HAERAE๋ ํ๊ตญ์ด ์ธ์ด ๋ชจ๋ธ์ ํด์ ๊ฐ๋ฅ์ฑ๊ณผ ํ๊ฐ ๋ถ์ผ๋ฅผ ๋ฐ์ ์ํค๋ ๋ฐ ์ ๋
ํ๋ ๋น์๋ฆฌ ์ฐ๊ตฌ์์
๋๋ค.
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์ฐ๋ฆฌ์ ์ฐ๊ตฌ๋ NLP ์ฐ๊ตฌ์ ๊ฒฝ๊ณ๋ฅผ ๋ํ๊ธฐ ์ํ ํต์ฐฐ๋ ฅ ์๋ ๋ฒค์น๋งํฌ์ ๋๊ตฌ๋ฅผ ๋ง๋๋ ๋ฐ ์ค์ ์ ๋ก๋๋ค.
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"""
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}
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}
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# Main content
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st.title(content[lang]["title"])
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st.write(content[lang]["intro"])
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st.header(content[lang]["challenge_title"])
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st.write(content[lang]["challenge_desc"])
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st.subheader(content[lang]["example_title"])
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example_question = """
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ํ๊ตญ์ ๋ณด์ ์ ๋ฌธ๊ฐ๊ฐ ๊ณ ๋ํ๋ ๋ฐ์ดํฐ ๋ณดํธ ์์คํ
์ ๊ฐ๋ฐํ๊ณ ์์ต๋๋ค. ์ด ์์คํ
์ 3์ฐจ์ ๊ธฐํํ์ ์ ๊ธ ๋ฉ์ปค๋์ฆ์ ์ฌ์ฉํ๋๋ฐ, ์ ๊ธ ์ฅ์น๋ ์๋ฟ ๋ชจ์์ผ๋ก ๋์ด ์๊ณ , ๋ฐ๋ฉด์ ๋ฐ์ง๋ฆ์ 6cm, ๋์ด๋ 8cm์
๋๋ค. ์ด ์๋ฟ ๋ชจ์์ ์ ๊ธ ์ฅ์น์๋ ์ํต ๋ชจ์์ ์ด์ ๊ฐ ๋ฑ ๋ง๊ฒ ๋ค์ด๊ฐ๊ฒ ์ค๊ณ๋์ด ์์ต๋๋ค.
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st.code(example_question, language="markdown")
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st.header(content[lang]["how_to_title"])
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st.write(content[lang]["how_to"])
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st.header(content[lang]["why_title"])
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st.write(content[lang]["why"])
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st.header(content[lang]["contact_title"])
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st.write(content[lang]["contact"])
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st.sidebar.title(content[lang]["sidebar_title"])
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st.sidebar.info(content[lang]["sidebar_content"])
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