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Update app.py
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app.py
CHANGED
@@ -6,7 +6,6 @@ from langchain_openai import ChatOpenAI
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from langchain_anthropic import ChatAnthropic
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from langchain_google_genai import ChatGoogleGenerativeAI
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import streamlit.components.v1 as components
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PROMPT = """
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1. 課題: ユーザーが報告した感情とその日の計画に直接関連するユニークなモチベーショナルまたはリフレクティブな引用を生成します。
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@@ -50,16 +49,7 @@ def init_chain():
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output_parser = StrOutputParser()
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chain = prompt | llm | output_parser
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return chain
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def send_height():
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st.components.v1.html("""
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<script>
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window.onload = () => {
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const height = document.body.scrollHeight;
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window.parent.postMessage({ type: 'resize', height: height }, '*');
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};
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</script>
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""", height=0)
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def main():
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@@ -68,7 +58,6 @@ def main():
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st.markdown("""<style>.st-emotion-cache-15ecox0 { display: none !important; }
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@media (max-width: 50.5rem) {.st-emotion-cache-13ln4jf {max-width: calc(0rem + 100vw);}}
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</style>""",unsafe_allow_html=True,)
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send_height()
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chain = init_chain()
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if chain:
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feeling = st.selectbox(
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from langchain_anthropic import ChatAnthropic
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from langchain_google_genai import ChatGoogleGenerativeAI
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PROMPT = """
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1. 課題: ユーザーが報告した感情とその日の計画に直接関連するユニークなモチベーショナルまたはリフレクティブな引用を生成します。
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output_parser = StrOutputParser()
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chain = prompt | llm | output_parser
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return chain
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def main():
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st.markdown("""<style>.st-emotion-cache-15ecox0 { display: none !important; }
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@media (max-width: 50.5rem) {.st-emotion-cache-13ln4jf {max-width: calc(0rem + 100vw);}}
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</style>""",unsafe_allow_html=True,)
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chain = init_chain()
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if chain:
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feeling = st.selectbox(
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