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Runtime error
Runtime error
shravya commited on
Commit Β·
7b4a850
1
Parent(s): bb6a634
branch with all the code before cleanup
Browse files- pages.py +35 -0
- ui/article_recommendation.py +2 -3
- ui/course_learn_suggest_expectations.py +4 -2
- ui/course_lessons_extractor.py +3 -3
- ui/research_paper.py +4 -2
- ui/til_feedback.py +5 -0
- ui_main.py +133 -95
pages.py
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# sidebar.py
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import streamlit as st
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import streamlit_router as sr
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def common_sidebar(router):
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st.sidebar.markdown("# Sidebar Navigation")
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st.sidebar.markdown("---")
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st.sidebar.markdown("### Pages")
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if st.sidebar.button("Home"):
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router.redirect(*router.build('/'))
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if st.sidebar.button("TIL Feedback"):
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router.redirect(*router.build('/feedback'))
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if st.sidebar.button("Course Suggester"):
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router.redirect(*router.build('/course_suggester'))
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if st.sidebar.button("Course Lesson Extractor"):
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router.redirect(*router.build('/lessons_extractor'))
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if st.sidebar.button("Article Recommender"):
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router.redirect(*router.build('/article_recommendor'))
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if st.sidebar.button("Recent Article Suggester"):
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router.redirect(*router.build('/research_article_suggester'))
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def with_sidebar(func):
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def wrapper(*args, **kwargs):
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from ui_main import router # Import router from the main file
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current_route = st.query_params.get("route", [""])[0]
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if current_route in ['feedback', 'course_suggester', 'lessons_extractor', 'article_recommendor', 'research_article_suggester']:
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common_sidebar(router)
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return func(*args, **kwargs)
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return wrapper
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ui/article_recommendation.py
CHANGED
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@@ -2,7 +2,6 @@ from dotenv import load_dotenv
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import json
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import streamlit as st
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import utils.settings as settings
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from workflows.article_suggestion import article_recommendation_crew
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from utils.write_to_json import write_dict_to_json as write_dict_to_json
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load_dotenv()
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)
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def
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page_bg_img = '''
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<style>
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[data-testid="stAppViewContainer"]{
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if st.sidebar.button("β Back to Main Page"):
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st.session_state.page = "main"
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if __name__ == "__main__":
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import json
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import streamlit as st
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import utils.settings as settings
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from workflows.article_suggestion import article_recommendation_crew
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from utils.write_to_json import write_dict_to_json as write_dict_to_json
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load_dotenv()
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)
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def article_recommendor_main():
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page_bg_img = '''
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<style>
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[data-testid="stAppViewContainer"]{
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if st.sidebar.button("β Back to Main Page"):
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st.session_state.page = "main"
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if __name__ == "__main__":
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article_recommendor_main()
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ui/course_learn_suggest_expectations.py
CHANGED
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@@ -4,7 +4,9 @@ from streamlit_extras.stylable_container import stylable_container
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from workflows.courses.expectation_revision import ExpectationRevision
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st.markdown("""
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<style>
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[data-testid="stAppViewContainer"]{
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if __name__ == "__main__":
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from workflows.courses.expectation_revision import ExpectationRevision
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def course_suggester_main():
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st.markdown("""
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<style>
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[data-testid="stAppViewContainer"]{
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if __name__ == "__main__":
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course_suggester_main()
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ui/course_lessons_extractor.py
CHANGED
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from dotenv import load_dotenv
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from workflows.courses.lessons_extractor import LessonsExtractor
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from streamlit_extras.capture import stdout
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load_dotenv()
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finally:
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loop.close()
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asyncio.set_event_loop(None)
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def main():
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page_bg_img = '''
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<style>
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[data-testid="stAppViewContainer"]{
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st.markdown(f"Concpets: {', '.join(lesson['concepts'])}")
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if __name__ == "__main__":
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from dotenv import load_dotenv
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from workflows.courses.lessons_extractor import LessonsExtractor
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from streamlit_extras.capture import stdout
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load_dotenv()
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finally:
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loop.close()
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asyncio.set_event_loop(None)
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def lessons_extractor_main():
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page_bg_img = '''
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<style>
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[data-testid="stAppViewContainer"]{
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st.markdown(f"Concpets: {', '.join(lesson['concepts'])}")
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if __name__ == "__main__":
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lessons_extractor_main()
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ui/research_paper.py
CHANGED
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st.markdown(
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"""
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if st.sidebar.button("β Back to Main Page"):
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st.session_state.page = "main"
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if __name__ == "__main__":
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def research_article_suggester_main():
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st.markdown(
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"""
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if st.sidebar.button("β Back to Main Page"):
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st.session_state.page = "main"
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if __name__ == "__main__":
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research_aricle_suggester_main()
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ui/til_feedback.py
CHANGED
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from langsmith import Client
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from workflows.utils.feedback import Feedback
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load_dotenv()
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def feedback_main():
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page_bg_img = '''
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if key.endswith("_feedback_given"):
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st.session_state[key] = False
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if __name__ == "__main__":
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feedback_main()
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from langsmith import Client
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from workflows.utils.feedback import Feedback
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load_dotenv()
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def feedback_main():
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page_bg_img = '''
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if key.endswith("_feedback_given"):
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st.session_state[key] = False
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if __name__ == "__main__":
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feedback_main()
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ui_main.py
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from dotenv import load_dotenv
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from streamlit_extras.stylable_container import stylable_container
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from ui.article_recommendation import
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from ui.course_lessons_extractor import
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from ui.research_paper import
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from ui.til_feedback import
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from ui.course_learn_suggest_expectations import
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import math
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import streamlit as st
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import subprocess
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load_dotenv()
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subprocess.run(["playwright", "install", "chromium"])
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def load_css(file_name):
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with open(file_name) as f:
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return f.read()
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elif st.session_state.page == "research_article_suggester":
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research_article_suggester_main()
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elif st.session_state.page == "feedback":
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feedback_main()
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elif st.session_state.page == "lessons_extractor":
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lessons_extractor_main()
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elif st.session_state.page == "course_suggester":
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course_suggester_main()
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def show_main_page():
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st.set_page_config(page_title='Growthy AI Workflows',
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page_icon='π°', layout="wide")
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page_bg_img = '''
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<style>
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[data-testid="stAppViewContainer"]{
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[data-testid="stToolbar"]{
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right: 2rem;
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}
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</style>
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'''
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st.markdown(page_bg_img, unsafe_allow_html=True)
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css = load_css("ui/main.css")
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st.markdown(f"<style>{css}</style>", unsafe_allow_html=True)
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st.markdown('<div class="main-title">Welcome to Growthy AI Workflows!</div>',
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unsafe_allow_html=True)
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st.markdown("---")
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card_info = [
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{"title": "Article Recommender", "description": "Discover articles tailored to your interests.",
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"key": "article_recommendor", "image": "https://agent.ai/icons/robot.svg"},
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{"title": "Recent Article Suggester", "description": "Get suggestions for recent research articles.",
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"key": "research_article_suggester", "image": "https://agent.ai/icons/data.svg"},
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]
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num_cols = 3
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num_rows = math.ceil(len(card_info) / num_cols)
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col1, col2, col3 = st.columns([1,
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with col2:
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for row in range(num_rows):
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cols = st.columns(num_cols)
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for col in range(num_cols):
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index = row * num_cols + col
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if index < len(card_info):
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card = card_info[index]
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with cols[col]:
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""", unsafe_allow_html=True
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from dotenv import load_dotenv
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from streamlit_extras.stylable_container import stylable_container
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from ui.article_recommendation import article_recommendor_main
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from ui.course_lessons_extractor import lessons_extractor_main
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from ui.research_paper import research_article_suggester_main
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from ui.til_feedback import feedback_main
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from ui.course_learn_suggest_expectations import course_suggester_main
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# from pages import card_main
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import math
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import streamlit as st
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import subprocess
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import streamlit_router as sr
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load_dotenv()
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subprocess.run(["playwright", "install", "chromium"])
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st.set_page_config(page_title='Growthy AI Workflows', page_icon='π°',layout="wide")
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def load_css(file_name):
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with open(file_name) as f:
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return f.read()
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def common_sidebar():
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st.sidebar.markdown("# Sidebar Navigation")
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st.sidebar.markdown("---")
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st.sidebar.markdown("### Pages")
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st.sidebar.button("Home", on_click=lambda: router.redirect(*router.build("show_main_page")))
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st.sidebar.button("TIL Feedback", on_click=lambda: router.redirect(*router.build("feedback_main_wrapper")))
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st.sidebar.button("Course Suggester", on_click=lambda: router.redirect(*router.build("course_suggester_main_wrapper")))
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st.sidebar.button("Course Lesson Extractor", on_click=lambda: router.redirect(*router.build("lessons_extractor_main_wrapper")))
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st.sidebar.button("Article Recommender", on_click=lambda: router.redirect(*router.build("article_recommendor_main_wrapper")))
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st.sidebar.button("Recent Article Suggester", on_click=lambda: router.redirect(*router.build("research_article_suggester_main_wrapper")))
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def show_main_page():
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page_bg_img = '''
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<style>
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[data-testid="stAppViewContainer"]{
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[data-testid="stToolbar"]{
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right: 2rem;
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}
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[data-testid="column"] {
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text-align: center;
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}
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</style>
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'''
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st.markdown(page_bg_img, unsafe_allow_html=True)
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css = load_css("ui/main.css")
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st.markdown(f"<style>{css}</style>", unsafe_allow_html=True)
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st.markdown('<div class="main-title">Welcome to Growthy AI Workflows!</div>', unsafe_allow_html=True)
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| 62 |
st.markdown("---")
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| 63 |
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| 64 |
+
# card_info = [
|
| 65 |
+
# {"title": "TIL Feedback", "description": "Provide your valuable feedback.", "key": "feedback_main_wrapper","image":"https://agent.ai/icons/search.svg"},
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| 66 |
+
# {"title": "Course Suggester", "description": "Get suggestions for courses", "key": "course_suggester_main_wrapper","image":"https://agent.ai/icons/prospecting.svg"},
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| 67 |
+
# {"title": "Course Lesson Extractor", "description": "Extract lessons for a given course", "key": "lessons_extractor_main_wrapper","image":"https://agent.ai/icons/business-analyst.svg"},
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| 68 |
+
# {"title": "Article Recommender", "description": "Discover articles tailored to your interests.", "key": "article_recommendor_main_wrapper","image":"https://agent.ai/icons/robot.svg"},
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| 69 |
+
# {"title": "Recent Article Suggester", "description": "Get suggestions for recent research articles.", "key": "research_article_suggester_main_wrapper","image":"https://agent.ai/icons/data.svg"},
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| 70 |
+
|
| 71 |
+
# ]
|
| 72 |
card_info = [
|
| 73 |
+
{"title": "TIL Feedback", "description": "Provide your valuable feedback.", "key": "feedback_main_wrapper", "image": "π"},
|
| 74 |
+
{"title": "Course Suggester", "description": "Get suggestions for courses", "key": "course_suggester_main_wrapper", "image": "π"},
|
| 75 |
+
{"title": "Course Lesson Extractor", "description": "Extract lessons for a given course", "key": "lessons_extractor_main_wrapper", "image": "π"},
|
| 76 |
+
{"title": "Article Recommender", "description": "Discover articles tailored to your interests.", "key": "article_recommendor_main_wrapper", "image": "π°"},
|
| 77 |
+
{"title": "Recent Article Suggester", "description": "Get suggestions for recent research articles.", "key": "research_article_suggester_main_wrapper", "image": "π"},
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| 78 |
+
]
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|
| 79 |
|
| 80 |
num_cols = 3
|
| 81 |
num_rows = math.ceil(len(card_info) / num_cols)
|
| 82 |
|
| 83 |
+
col1, col2, col3 = st.columns([1,8,1])
|
| 84 |
|
| 85 |
with col2:
|
| 86 |
for row in range(num_rows):
|
| 87 |
+
cols = st.columns(num_cols,gap="large")
|
| 88 |
for col in range(num_cols):
|
| 89 |
index = row * num_cols + col
|
| 90 |
if index < len(card_info):
|
| 91 |
card = card_info[index]
|
| 92 |
with cols[col]:
|
| 93 |
+
with st.container(height=280,border=False):
|
| 94 |
+
with stylable_container(
|
| 95 |
+
key="inside_container_with_border",
|
| 96 |
+
|
| 97 |
+
css_styles="""
|
| 98 |
+
{
|
| 99 |
+
background-color: #e9eaec;
|
| 100 |
+
border-radius: 10px;
|
| 101 |
+
box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.1);
|
| 102 |
+
# padding:10px;
|
| 103 |
+
display: flex;
|
| 104 |
+
flex-direction: row;
|
| 105 |
+
flex-wrap: wrap;
|
| 106 |
+
align-items: center;
|
| 107 |
+
justify-content: center;
|
| 108 |
+
border: 1px solid #C0C0C0;
|
| 109 |
+
text-align: center;
|
| 110 |
+
margin-bottom: 10px;
|
| 111 |
+
} """,
|
| 112 |
+
):
|
| 113 |
+
# with st.container():
|
| 114 |
+
st.markdown(
|
| 115 |
+
f"""
|
| 116 |
+
<div style="
|
| 117 |
+
font-size: 4rem;
|
| 118 |
+
margin-bottom: 10px;
|
| 119 |
+
">
|
| 120 |
+
{card['image']}
|
| 121 |
+
</div>
|
| 122 |
+
""", unsafe_allow_html=True
|
| 123 |
+
)
|
| 124 |
+
st.markdown(
|
| 125 |
+
f"""
|
| 126 |
+
<div style=" display: flex; flex-wrap:wrap; flex-direction: column; text-align: center; justify-content: center; align-items: center">
|
| 127 |
+
<span style="font-weight:900; font-size: 24px;"> {card["title"]}</span>
|
| 128 |
+
<p class="styled-description">{card["description"]}</p>
|
| 129 |
+
</div>
|
| 130 |
+
""", unsafe_allow_html=True
|
| 131 |
+
)
|
| 132 |
+
if st.button("Explore", key=card["key"]):
|
| 133 |
+
router.redirect(*router.build(f"{card['key']}"))
|
| 134 |
+
# st.experimental_rerun()
|
| 135 |
+
# st.session_state.page = card["key"]
|
| 136 |
+
|
| 137 |
+
st.markdown(
|
| 138 |
+
"""
|
| 139 |
+
<style>
|
| 140 |
+
# [data-testid="stImage"] img {
|
| 141 |
+
# padding:10px;
|
| 142 |
+
# height: 100px;
|
| 143 |
+
# width: 100px;
|
| 144 |
+
# border-radius: 50%;
|
| 145 |
+
# border: 2px solid white;
|
| 146 |
+
|
| 147 |
+
# }
|
| 148 |
+
|
| 149 |
+
[data-testid="column"] div[data-testid="column"]{
|
| 150 |
+
margin: 10px;
|
| 151 |
+
}
|
| 152 |
+
</style>
|
| 153 |
""", unsafe_allow_html=True
|
| 154 |
+
)
|
| 155 |
+
|
| 156 |
+
# Wrapping each main page function to include the common sidebar
|
| 157 |
+
def feedback_main_wrapper():
|
| 158 |
+
common_sidebar()
|
| 159 |
+
feedback_main()
|
| 160 |
+
|
| 161 |
+
def course_suggester_main_wrapper():
|
| 162 |
+
common_sidebar()
|
| 163 |
+
course_suggester_main()
|
| 164 |
+
|
| 165 |
+
def lessons_extractor_main_wrapper():
|
| 166 |
+
common_sidebar()
|
| 167 |
+
lessons_extractor_main()
|
| 168 |
+
|
| 169 |
+
def article_recommendor_main_wrapper():
|
| 170 |
+
common_sidebar()
|
| 171 |
+
article_recommendor_main()
|
| 172 |
+
|
| 173 |
+
def research_article_suggester_main_wrapper():
|
| 174 |
+
common_sidebar()
|
| 175 |
+
research_article_suggester_main()
|
| 176 |
+
|
| 177 |
+
router = sr.StreamlitRouter()
|
| 178 |
+
|
| 179 |
+
router.register(show_main_page, '/')
|
| 180 |
+
router.register(feedback_main_wrapper, '/feedback', methods=['GET'])
|
| 181 |
+
router.register(course_suggester_main_wrapper, '/course_suggester')
|
| 182 |
+
router.register(lessons_extractor_main_wrapper, '/lessons_extractor')
|
| 183 |
+
router.register(article_recommendor_main_wrapper, '/article_recommendor')
|
| 184 |
+
router.register(research_article_suggester_main_wrapper, '/research_article_suggester')
|
| 185 |
+
|
| 186 |
+
router.serve()
|