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# app.py | |
import streamlit as st | |
from learning_path_model import LearningPathModel | |
# Initialize the learning path model | |
model = LearningPathModel() | |
# Sample content data (replace with actual data) | |
content_data = [ | |
{"id": 1, "title": "Intro to Python", "description": "Learn the basics of Python programming."}, | |
{"id": 2, "title": "Data Science with Python", "description": "Advanced data science techniques using Python."}, | |
{"id": 3, "title": "Machine Learning", "description": "An introduction to machine learning concepts and algorithms."}, | |
] | |
st.title("Personalized Learning Path Generator") | |
# User input | |
user_input = st.text_area("Describe your current knowledge level and what you want to learn:", height=150) | |
if st.button("Generate Learning Path"): | |
if user_input: | |
# Generate recommendations | |
recommendations = model.recommend_learning_path(user_input, content_data) | |
st.subheader("Recommended Learning Path") | |
for rec in recommendations: | |
st.write(f"**{rec['title']}**") | |
st.write(f"{rec['description']}") | |
summary = model.summarize_content(rec['description']) | |
st.write(f"**Summary:** {summary}") | |
else: | |
st.error("Please enter a description of your current knowledge and learning goals.") | |