| import streamlit as st |
| import json |
| from scorer import IntroductionScorer |
|
|
| st.set_page_config(page_title="Intro Scorer", layout="wide") |
|
|
| st.title(" Introduction Scoring System") |
| st.write("Enter your speech transcript and duration to get a detailed rubric score.") |
|
|
| with st.form("score_form"): |
| transcript = st.text_area("Transcript", height=200, placeholder="Hello, my name is...") |
| duration = st.number_input("Duration (seconds)", min_value=0, value=0) |
| submitted = st.form_submit_button("Analyze Score") |
|
|
| if submitted and transcript: |
| with st.spinner("Analyzing... (Loading AI models might take a moment)"): |
| scorer = IntroductionScorer(transcript, duration) |
| results = scorer.calculate_overall_score() |
| |
| st.metric(label="Total Score", value=f"{results['Total Score']} / 100") |
| |
| st.subheader("Detailed Breakdown") |
| breakdown = results['Breakdown'] |
| |
| for category, data in breakdown.items(): |
| with st.expander(f"{category} (Score: {data['score']})"): |
| st.write(f"**Feedback:** {data['feedback']}") |
| st.progress(data['score'] / (data.get('max', 10) if data.get('max') else 15)) |
|
|
| st.subheader("Raw JSON Data") |
| st.json(results) |
