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import streamlit as st
st.set_page_config(
page_title="Sentiment Analysis",
page_icon="💬",
layout="wide"
)
st.title("Sentiment Analysis Service")
st.markdown("### Status: Coming Week 2")
st.info("This service will be available after Week 2 development")
col1, col2 = st.columns([2, 1])
with col1:
st.markdown("""
## What This Service Will Do
Analyze sentiment of text using fine-tuned BERT model.
**Capabilities:**
- Positive, Negative, Neutral classification
- Confidence scores
- Batch processing support
- Multi-language support
## Technical Implementation
**Model**: DistilBERT (Fine-tuned)
- Base: distilbert-base-uncased
- Fine-tuned on IMDB dataset
- 6 transformer layers
**Features**:
- Real-time inference
- API endpoints
- Batch processing
- Caching for speed
""")
with col2:
st.markdown("### Demo UI Preview")
text_input = st.text_area(
"Enter text to analyze",
placeholder="Type or paste text here...",
disabled=True,
height=150
)
if st.button("Analyze Sentiment", disabled=True):
st.warning("Service will be available in Week 2")
st.markdown("---")
st.info("Results will appear here")
st.markdown("---")
st.caption("Coming in Week 2") |